CN114764180A

CN114764180A - Focusing method and focusing system for object to be measured, equipment and storage medium

Info

Publication number: CN114764180A
Application number: CN202011636597.0A
Authority: CN
Inventors: 陈鲁; 吕肃; 李青格乐; 张嵩
Original assignee: Shenzhen Zhongke Feice Technology Co Ltd
Current assignee: Shenzhen Zhongke Feice Technology Co Ltd
Priority date: 2020-12-31
Filing date: 2020-12-31
Publication date: 2022-07-19
Anticipated expiration: 2040-12-31
Also published as: CN114764180B

Abstract

A focusing method of an object to be measured, a focusing system, equipment and a storage medium are provided, wherein the focusing method comprises the following steps: obtaining calibration images of an object to be measured at different focusing heights; acquiring a distribution relation between a first focusing degree parameter and a focusing height of each layer of calibration graph according to the calibration image, wherein the distribution relation is Gaussian distribution; respectively carrying out weighting processing after logarithm is solved on the distribution relation of the multilayer calibration graphs, and obtaining a calibration curve which is in a linear relation with the focusing height; acquiring an optimal focusing height reference value; shooting to obtain a to-be-detected image of the to-be-detected object; acquiring a second focusing power parameter of each layer of calibration graph according to the image to be detected; respectively carrying out logarithm solving on the second focusing power parameter of each layer of calibration graph in the image to be tested, and then carrying out weighting processing to obtain a test difference value; and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height as the defocusing amount of the image to be detected. The invention can improve focusing speed while ensuring focusing precision.

Description

Focusing method and focusing system for object to be measured, equipment and storage medium

Technical Field

The embodiment of the invention relates to the field of measurement, in particular to a focusing method, a focusing system, equipment and a storage medium of an object to be measured.

Background

In the application of measurement based on high-magnification microscopic imaging, the accuracy of focusing often directly affects the measurement precision, for example, in the measurement of overlay error, even if the difference is only dozens of nanometers at different heights, the measured overlay error has difference. On the other hand, the focusing speed directly affects the measurement efficiency, and the too long focusing time will cause the measurement efficiency to be lower.

The traditional focusing algorithm generally has two types, one is to use an imaging mode to determine the optimal focusing height based on images taken at different heights by using the response of the image focusing power (e.g. image sharpness) to the height, but this method usually needs to take multiple images at a smaller step size in order to achieve higher measurement accuracy, and has long data acquisition time and low measurement efficiency. The other is to measure the distance of the object from the lens in a non-imaging manner (e.g. using an interferometric manner), but this method needs to be equipped with an additional optical system (e.g. an interferometric system), which is costly and the overall system is complex.

Disclosure of Invention

The embodiment of the invention aims to provide a focusing method, a focusing system, equipment and a storage medium of an object to be measured, and improve the focusing speed while ensuring the focusing precision.

In order to solve the above problem, an embodiment of the present invention provides a focusing method for an object to be measured, where the object to be measured includes multiple layers of calibration patterns, and the multiple layers of calibration patterns have different heights along a focusing direction, and the focusing method includes: obtaining calibration images of the object to be measured at different focusing heights along the focusing direction; acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution; respectively carrying out weighting processing after solving logarithms of distribution relations corresponding to the multiple layers of calibration graphs to obtain calibration curves, wherein the calibration curves and the focusing heights are in a linear relation; acquiring an optimal focusing height reference value of the multilayer calibration graph; shooting and obtaining a to-be-detected image of the to-be-detected object; acquiring a second focusing power parameter of each layer of calibration graph in the image to be detected according to the image to be detected; respectively calculating the logarithm of the second focusing power parameter of each layer of calibration graph in the image to be tested, and then carrying out weighting processing to obtain a test difference value; and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height to be used as the defocusing amount of the image to be detected.

Correspondingly, an embodiment of the present invention further provides a focusing system for an object to be measured, where the object to be measured includes a plurality of layers of calibration patterns, and the plurality of layers of calibration patterns have different heights along a focusing direction, and the focusing system includes: the image acquisition module is used for acquiring calibration images of the object to be measured at different focusing heights along the focusing direction and shooting and acquiring the image to be measured of the object to be measured; the first image processing module is used for acquiring the distribution relation between the first focusing degree parameter and the focusing height of each layer of the calibration graph according to the calibration image, wherein the distribution relation is Gaussian distribution; the first data processing module is used for acquiring the distribution relation between the first focusing degree parameter and the focusing height of each layer of the calibration graph according to the calibration image, wherein the distribution relation is Gaussian distribution; the second data processing module is used for acquiring the optimal focusing height reference value of the multilayer calibration graph; the second image processing module is used for acquiring a second focusing power parameter of each layer of calibration graph in the image to be detected according to the image to be detected; the third data processing module is used for respectively carrying out logarithm calculation on the second focusing power parameter of each layer of calibration graph in the image to be tested and then carrying out weighting processing on the obtained logarithm calculation result to obtain a test difference value; and the fourth data processing module is used for determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height to be used as the defocusing amount of the image to be detected.

Accordingly, an embodiment of the present invention further provides an apparatus, which includes at least one memory and at least one processor, where the memory stores one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the method for focusing an object according to the embodiment of the present invention.

Correspondingly, the embodiment of the present invention further provides a storage medium, where one or more computer instructions are stored, and the one or more computer instructions are used to implement the method for focusing the object to be measured according to the embodiment of the present invention.

Compared with the prior art, the technical scheme of the embodiment of the invention has the following advantages:

in the focusing method provided in the embodiment of the present invention, after calibration images of the object to be measured at different focusing heights are obtained along the focusing direction, the distribution relationship between the first focusing parameter and the focusing height of each layer of the calibration image is obtained according to the calibration images, the distribution relationship is gaussian distribution, and then logarithms are respectively calculated for the distribution relationships corresponding to the plurality of layers of calibration images, and then weighting is performed to obtain a calibration curve having a linear relationship, where the calibration curve is a differential response curve of the first focusing parameter in a logarithmic coordinate system, so that by obtaining the relationship between the first focusing parameter difference and the focusing height in the logarithmic coordinate system in advance, after the image to be measured is obtained by shooting, the second focusing parameter of each layer of the calibration image in the image to be measured is logarithmically calculated respectively, and then weighting is performed to obtain a test difference, the known test difference value is substituted into the calibration curve, so that the actual height of the image to be detected can be obtained, the defocus (focus shift) of the image to be detected can be obtained by calculating the difference value between the optimal focus height reference value and the actual height, and compared with a scheme of shooting a plurality of images under a small step length to determine the optimal focus height reference value and a scheme of determining the optimal focus height reference value by adopting a non-imaging mode (such as an interference mode), the embodiment of the invention can improve the focusing speed while ensuring the focusing accuracy without increasing the cost of additional hardware (such as an interference system).

In the focusing system provided in the embodiment of the present invention, after the calibration images of the object to be measured at different focusing heights are obtained by the image obtaining module along the focusing direction, the first image processing module obtains the distribution relationship between the first focusing parameter and the focusing height of each layer of the calibration graph according to the calibration images, the distribution relationship is gaussian distribution, and then the first data processing module performs logarithm calculation on the distribution relationship corresponding to the plurality of layers of the calibration graphs and performs weighting processing to obtain the calibration curve having a linear relationship, where the calibration curve is the differential response curve of the first focusing parameter in a logarithmic coordinate system, so that after the image to be measured is obtained by shooting by the image obtaining module, the second focusing parameter of each layer of the calibration graph in the image to be measured is obtained by the second image processing module, and the second focusing parameter of each layer of the calibration graph in the image to be measured is obtained by the third data processing module After the logarithm is carried out, the weighting processing is carried out, after a test difference value is obtained, the known test difference value is substituted into the calibration curve through a fourth data processing module, the actual height of the image to be measured can be obtained, and therefore the defocus amount of the image to be measured can be obtained through calculating the difference value between the optimal focusing height reference value and the actual height, compared with a scheme of shooting a plurality of images under a small step length to determine the optimal focusing height reference value and a scheme of determining the optimal focusing height reference value in a non-imaging mode (for example, an interference mode), the embodiment of the invention can improve the focusing speed while guaranteeing the focusing accuracy under the condition that the cost of extra hardware (for example, an interference system) is not increased, and for example, the focusing accuracy can meet the requirement of double micro imaging.

Drawings

FIG. 1 is a flowchart illustrating a method for focusing an object according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a calibration image of the embodiment of step S1 in FIG. 1;

FIG. 3 is a flowchart of an embodiment of step S2 in FIG. 1;

FIG. 4 is a diagram illustrating the distribution of the first degree of focus parameter and the focus height and the calibration curve in the logarithmic coordinate system in the embodiment of step S3 in FIG. 1;

FIG. 5 is a flowchart of an embodiment of step S4 in FIG. 1;

FIG. 6 is a functional block diagram of an embodiment of a focus system for an analyte according to the present invention;

fig. 7 is a hardware structure diagram of an apparatus according to an embodiment of the present invention.

Detailed Description

As is clear from the background art, it is difficult to improve the focusing speed while ensuring the focusing accuracy in the conventional focusing method.

In order to solve the technical problem, an embodiment of the present invention provides a focusing method for an object to be measured, where the object to be measured includes multiple layers of calibration patterns, and the multiple layers of calibration patterns have different heights along a focusing direction, and the focusing method includes: obtaining calibration images of the object to be measured at different focusing heights along the focusing direction; acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution; respectively carrying out weighting processing after solving logarithms of distribution relations corresponding to the multiple layers of calibration graphs to obtain calibration curves, wherein the calibration curves and the focusing heights are in a linear relation; acquiring an optimal focusing height reference value of the multilayer calibration graph; shooting and obtaining a to-be-detected image of the to-be-detected object; acquiring a second focusing power parameter of each layer of calibration graph in the image to be detected according to the image to be detected; respectively calculating the logarithm of the second focusing power parameter of each layer of calibration graph in the image to be tested, and then carrying out weighting processing to obtain a test difference value; and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height to be used as the defocusing amount of the image to be detected.

In the focusing method provided by the embodiment of the invention, the relation between the first focusing degree parameter difference and the focusing height under a logarithmic coordinate system is obtained in advance, after an image to be detected is shot and obtained, the second focusing degree parameter of each layer of calibration graph in the image to be detected is subjected to the weighting processing after the logarithm is respectively solved, the test difference is obtained, the known test difference is substituted into the calibration curve, and the actual height of the image to be detected can be obtained, so that the defocusing amount of the image to be detected can be obtained by calculating the difference between the optimal focusing height reference value and the actual height, compared with the scheme of shooting a plurality of images under a small step length to determine the optimal focusing height reference value and the scheme of determining the optimal focusing height reference value in a non-imaging mode, the embodiment of the invention can ensure the focusing precision under the condition of not increasing extra hardware cost, the focusing speed is increased.

Referring to fig. 1, a flowchart of an embodiment of a method for focusing a test object of the present invention is shown.

In this embodiment, the object to be measured includes a plurality of layers of calibration patterns, and the plurality of layers of calibration patterns have different heights along the focusing direction. In this embodiment, the focusing method includes the following basic steps:

step S1: obtaining calibration images of the object to be measured at different focusing heights along the focusing direction;

step S2: acquiring a distribution relation between a first focusing degree parameter and the focusing height of each layer of the calibration graph according to the calibration image, wherein the distribution relation is Gaussian distribution;

step S3: respectively carrying out weighting processing after logarithm is solved on distribution relations corresponding to the multilayer calibration graphs to obtain calibration curves, wherein the calibration curves and the focusing heights are in a linear relation;

step S4: acquiring an optimal focusing height reference value of the multilayer calibration graph;

step S5: shooting and obtaining a to-be-detected image of the to-be-detected object;

step S6: acquiring a second focusing power parameter of each layer of calibration graph in the image to be detected according to the image to be detected;

step S7: respectively carrying out logarithm solving on the second focusing power parameter of each layer of calibration graph in the image to be tested, and then carrying out weighting processing to obtain a test difference value;

step S8: and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height to be used as the defocusing amount of the image to be detected.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.

Referring to fig. 1 and fig. 2 in combination, fig. 2 is a schematic diagram of a calibration image of an embodiment of step S1 in fig. 1.

Specifically, step S1 is executed to obtain calibration images 110 of the object under different focal heights along the focusing direction.

In this embodiment, the object to be measured (not shown) includes multiple layers of calibration patterns 100, the multiple layers of calibration patterns 100 have different heights along the focusing direction, and calibration images 110 of the object to be measured at different focusing heights are obtained first, so as to prepare for obtaining the distribution relationship between the first focusing degree parameter and the focusing height corresponding to each layer of calibration patterns 100 subsequently.

Specifically, in the focusing direction, the object to be measured is photographed at different focusing heights, and an image of the object to be measured is obtained as a calibration image 110, where the object to be measured includes multiple layers of calibration patterns 100, and the calibration image 110 includes an image of the calibration pattern 100. It should be noted that the fact that the multi-layer calibration patterns 100 have different heights along the focusing direction means that: along the focusing direction, the multilayer calibration pattern 100 is located at different height positions on the object to be measured. That is to say, the multilayer calibration patterns 100 are located on the same object to be measured, and the multilayer calibration patterns 100 are spatially located in different layers along the normal direction of the surface of the object to be measured.

It should be further noted that, for the same calibration image 110, the calibration patterns 100 located at different layers have different focal heights, and therefore, the focal heights of the multiple layers of calibration patterns 100 have different focal heights. As an example, the object to be measured is a wafer (wafer), and the calibration pattern 100 is an overlay mark (overlay mark) pattern, and the overlay mark pattern is spatially located on different layers on the wafer.

As an example, the number of the calibration patterns 100 is two, that is, the object to be measured includes two layers of calibration patterns 100. Specifically, the two layers of calibration patterns 100 are a first layer of calibration pattern 101 and a second layer of calibration pattern 102, respectively, and the first layer of calibration pattern 101 and the second layer of calibration pattern 102 have different heights along the focusing direction. It should be noted that the first layer of calibration patterns 101 and the second layer of calibration patterns 102 may be two adjacent layers of calibration patterns 100, or may be separated by one or more layers of other calibration patterns. It should be further noted that, in other embodiments, the number of the calibration patterns may also be three or four, and the number of the calibration patterns may also be more than four.

Specifically, the step of obtaining the calibration image 110 of the object under different focusing heights along the focusing direction includes: the object to be measured is photographed at different focusing heights to obtain a plurality of calibration images 110, and each calibration image 110 contains an image of the multilayer calibration graph 100. That is, each time one calibration image 110 is captured, the multi-layer calibration pattern 100 is captured at the same time, i.e., the images of the multi-layer calibration pattern 100 are displayed in the same calibration image 110.

In this embodiment, the images of the first layer calibration pattern 101 and the second layer calibration pattern 102 are displayed in the same calibration image 110. On one hand, shooting one calibration image 110 can obtain the first focusing degree parameter of the multilayer calibration image 100 at the same time, and the efficiency of obtaining the first focusing degree parameter is higher, and meanwhile, for the same calibration image 110, shooting the multilayer calibration image 100 at the same focusing height has higher efficiency of obtaining the focusing height, and the focusing height is easier to obtain. Therefore, by making each of the calibration images 110 contain the plurality of layers of the calibration patterns 100, the efficiency of obtaining the first degree of focus parameter and the height of focus of each layer of the calibration patterns 100 in the calibration images 110 is improved.

Correspondingly, in this embodiment, the object to be measured is photographed at different focusing heights by a preset step length, and the calibration image 110 is obtained. The preset step length is not too small and is not too large. If the preset step length is too small, a large number of calibration images 110 need to be shot correspondingly, so that the data acquisition time is long, and the focusing efficiency of the focusing method is low; if the preset step length is too large, the data size is too small correspondingly, and when the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height is obtained according to the calibration image subsequently, the precision of the obtained distribution relation is low, so that the focusing precision is easy to reduce. For this reason, in the present embodiment, the preset step size is 30 nm to 200 nm. For example, the preset step size is 50 nm, 100 nm or 150 nm.

In other embodiments, when multiple layers of calibration patterns cannot be captured in the same calibration image, calibration images of each layer of calibration pattern at different focal heights may also be captured and obtained, and the focal height of each layer of calibration pattern and the first focusing degree parameter corresponding to the focal height may also be obtained.

In this embodiment, the focusing method further includes: an imaging system is provided. Correspondingly, calibration images 110 of the object to be measured at different focusing heights are obtained along the focusing direction through the imaging system. As an example, the imaging system is a microscopic imaging device

With continuing reference to fig. 1 and fig. 2, step S2 is executed to obtain a distribution relationship between the first degree of focus parameter and the focal height of each layer of the calibration graph 100 according to the calibration image 110, where the distribution relationship is a gaussian distribution.

In the process of shooting the calibration graph 100 (i.e. shooting the object to be measured) at different focal heights, the focal height during shooting can be determined, and the first focusing degree parameter can be obtained through the calibration image 110, so that the focal height and the first focusing degree parameter corresponding to the focal height can be obtained. By obtaining the distribution relationship between the first focusing degree parameter and the focusing height corresponding to each layer of the calibration graph 100, the differential response curve of the first focusing degree parameter in the logarithmic coordinate system is obtained in the following. Since the distribution relation is gaussian, the obtained curve can be made to have a linear relation with the focal height by performing a weighting process after obtaining a logarithm of the distribution relation.

Here, the focal height is a shooting height. For example, the focal height is a distance between the object to be measured and an objective lens of the imaging system. It should be further noted that, for the same calibration image 110, the focus heights of the calibration patterns 100 located at different layers have differences, and therefore, each layer of the calibration pattern 100 has a function of the corresponding first degree of focus parameter and the focus height.

The first focus parameter comprises image sharpness, image contrast, image center-to-center distance, image curvature, image autocorrelation, or a gaussian derivative of an image. By adopting the first focusing degree parameters of the types, the distribution relation between the first focusing degree parameters and the focusing height is Gaussian distribution. As an example, the first degree of focus parameter is image sharpness.

Referring to fig. 3 in combination, fig. 3 is a flowchart of an embodiment of step S2. In this embodiment, the step of obtaining the distribution relationship between the first degree of focus parameter and the focal height of each layer of the calibration graph 100 according to the calibration image 110 includes: step S21 is executed to divide each of the calibration images 110 into a plurality of areas 130 (as shown in fig. 2), and each area 130 includes an image of one layer of the calibration graph 100.

Each area 130 comprises an image of a layer of calibration patterns 100, the calibration patterns 100 located in the same area 130 having the same height.

As shown in fig. 2, in this embodiment, taking the object to be measured includes two layers of calibration patterns 100 as an example, the multiple regions 130 are respectively a first region 130a (shown by a dashed line frame in fig. 2) and a second region 130b (shown by a dashed line frame in fig. 2), and the calibration patterns 100 in the first region 130a and the second region 130b are located in different layers, that is, the calibration patterns 100 in the first region 130a and the second region 130b have different heights in the focusing direction.

In this embodiment, the step of obtaining the distribution relationship between the first degree of focus parameter and the focal height of each layer of the calibration graph 100 according to the calibration image 110 further includes: step S22 is executed to calculate first degree-of-focus parameters of each region 130 at different focal heights, and obtain a distribution relationship between the first degree-of-focus parameters and the focal heights.

Specifically, the image sharpness corresponding to the calibration graph 100 in the first region 130a and the second region 130b is expressed by formula (1) and formula (2), respectively,

wherein, G₁(z) is the image sharpness, G, of the first region 130a₂(z) the image sharpness of the second region 130b, z the distance between the test object and the imaging device, a₁、a₂、b₁、b₂、C₁And C₂Are all constant coefficients, and a₁And a₂Are all of Gaussian width, C₁And C₂Are coefficients related to the depth of field of the imaging device.

It should be noted that, since the calibration images 110 of the object under test at different focal heights are obtained by the same imaging system, C is₁＝C₂。

With reference to fig. 1 and fig. 4, step S3 is executed to respectively perform a weighting process after logarithms are calculated for distribution relationships corresponding to the multilayer calibration graph 100, so as to obtain a calibration curve 140, where the calibration curve 140 and the focal height are in a linear relationship.

Fig. 4 is a schematic diagram of the distribution relationship between the first degree of focus parameter and the focal height and the calibration curve 140 in the logarithmic coordinate system in the embodiment of step S3, where the abscissa represents the focal height and the ordinate represents the degree of focus parameter (e.g., image sharpness).

The calibration curve 140 is in a linear relationship with the focusing height, so that after a to-be-measured image of the to-be-measured object is obtained by subsequent shooting, the second focusing power parameter of each layer of calibration graph 100 in the image to be tested is respectively subjected to logarithm processing to obtain a test difference value, the known test difference value is substituted into the calibration curve 140, the actual height of the image to be measured can be obtained, so that by calculating the difference value between the reference value of the optimal focusing height and the actual height, the defocus amount of the image to be measured can be obtained, and compared with the scheme of shooting a plurality of images under a smaller step length to determine the optimal focusing height reference value and the scheme of determining the optimal focusing height reference value in a non-imaging mode, the embodiment can obtain the defocus amount of the image to be measured without increasing extra hardware cost, the focusing speed is improved while the focusing precision is ensured, for example, the focusing precision can meet the requirement of 100 times microscopic imaging.

Each layer of calibration graph 100 has a distribution relationship between the corresponding first focusing degree parameter and the focusing height, so that after the distribution relationship corresponding to the plurality of layers of calibration graphs 100 is logarithmized, each layer of calibration graph 100 corresponds to one curve. For example, as shown in fig. 3, a curve corresponding to the first region 130a is a first curve 131, and a curve corresponding to the second region 130b is a second curve 132.

Specifically, the weighting process includes: providing a plurality of weighted values; weighting is carried out by utilizing each weighted value and the plurality of first focusing degree parameters to obtain a calibration curve 140, and the calibration curve 140 and the focusing height are in a linear relation through the weighted value.

In this embodiment, the number of the calibration graphs 100 is two, and therefore, the weighted values are 1 and-1, that is, the distribution relations corresponding to the two calibration graphs 100 are subjected to logarithm calculation and then subtraction to obtain the calibration curve 140. In other embodiments, when the number of calibration patterns is three, the plurality of weighting values are 1, -1/2, and-1/2, respectively. In other embodiments, when the number of the calibration patterns is four, the weighting values are 1, -1, and-1, respectively.

In this embodiment, in the step of obtaining the calibration curve 140, before respectively logarithm of the distribution relations corresponding to the multilayer calibration graph 100, the method further includes: and respectively performing first normalization processing on the distribution relation corresponding to the multilayer calibration graph 100 by taking the Gaussian width as a normalization coefficient. The normalization is a linear feature transformation which scales the numerical range of the data according to a specific coefficient but does not change the data distribution, and the normalization processing is performed to eliminate the influence of the coefficient and facilitate the processing of the data.

In this embodiment, a in the formula (1)₁And a in formula (2)₂And (6) normalizing.

Therefore, the function S (z) of the calibration curve 140 is expressed by equation (3),

as shown in the formula (3), the calibration curve 140 has a linear relationship with the focal height in a logarithmic coordinate system.

With continued reference to fig. 1, step S4 is executed to obtain the best focus height reference value of the multi-layer calibration pattern 100.

And in the subsequent actual detection process, when the image to be detected of the object to be detected is shot, the reference value of the optimal focusing height is used as the focusing reference position. Specifically, the second focusing power parameters of each layer of calibration graph in the image to be detected are subjected to weighting processing after logarithms are respectively obtained, after a test difference value is obtained, the actual height corresponding to the test difference value is determined by using the calibration curve, and the difference value between the reference value of the optimal focusing height and the actual height is calculated to be used as the defocusing amount of the image to be detected, so that focusing can be achieved according to the defocusing amount, and the defocusing amount is obtained through calculation, so that the focusing accuracy is improved, and the requirement of detection accuracy is further met.

Referring to fig. 5 in combination, fig. 5 is a flowchart of an embodiment of step S4. In this embodiment, the step of obtaining the reference value of the optimal focusing height of the multilayer calibration graph 100 includes: step S41 is executed, and the focusing height corresponding to the maximum value of the first focusing parameter of each layer of the calibration graph 100 is respectively obtained according to the distribution relationship corresponding to each layer of the calibration graph 100.

The distribution relationship between the first focusing degree parameter and the focusing height is gaussian distribution, so that the focusing height corresponding to the maximum value of the first focusing degree parameter is the optimal focusing height reference value, that is, in the distribution relationship between the first focusing degree parameter and the focusing height, the peak of the curve is the optimal focusing height reference value. For the same calibration image 110, the focus heights of the calibration patterns 100 located in different layers have differences, and therefore, each layer of the calibration patterns 100 has the maximum value of the corresponding first focusing parameter.

Therefore, in this embodiment, the step of obtaining the reference value of the optimal focal height of the multi-layer calibration pattern 100 further includes: step S42 is executed to calculate the average value of the focus heights corresponding to the maximum value of the first focus parameter of each layer of calibration graph 100 as the reference value of the best focus height. By calculating the average value of the focusing heights corresponding to the maximum value of the first focusing parameter of each layer of the calibration graph 100 as the reference value of the optimal focusing height, the complexity of obtaining the reference value of the optimal focusing height is reduced, and the obtained reference value of the optimal focusing height is more accurate. In other embodiments, the step of obtaining the reference value of the best focus height of the multi-layer calibration pattern comprises: acquiring a third focusing power parameter of the calibration image at different focusing heights; and acquiring the focal height corresponding to the maximum value of the plurality of third focusing power parameters as an optimal focal height reference value. In this embodiment, the third focus power parameter is used to characterize the overall focus quality of the calibration image. In other embodiments, the optimal focus height reference value may also be defined by empirical values or experimental data.

With continued reference to fig. 1, step S5 is executed to capture a to-be-measured image of the to-be-measured object.

And acquiring an image to be detected of the object to be detected by shooting, and preparing for acquiring a second focal power parameter of each layer of calibration graph 100 in the image to be detected subsequently, so that after the defocusing amount of the image to be detected is acquired by subsequent calculation, the focusing height of the image to be detected is adjusted to the optimal focusing height reference value according to the defocusing amount. Specifically, the imaging system is used for shooting and acquiring the image to be measured of the object to be measured. The description of the calibration graph 100 in the image to be measured may be combined with the related description referring to the foregoing steps, and is not repeated herein.

With reference to fig. 1, step S6 is executed to obtain a second focusing power parameter of each layer of calibration graph 100 in the image to be measured according to the image to be measured.

And obtaining a second focusing power parameter of each layer of the calibration graph 100 in the image to be tested, so as to perform weighting processing after respectively calculating logarithms on the second focusing power parameters of each layer of the calibration graph 100 in the image to be tested subsequently, and obtaining a test difference value. Specifically, the step of obtaining the second focusing power parameter of each layer of the calibration graph 100 in the image to be measured according to the image to be measured includes: registering the image to be detected and the calibration image 110 to obtain a region of interest (ROI) in the image to be detected corresponding to the multilayer calibration pattern 100; a second focusing power parameter of the region of interest corresponding to the multi-layer calibration pattern 100 is obtained. By obtaining the second focus power parameter of the region of interest corresponding to the multilayer calibration pattern 100, the focusing process can be accelerated and simplified.

The second focus power parameter comprises image sharpness, image contrast, image center-to-center distance, image curvature, image autocorrelation, or a gaussian derivative of an image, and the first focus power parameter and the second focus power parameter are of the same type. The type of the focus parameter of the calibration image 110 is the same as that of the image to be measured, so that the defocus amount of the image to be measured can be obtained by using the calibration curve 130 obtained through the calibration image 110.

In this embodiment, when the first focus parameter is acquired, the first focus parameter is the image sharpness, and therefore, in the step of acquiring the second focus parameter, the second focus parameter is also the image sharpness.

With reference to fig. 1, step S7 is executed to perform the weighting processing after the logarithm of the second focusing power parameter of each layer of calibration graph 100 in the image to be tested is respectively solved, so as to obtain a test difference.

In step S3, the distribution relations corresponding to the multiple layers of calibration patterns 100 are respectively logarithmized and then weighted to obtain a calibration curve 140, where the calibration curve 140 and the focusing height are in a linear relation, so that the actual height corresponding to the test difference can be obtained by substituting the test difference into the function corresponding to the calibration curve 140, and accordingly, the difference between the reference value of the optimal focusing height and the actual height is calculated, and the defocus amount of the image to be measured can be obtained.

Specifically, the step of obtaining the test difference value includes: and respectively calculating logarithms of the second focusing power parameters of the interested region, and then carrying out the weighting processing. For the specific description of the weighting process, reference may be made to the corresponding description in the foregoing steps, which is not repeated herein.

In this embodiment, in the step of obtaining the test difference, before the logarithm of the second focal power parameter of each layer of the calibration graph 100 in the image to be tested, the method further includes: and performing second normalization processing on the second focusing power parameter of each layer of the calibration graph 100 in the image to be detected by adopting the normalization coefficient which is the same as that of the first normalization processing. In the step of obtaining the calibration curve 140, before the logarithm of the distribution relations corresponding to the multiple layers of calibration graphs 100 are obtained, the gaussian width is used as a normalization coefficient, and the first normalization processing is performed on the distribution relations corresponding to the multiple layers of calibration graphs 100, so that the second normalization processing is performed on the second focusing degree parameter of each layer of calibration graph 100 in the image to be tested by using the normalization coefficient the same as that of the first normalization processing, so that the test difference value can be matched with the calibration curve 140, the accuracy of data calculation is improved, and the focusing accuracy is further improved.

Continuing to refer to fig. 1, step S8 is executed, the calibration curve 130 is used to determine the actual height corresponding to the test difference, and the difference between the reference value of the optimal focusing height and the actual height is calculated as the defocus of the image to be measured.

The defocus amount is obtained through calculation, the accuracy of the defocus amount is high, and compared with a scheme of shooting a plurality of images at a small step length to determine an optimal focus height reference value and a scheme of determining the optimal focus height reference value in a non-imaging mode (for example, in an interference mode), the defocus amount calculation method can improve the focusing speed while guaranteeing the focusing accuracy without increasing extra hardware cost.

In this embodiment, the focusing method further includes: and focusing the object to be measured by the imaging system according to the defocusing amount. Specifically, the focusing the object to be measured by the imaging system according to the defocus amount includes: and relatively moving the focusing amount on the focusing height through the imaging system and the object to be measured.

Correspondingly, the embodiment of the invention also provides a focusing system. Referring to FIG. 6, a functional block diagram of an embodiment of a focus system for an analyte of the present invention is shown.

In this embodiment, the object to be measured (not shown) includes a plurality of layers of calibration patterns, and the plurality of layers of calibration patterns have different heights along the focusing direction. The focusing system includes: an image obtaining module 50, configured to obtain calibration images 110 of the object under different focusing heights along the focusing direction, and further configured to capture an image to be measured (not shown) of the object; the first image processing module 61 is configured to obtain a distribution relationship between a first focusing degree parameter and a focusing height of each layer of the calibration graph 100 according to the calibration image 110, where the distribution relationship is gaussian distribution; the first data processing module 71 is configured to respectively perform weighting processing after logarithm is obtained on distribution relations corresponding to the multiple layers of calibration graphs 100, so as to obtain a calibration curve 140 (as shown in fig. 4), where the calibration curve 130 and the focusing height are in a linear relation; a second data processing module 72, configured to obtain an optimal focal height reference value of the multilayer calibration graph 100; the second image processing module 62 is configured to obtain a second focusing power parameter of each layer of the calibration graph 100 in the image to be detected according to the image to be detected; the third data processing module 73 is configured to perform the weighting processing after respectively logarithmizing the second focusing power parameters of each layer of the calibration graph 100 in the image to be tested, so as to obtain a test difference value; a fourth data processing module 80, configured to determine an actual height corresponding to the test difference by using the calibration curve 130, and calculate a difference between the reference value of the optimal focusing height and the actual height as a defocus amount of the image to be detected.

In the focusing system, after the calibration image 110 of the object to be measured at different focusing heights is obtained by the image obtaining module 50 along the focusing direction, the first image processing module 61 obtains the distribution relationship between the first focusing degree parameter and the focusing height of each layer of calibration graph 100 according to the calibration image 110, the distribution relationship is gaussian distribution, then the first data processing module 71 is used to respectively logarithm the distribution relationship corresponding to the plurality of layers of calibration graphs 100 and perform weighting processing, and the calibration curve 130140 with linear relationship is obtained as the calibration curve 140, i.e. the differential response curve of the first focusing degree parameter in the logarithmic coordinate system, therefore, after the image to be measured is obtained by shooting by the image obtaining module 50, the second focusing degree parameter of each layer of calibration graph 100 in the image to be measured is obtained by the second image processing module 62, and the second focusing degree parameter of each layer of calibration graph 100 in the image to be measured is respectively logarithmized by the third data processing module 73 and then the second focusing degree parameter of each layer of calibration graph 100 in the image to be measured is obtained After the weighting processing is performed and the test difference value is obtained, the known test difference value is substituted into the calibration curve 140 through the fourth data processing module 80, and the actual height of the image to be measured can be obtained, so that the defocus amount of the image to be measured can be obtained by calculating the difference value between the optimal focusing height reference value and the actual height, and compared with a scheme of shooting a plurality of images at a small step length to determine the optimal focusing height reference value and a scheme of determining the optimal focusing height reference value in a non-imaging manner, the embodiment can improve the focusing speed while ensuring the focusing accuracy without increasing extra hardware cost.

The object to be measured (not shown) includes multiple layers of calibration patterns 100, the multiple layers of calibration patterns 100 have different heights along the focusing direction, and the image obtaining module 50 is configured to obtain calibration images 110 of the object to be measured at different focusing heights along the focusing direction, so as to prepare for subsequently obtaining a distribution relationship between a first focusing degree parameter and a focusing height corresponding to each layer of the calibration patterns 100. Specifically, the image obtaining module 50 is configured to shoot an object to be measured at different focusing heights in a focusing direction, and obtain an image of the object to be measured as a calibration image 110, where the object to be measured includes multiple layers of calibration patterns 100, and the calibration image 110 includes an image of the calibration patterns 100. In this embodiment, the image acquiring module 50 is an imaging system. In particular, the imaging system comprises a microscopic imaging device.

As an example, the object to be measured is a wafer, and the calibration pattern 100 is an overlay mark pattern spatially located at different layers on the wafer.

In this embodiment, the number of the calibration patterns 100 is two, that is, the object to be measured includes two layers of the calibration patterns 100. Specifically, the two layers of calibration patterns 100 are a first layer of calibration pattern 101 and a second layer of calibration pattern 102, respectively, and the first layer of calibration pattern 101 and the second layer of calibration pattern 102 have different heights along the focusing direction.

In this embodiment, the image obtaining module 50 captures a plurality of calibration images 110 at different focal heights, and each calibration image 110 includes an image of the multi-layered calibration pattern 100. That is, each time one calibration image 110 is captured, the multi-layer calibration pattern 100 is captured at the same time, i.e., the images of the multi-layer calibration pattern 100 are displayed in the same calibration image 110. In this embodiment, the first layer calibration pattern 101 and the second layer calibration pattern 102 are displayed in the same calibration image 110.

In this embodiment, the image obtaining module 50 obtains the calibration image 110 by shooting the object to be measured at different focusing heights with a preset step length. Wherein, the preset step length is not suitable to be too small or too large. If the preset step length is too small, a large number of calibration images 110 need to be shot correspondingly, so that the data acquisition time is long correspondingly, and the focusing efficiency of the focusing method is low; if the preset step length is too large, the data size is too small correspondingly, and when the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height is obtained according to the calibration image subsequently, the precision of the obtained distribution relation is low, so that the focusing precision is easy to reduce. For this reason, in the present embodiment, the preset step size is 30 nm to 200 nm.

In this embodiment, the image obtaining module 50 is further configured to capture and obtain an image of the object to be detected in an actual detection process. And acquiring an image to be detected by shooting, and preparing for acquiring a second focal power parameter of each layer of calibration graph 100 in the image to be detected according to the image to be detected subsequently so as to adjust the focal height of the image to be detected to an optimal focal height reference value according to the focal power after calculating the defocusing amount of the image to be detected.

The first image processing module 61 is configured to obtain a distribution relationship between the first focusing degree parameter and the focusing height of each layer of the calibration graph 100 according to the calibration image 110, where the distribution relationship is gaussian distribution. In the process of shooting the calibration graph 100 at different focusing heights, the image obtaining module 50 may determine the focusing height, and obtain the first focusing degree parameter through the calibration image 110, so as to obtain the focusing height and the first focusing degree parameter corresponding to the focusing height. Therefore, the first image processing module 61 obtains the distribution relationship between the first degree of focus parameter and the focal height of each layer of calibration graph 100, so as to transmit the obtained data to the first data processing module 71, and thus the first data processing module 71 is used to obtain the differential response curve of the first degree of focus parameter in the logarithmic coordinate system. Moreover, the distribution relationship is gaussian distribution, and therefore, the distribution relationship is subjected to weighting after being subjected to logarithm processing, and the calibration curve 140 having a linear relationship with the focal height can be easily obtained.

The first focus parameter comprises image sharpness, image contrast, image center-to-center distance, image curvature, image autocorrelation, or a gaussian derivative of the image. As an example, the first degree of focus parameter is image sharpness.

Specifically, the first image processing module 61 divides each calibration image 110 into a plurality of regions 130 (as shown in fig. 2), each region 130 includes an image of one layer of the calibration graph 100, and is further configured to calculate first degree-of-focus parameters of each region 130 at different focal heights, and obtain a distribution relationship between the first degree-of-focus parameters and the focal heights. Each area 130 comprises an image of a layer of calibration patterns 100, the calibration patterns 100 located in the same area 130 having the same height. As shown in fig. 2, in this embodiment, taking the object to be measured includes two layers of calibration patterns 100 as an example, the multiple regions 130 are respectively a first region 130a (shown by a dashed line frame in fig. 2) and a second region 130b (shown by a dashed line frame in fig. 2), and the calibration patterns 100 in the first region 130a and the second region 130b are located in different layers, that is, the calibration patterns 100 in the first region 130a and the second region 130b have different heights in the focusing direction.

wherein G is₁(z) is the image sharpness, G, of the first region 130a₂(z) the image sharpness of the second region 130b, z the distance between the object and the imaging device, a₁、a₂、b₁、b₂、C₁And C₂Are all constant coefficients, and a₁And a₂Are all of Gaussian width, C₁And C₂Are depth-dependent coefficients. It should be noted that, since the calibration images 110 of the object under test at different focal heights are obtained by the same image obtaining module 50, C is₁＝C₂。

The first data processing module 71 is configured to perform weighting processing after calculating logarithms of distribution relations corresponding to the multiple layers of calibration graphs 100, respectively, to obtain a calibration curve 140 (as shown in fig. 4), where the calibration curve 130 and the focusing height are in a linear relation. Referring to fig. 4 in conjunction, fig. 4 is a schematic diagram of a distribution of a first degree of focus parameter to a height of focus and a calibration curve 140 in a logarithmic coordinate system, with the abscissa representing the height of focus and the ordinate representing the degree of focus parameter (e.g., image sharpness).

The calibration curve 140 and the focusing height are in a linear relationship, so that after a to-be-detected image of the to-be-detected object is obtained through subsequent shooting, the second focusing power parameters of each layer of calibration graph in the to-be-detected image are respectively subjected to logarithm processing to obtain a test difference value, the known test difference value is substituted into a function corresponding to the calibration curve 140, the actual height of the to-be-detected image can be obtained, and the defocusing amount of the to-be-detected image can be obtained by calculating the difference value between the reference value of the optimal focusing height and the actual height.

Each layer of calibration graph 100 has a distribution relationship between the corresponding first degree of focus parameter and the corresponding focus height, so that after the first data processing module 71 respectively logarithmically calculates the distribution relationship corresponding to the multiple layers of calibration graphs 100, each layer of calibration graph 100 corresponds to one curve. For example, as shown in fig. 4, a curve corresponding to the first region 130a is a first curve 131, and a curve corresponding to the second region 130b is a second curve 132.

Specifically, the first data processing module 71 is configured to provide a plurality of weighted values, perform weighting using each weighted value and a plurality of first focusing degree parameters, obtain the calibration curve 140, and make the calibration curve 140 and the focusing height form a linear relationship through the weighted values. In this embodiment, the number of the calibration graphs 100 is two, and therefore, the weighted values are 1 and-1, that is, the distribution relations corresponding to the two calibration graphs 100 are subjected to logarithm calculation and then subtraction to obtain the calibration curve 140. In other embodiments, when the number of calibration patterns is three, the plurality of weighting values are 1, -1/2, and-1/2, respectively. In other embodiments, when the number of calibration patterns is four, the weighting values are 1, -1, and-1, respectively.

In this embodiment, the first data processing module 71 is further configured to perform a first normalization process on the distribution relationships corresponding to the multilayer calibration graph 100 respectively by using the gaussian width as a normalization coefficient before respectively logarithm-solving the distribution relationships corresponding to the multilayer calibration graph 100.

In this embodiment, the first data processing module 71 uses a in formula (1)₁And a in formula (2)₂And (6) normalizing. Therefore, the function S (z) of the calibration curve 140 is expressed by equation (3),

The second data processing module 72 is used for obtaining the best focus height reference value of the multi-layer calibration graph 100.

And in the process of actual detection, when an image to be detected of an object to be detected is shot, the optimal focusing height reference value is used as a focusing reference position.

Specifically, after the second focusing power parameters of each layer of calibration graph 100 in the image to be detected are respectively subjected to the weighting processing after logarithmization, after a test difference value is obtained, the actual height corresponding to the test difference value is determined by using the calibration curve, and the difference value between the reference value of the optimal focusing height and the actual height is calculated to be used as the defocusing amount of the image to be detected, so that focusing can be realized according to the defocusing amount, and the defocusing amount is obtained through calculation, so that the focusing accuracy is improved, and the requirement of detection accuracy is further met.

Specifically, the second data processing module 72 is configured to obtain the focal height corresponding to the maximum value of the first focusing parameter of each layer of the calibration graph 100 according to the distribution relationship corresponding to each layer of the calibration graph 100, and is further configured to calculate an average value of the focal heights corresponding to the maximum values of the first focusing parameters of each layer of the calibration graph 100, as an optimal focal height reference value. The distribution relationship between the first focusing degree parameter and the focusing height is gaussian distribution, so that the focusing height corresponding to the maximum value of the first focusing degree parameter is the optimal focusing height reference value, that is, in the distribution relationship between the first focusing degree parameter and the focusing height, the peak value of the curve is the optimal focusing height reference value. By calculating the average value of the heights corresponding to the maximum values of the first focusing degree parameters of the multilayer calibration graph 100 as the reference value of the optimal focusing height, the complexity of obtaining the reference value of the optimal focusing height is reduced, and the obtained reference value of the optimal focusing height is more accurate.

In other embodiments, the second data processing module may also be configured to obtain a third focal power parameter of the calibration image at different focal heights, and further be configured to obtain a focal height corresponding to a maximum value of the third focal power parameters as an optimal focal height reference value, where in the embodiments, the third focal power parameter is used to characterize the overall focal quality of the calibration image. In other embodiments, the focusing system may not be provided with the second data processing module, and the optimal focusing height reference value may be customized by empirical values or experimental data.

After the image obtaining module 50 obtains the image to be measured of the object to be measured, the second image processing module 62 is configured to obtain the second focusing power parameter of each layer of the calibration graph 100 in the image to be measured. And obtaining a second focusing power parameter of each layer of the calibration graph 100 in the image to be tested so as to calculate and respectively logarithm the second focusing power parameter of each layer of the calibration graph 100 in the image to be tested, and then performing the weighting processing to obtain a test difference value.

Specifically, the second image processing module 62 is configured to register the image to be measured with the calibration image 110, obtain a region of interest in the image to be measured corresponding to the multi-layer calibration graph 100, and further obtain a second focusing power parameter of the region of interest corresponding to the multi-layer calibration graph 100. By obtaining the second focusing power parameter of the region of interest corresponding to the multi-layer calibration pattern 100, the focusing process can be accelerated and simplified.

In this embodiment, the first focus parameter and the second focus parameter have the same type, so that the defocus amount of the image to be measured can be obtained by using the calibration curve 130 obtained by the calibration image 110. In this embodiment, when the first focus parameter is acquired, the first focus parameter is the image sharpness, and therefore, when the second focus parameter is acquired, the second focus parameter is also the image sharpness.

The third data processing module 73 is configured to calculate the second focusing power parameter of each layer of the calibration graph 100, perform the weighting processing after respectively calculating the logarithm, and obtain a test difference value. The calibration curve 140 is a linear function curve, so that the test difference is obtained through the third data processing module 73, and then the actual height corresponding to the test difference can be obtained by substituting the test difference into the calibration curve 140, and correspondingly, the difference between the reference value of the optimal focusing height and the actual height is calculated, so that the defocus amount of the image to be measured can be obtained.

Specifically, the third data processing module 73 is configured to perform the weighting processing after respectively performing logarithm on the second focusing power parameters of the region of interest, so as to obtain a test difference value.

In this embodiment, the third data processing module 73 is further configured to perform a second normalization process on the second focusing power parameter of each layer of the calibration graph 100 in the image to be measured by using a normalization coefficient that is the same as the first normalization process before the logarithm of the second focusing power parameter of each layer of the calibration graph 100 in the image to be measured is calculated.

The fourth data processing module 80 is configured to determine an actual height corresponding to the test difference by using the calibration curve 140, and calculate a difference between the reference value of the optimal focusing height and the actual height as a defocus of the image to be measured

Through the image acquisition module 50, the first image processing module 61, the first data processing module 71, the second data processing module 72, the second image processing module 62 and the third data processing module 73, the defocus amount is obtained through calculation, the precision of the defocus amount is high, and compared with a scheme of shooting a plurality of images at a small step length to determine the optimal focus height reference value and a scheme of determining the optimal focus height reference value in a non-imaging mode, the embodiment can improve the focusing speed while ensuring the focusing precision without increasing extra hardware cost, for example, the focusing precision can meet the requirement of 100-fold microscopic imaging.

In this embodiment, the image obtaining module 50 is further configured to enable the imaging system to focus on the object to be measured according to the defocus amount. Specifically, the focus amount is relatively moved in the focus height by the imaging system and the object to be measured.

The embodiment of the present invention further provides a device, which can implement the focusing method for the object to be measured provided by the embodiment of the present invention by loading the focusing method for the object to be measured in the program form.

Referring to fig. 7, a hardware structure diagram of a device provided by an embodiment of the present invention is shown. The device of the embodiment comprises: at least one processor 01, at least one communication interface 02, at least one memory 03, and at least one communication bus 04.

In this embodiment, the number of the processor 01, the communication interface 02, the memory 03 and the communication bus 04 is at least one, and the processor 01, the communication interface 02 and the memory 03 complete mutual communication through the communication bus 04.

The communication interface 02 may be an interface of a communication module for performing network communication, for example, an interface of a GSM module.

The processor 01 may be a central processing unit CPU, or a Specific Integrated circuit asic (application Specific Integrated circuit), or one or more Integrated circuits configured to implement the focusing method of the present embodiment.

The memory 03 may comprise a high-speed RAM memory, and may further comprise a non-volatile memory (non-volatile memory), such as at least one disk memory.

The memory 03 stores one or more computer instructions, which are executed by the processor 01 to implement the method for focusing the dut provided in the foregoing embodiments.

It should be noted that the above-mentioned terminal device may further include other devices (not shown) that may not be necessary for the disclosure of the embodiment of the present invention; these other components may not be necessary to understand the disclosure of embodiments of the present invention, which are not individually described herein.

The embodiment of the present invention further provides a storage medium, where one or more computer instructions are stored, and the one or more computer instructions are used to implement the method for focusing an object to be measured provided in the foregoing embodiment.

In the focusing method of the embodiment of the invention, the relation between the difference value of the first focusing degree parameter and the focusing height under a logarithmic coordinate system is obtained in advance, after an image to be detected is obtained by shooting, the second focusing degree parameter of each layer of calibration graph in the image to be detected is subjected to the weighting processing after the logarithm is respectively solved, a test difference value is obtained, and the known test difference value is substituted into the calibration curve, so that the actual height of the image to be detected can be obtained, the defocusing amount of the image to be detected can be obtained by calculating the difference value between the optimal focusing height reference value and the actual height, compared with the scheme of shooting a plurality of images under a smaller step length to determine the optimal focusing height reference value and the scheme of determining the optimal focusing height reference value in a non-imaging mode, the embodiment of the invention can obtain the focusing height without increasing extra hardware cost, the focusing precision is ensured, the focusing speed is improved, and the focusing precision can meet the requirement of 100 times microscopic imaging.

The embodiments of the present invention described above are combinations of elements and features of the present invention. Unless otherwise mentioned, the elements or features may be considered optional. Each element or feature may be practiced without being combined with other elements or features. In addition, the embodiments of the present invention may be configured by combining some elements and/or features. The order of operations described in the embodiments of the present invention may be rearranged. Some configurations of any embodiment may be included in another embodiment, and may be replaced with corresponding configurations of the other embodiment. It will be apparent to those skilled in the art that claims that are not explicitly cited in each other in the appended claims may be incorporated into the embodiments of the present invention or may be incorporated as new claims in modifications subsequent to the filing of this application.

Embodiments of the invention may be implemented by various means, such as hardware, firmware, software, or a combination thereof. In a hardware configuration, the method according to the exemplary embodiment of the present invention may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, and the like.

In a firmware or software configuration, embodiments of the present invention may be implemented in the form of modules, procedures, functions, and the like. The software codes may be stored in memory units and executed by processors. The memory unit is located inside or outside the processor, and may transmit and receive data to and from the processor via various known means.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected by one skilled in the art without departing from the spirit and scope of the invention, as defined in the appended claims.

Claims

1. A focusing method of an object to be measured is characterized in that the object to be measured comprises a plurality of layers of calibration patterns, the plurality of layers of calibration patterns have different heights along a focusing direction, and the focusing method comprises the following steps:

obtaining calibration images of the object to be measured at different focusing heights along the focusing direction;

acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution;

respectively carrying out weighting processing after solving logarithms of distribution relations corresponding to the multiple layers of calibration graphs to obtain calibration curves, wherein the calibration curves and the focusing heights are in a linear relation;

acquiring an optimal focusing height reference value of the multilayer calibration graph;

shooting and obtaining a to-be-detected image of the to-be-detected object;

acquiring a second focusing power parameter of each layer of calibration graph in the image to be detected according to the image to be detected;

respectively carrying out logarithm solving on the second focusing power parameter of each layer of calibration graph in the image to be tested, and then carrying out weighting processing to obtain a test difference value;

and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height to be used as the defocusing amount of the image to be detected.

2. The focusing method of claim 1, wherein the step of acquiring calibration images of the object at different focal heights along the focusing direction comprises: shooting at different focusing heights to obtain a plurality of calibration images, wherein each calibration image contains images of the plurality of layers of calibration images;

the step of obtaining the distribution relation between the first focusing degree parameter and the focusing height of each layer of the calibration graph according to the calibration image comprises the following steps: dividing each calibration image into a plurality of areas, wherein each area comprises a layer of image of the calibration image; and respectively calculating first focusing degree parameters of each region under different focusing heights to obtain the distribution relation between the first focusing degree parameters and the focusing heights.

3. The focusing method of claim 1 or 2, wherein the calibration image is obtained by photographing the object to be measured at different focusing heights with a preset step size, wherein the preset step size is 30 nm to 200 nm.

4. The focusing method of claim 1, wherein the step of obtaining the reference value of the optimum focus height of the multi-layered calibration pattern comprises: respectively obtaining the focusing height corresponding to the maximum value of the first focusing degree parameter of each layer of the calibration graph according to the distribution relation corresponding to each layer of the calibration graph; calculating the average value of the focusing heights corresponding to the maximum values of the first focusing degree parameters of each layer of the calibration graph as the reference value of the optimal focusing height;

or,

the step of obtaining the optimal focusing height reference value of the multilayer calibration graph comprises the following steps: acquiring a third focusing power parameter of the calibration image at different focusing heights; and acquiring the focal height corresponding to the maximum value of the third focal power parameters as an optimal focal height reference value.

5. The focusing method of claim 1, wherein the step of obtaining the second focusing power parameter of each calibration pattern of each layer in the image to be measured according to the image to be measured comprises: registering the image to be detected and the calibration image to obtain an interested area corresponding to the multilayer calibration graph in the image to be detected; acquiring a second focusing power parameter of the region of interest corresponding to the multilayer calibration graph;

the step of obtaining the test difference value comprises: and respectively carrying out the weighting processing after the logarithms of the second focusing power parameters of the region of interest are solved.

6. The focusing method of claim 1, wherein the step of obtaining the calibration curve further comprises, before logarithmically computing the distribution relations corresponding to the plurality of calibration patterns, respectively: respectively carrying out first normalization processing on distribution relations corresponding to the multiple layers of calibration graphs by taking the Gaussian width as a normalization coefficient;

in the step of obtaining the test difference, before logarithm is calculated on the second focusing power parameter of each layer of calibration graph in the image to be tested, the method further includes: and performing second normalization processing on the second focusing power parameter of each layer of calibration graph in the image to be measured by adopting a normalization coefficient which is the same as the first normalization processing.

7. The focusing method of claim 1, wherein the first focus power parameter and the second focus power parameter each comprise an image sharpness, an image contrast, an image center-to-center distance, an image curvature, an image autocorrelation, or a gaussian derivative of an image, and the first focus power parameter and the second focus power parameter are of the same type.

8. The focusing method according to claim 1, wherein the weighting process step includes: providing a plurality of weighting values; and weighting by utilizing each weighted value and the plurality of first focusing degree parameters to obtain a calibration curve, and enabling the calibration curve and the focusing height to be in a linear relation through the weighted value.

9. The focusing method according to claim 8, wherein the number of said calibration patterns is two, and said plurality of weighting values are 1 and-1, respectively;

or the number of the calibration graphs is three, and the weighted values are respectively 1, -1/2 and-1/2;

or the number of the calibration graphs is four, and the weighted values are respectively 1, -1, 1 and-1.

10. The focusing method of claim 9, further comprising: providing an imaging system;

obtaining calibration images of the object to be measured at different focusing heights along the focusing direction through the imaging system;

and shooting and acquiring the image to be detected of the object to be detected through the imaging system.

11. A focusing system of an object to be measured, the object to be measured including a plurality of layers of calibration patterns having different heights along a focusing direction, the focusing system comprising:

the image acquisition module is used for acquiring calibration images of the object to be detected at different focusing heights along the focusing direction and shooting and acquiring the image to be detected of the object to be detected;

the first image processing module is used for acquiring a distribution relation between a first focusing degree parameter and the focusing height of each layer of the calibration graph according to the calibration image, wherein the distribution relation is Gaussian distribution;

the first data processing module is used for respectively carrying out weighting processing after logarithm is solved on distribution relations corresponding to the multiple layers of calibration graphs to obtain calibration curves, and the calibration curves and the focusing height are in a linear relation;

the second data processing module is used for acquiring the optimal focusing height reference value of the multilayer calibration graph;

the second image processing module is used for acquiring a second focusing power parameter of each layer of calibration graph in the image to be detected according to the image to be detected;

the third data processing module is used for respectively carrying out logarithm calculation on the second focusing power parameter of each layer of calibration graph in the image to be tested and then carrying out weighting processing on the obtained logarithm calculation result to obtain a test difference value;

and the fourth data processing module is used for determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height to be used as the defocusing amount of the image to be detected.

12. An apparatus comprising at least one memory and at least one processor, the memory storing one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method of focusing an object as claimed in any one of claims 1 to 10.

13. A storage medium storing one or more computer instructions for implementing a method of focusing an object to be measured according to any one of claims 1 to 10.