CN105973466B - Method and terminal for spectral detection - Google Patents

Abstract

A method and terminal for spectral detection can improve the spectral detection efficiency of the terminal. Including: the terminal obtains the first spectral response curve of the object to be measured under the light source and the current ambient light through the light sensor; the terminal determines the second spectral response curve of the current ambient light; the terminal according to the first spectral response curve and the second spectral response curve, Determine a third spectral response curve, where the third spectral response curve is the spectral response curve of the object to be measured after filtering out the interference of the current ambient light; the terminal determines the fourth spectral response of the target attribute of the object to be measured according to the third spectral response curve curve.

Description

Method and terminal for spectral detection

technical field

The present invention relates to the field of terminals, and in particular, to a method and terminal for spectrum detection in the field of terminals.

Background technique

The current spectral detection technology has been used in skin detection in the beauty industry. When the skin detector in the beauty industry detects the skin area, in order to obtain the spectral response result of the skin area under the illumination light source, the ambient light should be prevented as much as possible from the skin to be tested. The spectral interference of the area under the illumination light source, so the existing technology usually adds a cylindrical shading closed ring design in front of the spectral sensor of the skin detector to obtain the spectral response result of the measured skin area that is not disturbed by ambient light. .

With the development of smart terminals and sensor technology, the miniaturization of devices makes it possible for professional applications in the beauty industry to develop into the consumer field. For example, the function of skin detection is integrated into the smart terminal. However, the existing skin detection equipment or instruments must use a light hood to close the area to be measured on the skin to isolate the influence of ambient light, and then measure skin parameters (such as skin color) and perform background calculations. However, applying the hood to the smart terminal does not conform to the development direction of terminal miniaturization and convenience, that is, the traditional solution is not conducive to the application of the smart terminal in terms of composition and principle. Simply removing the hood for spectral detection will affect the detection results due to the interference of ambient light, reducing the user experience.

SUMMARY OF THE INVENTION

The present invention provides a method and a terminal for spectral detection to improve the spectral detection efficiency of the terminal.

In a first aspect, a method for spectral detection is provided, comprising: a terminal acquiring a first spectral response curve of an object to be measured under a light source and current ambient light through a light sensor; the terminal determining the first spectral response curve of the current ambient light; Two spectral response curves; the terminal determines a third spectral response curve according to the first spectral response curve and the second spectral response curve, and the third spectral response curve is the filter of the object to be tested. The spectral response curve after the interference of the current ambient light; the terminal determines the fourth spectral response curve of the target attribute of the object to be measured according to the third spectral response curve.

After the first spectral response curve of the object to be measured is obtained, the second spectral response curve of the ambient light is determined, and the interference of the ambient light in the first spectral response curve is eliminated according to the second spectral response curve, so as to obtain a better spectral characteristic. Accurate spectral response results improve the spectral detection efficiency of the terminal.

In a possible implementation manner, the determining, by the terminal, the second spectral response curve of the current ambient light includes: the terminal acquiring, by the light sensor, all of the object to be measured under the current ambient light. the second spectral response curve.

In a possible implementation manner, the terminal determines, according to the third spectral response curve, a fourth spectral response curve of the target attribute of the object to be measured, including: the terminal according to the third spectral response curve , the filter function model of the light sensor, the reflection model of the target attribute of the object to be measured, and the energy distribution function of the light source determine the fourth spectral response curve.

In a possible implementation manner, the terminal uses the third spectral response curve, the filter function model of the light sensor, the reflection model of the target attribute of the object to be measured, and the energy distribution function of the light source, Determining the fourth spectral response curve includes: the terminal determines the fourth spectral response curve according to the formula Y(λ)=∫F(λ)R(λ)I(λ)dλ, where Y(λ) represents the third spectral response curve, F(λ) represents the filter function model of the light sensor, the R(λ) represents the reflection model of the target attribute of the object to be measured, and the I(λ) represents the The energy distribution function of the light source.

In a possible implementation manner, the method further includes: the terminal determining a target illumination scene; the terminal determining, according to the target illumination scene, an illumination mapping model between the fourth spectral curve and the CIE XYZ domain; The terminal determines, according to the illumination mapping model, the value of the fourth spectral curve mapped to the CIE XYZ domain.

Determine the illumination mapping model according to the target illumination scene, and then determine the value of the fourth spectral curve mapped to the CIE XYZ domain, so as to obtain the value of the CIE XYZ domain corresponding to the target illumination scene, and improve the spectral detection efficiency of the terminal.

In a possible implementation manner, the determining, by the terminal, the target lighting scene includes: acquiring, by the terminal, user input information, where the input information is used to indicate the target lighting scene; and, according to the input information, the terminal, The target lighting scene is determined from a plurality of candidate lighting scenes, and the plurality of candidate lighting scenes have a corresponding relationship with a plurality of lighting mapping models; the terminal determines the fourth spectral curve according to the target lighting scene The illumination mapping model between the CIE XYZ domain and the CIE XYZ domain includes: the terminal determining the illumination mapping model corresponding to the target illumination scene according to the corresponding relationship.

In a possible implementation manner, the light sensor is a multispectral sensor.

In a second aspect, a terminal is provided, the terminal including means for performing the method of the first aspect. Based on the same inventive concept, since the principle of the terminal for solving the problem corresponds to the solution in the method design of the first aspect, the implementation of the terminal can refer to the implementation of the method, and the repetition will not be repeated.

In a third aspect, a terminal is provided, where the terminal includes a memory and a processor. The memory is used for storing programs, and the processor is used for executing programs. When the program is executed, the processor is configured to perform the method of the first aspect. Based on the same inventive concept, since the principle of the terminal for solving the problem corresponds to the solution in the method design of the first aspect, the implementation of the terminal can refer to the implementation of the method, and the repetition will not be repeated.

In a fourth aspect, a system chip is provided, including an input interface, an output interface, at least one processor, and a memory, wherein the input interface, the output interface, the processor, and the memory are directly connected through a bus, and the processor is used for executing The code in the memory, when executed, the processor implements the method of the first aspect. Based on the same inventive concept, since the principle of solving the problem of the system chip corresponds to the solution in the method design of the first aspect, the implementation of the system chip can refer to the implementation of the method, and the repetition will not be repeated.

In a fifth aspect, a computer-readable medium is provided, the computer-readable medium stores a program code for execution by a terminal, the program code is used for executing the instructions of the method of the first aspect, based on the same inventive concept, due to the The principle of the system chip for solving the problem corresponds to the solution in the method design of the first aspect. Therefore, the implementation of the system chip can refer to the implementation of the method, and the repetition will not be repeated.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

FIG. 1 is a schematic diagram of a skin detector in the prior art.

FIG. 2 is a schematic frame diagram of a terminal according to an embodiment of the present invention.

FIG. 3 is a flowchart of a method for spectral detection according to an embodiment of the present invention.

FIG. 4 is a flowchart of a method for spectral detection according to another embodiment of the present invention.

FIG. 5 is a schematic frame diagram of a terminal according to another embodiment of the present invention.

FIG. 6 is a schematic frame diagram of a terminal according to another embodiment of the present invention.

FIG. 7 is a schematic frame diagram of a terminal according to another embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

It should be understood that the technical solutions of the embodiments of the present invention can be applied to various communication systems, such as: Global System of Mobile communication (referred to as "GSM") system, Code Division Multiple Access (Code Division Multiple Access, referred to as "" CDMA") system, Wideband Code Division Multiple Access (WCDMA for short) system, General Packet Radio Service (General Packet Radio Service, referred to as "GPRS"), Long Term Evolution (Long Term Evolution, referred to as "" LTE") system, LTE Frequency Division Duplex ("FDD") system, LTE Time Division Duplex ("TDD"), Universal Mobile Telecommunication System ("Universal Mobile Telecommunication System") UMTS") or Worldwide Interoperability for Microwave Access (Widely Interoperability for Microwave Access, referred to as "WiMAX") communication system, etc.

It should also be understood that, in this embodiment of the present invention, the terminal may include a mobile phone, a tablet computer, a PDA (Personal Digital Assistant, personal digital assistant), a POS (Point of Sales, a sales terminal), a vehicle-mounted computer, and the like.

As mentioned above, a light shield is usually provided in the instrument for spectral detection in the prior art to shield the interference of the spectral detection result of the object to be measured by ambient light. For example, Figure 1 is an example of a prior art spectroscopic detection instrument for detecting skin. As can be seen from Figure 1, whether it is a skin detector used in medicine/scientific research or a portable skin detector used in a makeup counter, a light-shielding sealing ring is added in front of the sensor to avoid interference from ambient light. In the prospect that the spectral detection method may be applied to the terminal, due to the requirements of simplicity and portability of the terminal itself, the traditional design of the light shield is not suitable for use in the terminal, and the light shield is simply removed for spectral detection. The detection result will be affected by the interference of ambient light, and the user experience will be reduced.

In view of the above problems, the present invention proposes a method for spectral detection. The method can be executed by the terminal. The main idea is: in the absence of a hood, the first spectral response curve of the object to be measured under the light source and the current ambient light is obtained through the light sensor, and the second spectral response curve of the current ambient light is determined, and according to the first spectral response curve. The spectral response curve and the second spectral response curve obtain a third spectral response curve after filtering out ambient light interference. Thus, a third spectral response curve in which the object to be tested is not disturbed by ambient light is obtained. and acquiring a fourth spectral curve of the target attribute of the object to be measured according to the third spectral curve.

In the embodiment of the present invention, after the first spectral response curve of the object to be tested is obtained, the second spectral response curve of the ambient light is determined, and according to the second spectral response curve, the ambient light in the first spectral response curve is eliminated Therefore, more accurate spectral response results with spectral characteristics are obtained, and the efficiency of terminal spectral detection is improved.

The method for spectral detection provided by the embodiment of the present invention can reduce the interference of the spectral response curve of the object to be measured by ambient light, obtain spectral response results with more accurate spectral characteristics, and improve user experience.

It should be noted that, in the prior art, a spectral detection instrument usually uses a tricolor spectral device such as an XYZ sensor or a red-green-blue (RedGreen Blue, RGB) sensor to obtain the spectral response information of the object to be measured, and the spectrum of the collected spectral information is Limited scope. In the embodiment of the present invention, as a preferred embodiment, a multi-spectral sensor (or hyperspectral sensor) can be set in the terminal, and the multi-spectral sensor can be used to collect more abundant spectral information than the conventional XYZ sensor or RGB sensor. , so as to obtain a first spectral response curve with more spectral information than using the XYZ sensor, and then perform algorithm processing according to the first spectral response curve and the second spectral response curve to obtain the third spectral response of the object to be measured after filtering out ambient light interference. Spectral response curve. More accurate spectral response information of the object to be measured can be obtained through multispectral sensors. It should be understood that acceptable wavelength ranges for multispectral sensors may include the wavelength ranges of conventional XYZ or conventional RGB sensors.

FIG. 2 shows a schematic block diagram of a terminal according to an embodiment of the present invention. As shown in FIG. 1 , the terminal 100 includes a light sensor 101 and a light source 102 . The light sensor may be an XYZ sensor, an RGB sensor or a multi-spectral sensor. As a preferred solution, the following will take a multi-spectral sensor as an example to describe. The working range of multispectral sensors includes multiple bands. Among them, multi-spectral sensors of different wavelength bands can be selected according to the different reflection characteristics of the object to be measured for light of different wavelength bands. ~800nm (or 470nm-630nm), when the object to be measured is food or object material, a multispectral sensor with a receiving wavelength range of 700nm to 1050nm can be selected. Among them, according to the resolution of the multi-spectral sensor, multiple wavelengths can be selected to detect the spectrum of the object to be measured, for example, 480nm, 520nm, 560nm, 600ms, 660nm, 710nm, 750nm, 780nm, 820nm, 880nm can be selected in the wavelength range , 900nm, 950nm, 1000nm and other wavelengths to detect the spectrum of the object to be tested. The multispectral sensors of the embodiments of the present invention also include multispectral sensors in other wavelength ranges. The present invention does not specifically limit the multispectral sensor. In addition, in order to facilitate the integration of the smart terminal, the light source may be a light emitting diode (Light Emitting Diode, LED) lamp commonly used in the terminal.

In addition, the terminal 100 further includes components such as a radio frequency (Radio Frequency, RF) circuit 110 , a memory 120 , a display screen 140 , an audio circuit 160 , an I/O subsystem 170 , a processor 180 , and a power supply 190 . Those skilled in the art can understand that the terminal structure shown in FIG. 2 does not constitute a limitation on the terminal, and may include more or less components than those shown in the figure, or combine some components, or separate some components, or Different component arrangements.

Wherein, the light sensor used for shooting in the smart terminal in the prior art is usually an RGB sensor. As an example, the multispectral sensor 101 in FIG. 2 can be integrated with the RGB sensor on one chip, that is, the device range of the multispectral sensor is RGB sensor included. Alternatively, the multispectral sensor 101 can also be located on different chips as an independent sensor and the RGB sensor.

FIG. 3 is a schematic flowchart of a method for spectrum detection according to an embodiment of the present invention. As shown in FIG. 3 , the method may be executed by a terminal, and the method 300 includes:

301. The terminal obtains, through a light sensor, a first spectral response curve of the object to be measured under the light source and the current ambient light.

Those skilled in the art may understand that the spectral response curve in the embodiment of the present invention may also be referred to as spectrum, spectral information, or spectral response curve or the like. It should be understood that the first spectral response curve in the embodiment of the present invention may refer to the spectrum of the reflected light of the object to be tested under the illumination of the light source and the current ambient light.

Optionally, the light source may be provided in the terminal, for example, the light source may be an LED lamp in the terminal. Optionally, the light sensor may be a multispectral sensor.

Optionally, the above-mentioned object to be measured may be human face skin, or an object of food or other materials.

For example, when the object to be measured is human face skin, the terminal can turn on the light source, and when the terminal is close to the area of the skin to be measured, the first spectral response curve of the skin to be measured under the light source and the current ambient light is obtained through the multispectral sensor.

302. The terminal determines a second spectral response curve of the current ambient light.

Those skilled in the art can understand that the current ambient light refers to the ambient light of the environment where the object to be measured is currently located.

Optionally, determining the second spectral response curve may be that the terminal obtains the second spectral response curve of the object to be measured under current ambient light through the light sensor.

For example, the terminal may acquire the second spectral response curve of the object to be measured in the current environment when the light source is turned off.

Optionally, to determine the second spectral response curve of the ambient light, the terminal may determine the second spectral response curve according to the user's input. For example, the second spectral response curves corresponding to multiple common environments, such as offices, shopping malls, bedrooms, etc., may be pre-stored in the terminal. Alternatively, scenes can also be distinguished according to lighting conditions, such as sunlight, incandescent lamps, tungsten lamps, etc., and the typical second spectral response curves of different scenes can be measured and stored in advance. After acquiring the user's input information for indicating the current environment, the current environment is determined from a plurality of stored common environments, and then the second spectral response curve corresponding to the current environment is determined as the second spectral response curve of the current ambient light.

303. The terminal determines, according to the first spectral response curve and the second spectral response curve, a third spectral response curve, where the third spectral response curve is the effect of the object under test filtering out the ambient light. Spectral response curve after interference.

Optionally, the terminal determining a third spectral response curve according to the first spectral response curve and the second spectral response curve, comprising: the terminal combining the first spectral response curve and the second spectral response curve. Noise cancellation processing is performed on the response curve to obtain a fourth spectral response curve that is not disturbed by ambient light. The embodiment of the present invention does not limit the specific method of noise cancellation processing. For example, the above noise cancellation processing may adopt a vector operation method.

304. The terminal determines, according to the third spectral response curve, a fourth spectral response curve of the target attribute of the object to be measured.

Wherein, the target attribute of the object to be measured may be the attribute of the object to be measured. For example, the object to be detected may be human face skin, and the target attribute may be the skin color of the human face skin or the oiliness of the human face skin.

Optionally, determining the fourth spectral response curve may be the filter function model of the optical sensor, the reflection model of the target attribute of the object to be measured, the The energy distribution function of the light source determines the fourth spectral response curve.

Wherein, the reflection model of the target attribute of the object to be measured may refer to an optical reflection model of the target attribute of the object to be measured. The reflection model of the target attribute of the object to be measured may be a reflection model constructed by detecting the attribute parameters of the object to be measured through a third-party device or module. For example, when the object to be measured is human face skin, a third-party device or module can be obtained to detect parameters such as skin blood vessels, sebum, and texture of the measured object, and a skin parameter model of the measured object can be constructed. Such models are individualized. Alternatively, a classical skin model, such as the Kubelka-Munk model, can also be obtained as the reflection model of the human face skin.

The energy distribution function of the above-mentioned light source may be a predetermined energy distribution function of the light source. For example, if the light source is an LED lamp of a certain specification, its energy distribution function can be obtained through a unified test in advance. In some cases, due to the fact that LED lamps cannot guarantee that all devices are completely consistent in manufacturing, it is allowed to have a certain error between the actual light intensity distribution and the pre-obtained energy distribution function, and the error can be compensated by an algorithm to avoid the inaccuracy of subsequent calculations. . As a preferred solution, the light source and the multi-spectral sensor can be packaged together, and the light intensity distribution of the light source can be set according to the adjustment of the response of the light source and the multi-spectral sensor.

Optionally, the terminal determines the fourth spectral response curve according to the third spectral response curve, the filter function model of the light sensor, the reflection model of the target attribute of the object to be measured, and the energy distribution function of the light source. Spectral response curve, including: the terminal according to the formula

Y(λ)=∫F(λ)R(λ)I(λ)dλ, (1)

Determine the fourth spectral response curve, wherein Y(λ) represents the third spectral response curve, F(λ) represents the filter function model of the light sensor, and the R(λ) represents the object to be measured. The reflection model of the target property, the I(λ) represents the energy distribution function of the light source.

Wherein, the above-mentioned determination of the fourth spectral response curve according to formula (1) may be to obtain the fourth spectral response curve through learning according to the third spectral response curve and formula (1).

Optionally, I(λ) is the energy distribution function of the light source, and a more accurate energy distribution function of the light source can be obtained through a compensation algorithm. Correction. For example, the corrected I(λ) can be obtained according to formula (2)

I(λ)=I _approx (λ)*SI(λ) (2)

where I _approx (λ) represents the energy distribution function of the light source before correction. I(λ) represents the energy distribution function of the corrected light source. SI(λ) represents the correction coefficient function at the corresponding wavelength, which can be learned by combining the response characteristics of the spectrum sensor module in the embodiment of the present invention to each wavelength spectrum and mapping with a professional spectrum analyzer.

Optionally, the method 300 in this embodiment of the present invention further includes:

305. The terminal determines a target lighting scene; the terminal determines, according to the target lighting scene, the fourth spectral curve and the lighting mapping model of the CIE XYZ domain; the terminal determines the fourth spectral curve according to the lighting mapping model. Four spectral curves map to values in the CIE XYZ domain.

The embodiment of the present invention determines the illumination mapping model according to the target illumination scene, and further determines the value of the fourth spectral curve mapped to the CIE XYZ domain, thereby obtaining the value of the CIE XYZ domain corresponding to the target illumination scene, improving the spectral detection efficiency of the terminal and the user experience.

It should be understood that the above-mentioned illumination mapping model may refer to the mapping relationship between the fourth spectral curve and the CIE XYZ domain. Depending on the target lighting scene, the fourth spectral curve is different from the lighting mapping model of the CIE XYZ domain.

Optionally, determining the target lighting scene by the terminal includes: acquiring, by the terminal, input information from a user, where the input information is used to indicate the target lighting scene; and, according to the input information, the terminal selecting from multiple candidate lighting scenes The target lighting scene is determined in the above, and the multiple candidate lighting scenes and multiple lighting mapping models have correspondences; the terminal determines the lighting mapping model corresponding to the target lighting scene according to the correspondences.

Wherein, the multiple candidate lighting scenes may be the scenes under different lighting conditions such as sunlight, incandescent lamps, and tungsten lamps mentioned above. The user's input information can be used to indicate the target lighting scene of the object to be measured. For example, before the terminal acquires the user's input information, it may display options of multiple candidate lighting scenes to the user through the man-machine interface, and determine the target lighting scene selected by the user from the multiple candidate lighting scenes through the user's input information. Then, the illumination mapping model corresponding to the target illumination scene is determined.

The following describes the embodiment of the present invention in more detail with reference to the specific example shown in FIG. 4 . It should be noted that the embodiment of FIG. 4 is only for helping those skilled in the art to understand the embodiment of the present invention. It is not intended that the embodiments of the present invention be limited to the exemplified specific numerical values or specific scenarios. Those skilled in the art can obviously make various equivalent modifications or changes according to the given example of FIG. 4 , and such modifications and changes also fall within the scope of the embodiments of the present invention.

As an example, FIG. 4 is a schematic flowchart of a method for detecting the skin color of human face skin by a method according to an embodiment of the present invention. Among them, it is assumed that the light source is an LED lamp located in the terminal. The light sensor is a multispectral sensor as shown in Figure 4, and the method includes:

Step 1. The terminal receives the user's instruction information, turns on the LED light, and obtains the first spectral response curve of the tested skin under the LED light and the current ambient light when the terminal is close to the skin area to be tested;

Among them, the product energy distribution response of the general LED light source is known, but because the LED manufacturing cannot guarantee that all devices are completely consistent, it is allowed to have a certain error between the actual energy distribution and the known characteristics. It needs to be compensated by an algorithm to avoid the inaccuracy of subsequent calculations; wherein, the implementation of the above compensation algorithm can pre-train or correct the response of the device and the professional spectrum analyzer through the background.

The terminal mentioned in this step is detected by the method of shooting the skin area at a close distance or close to the skin area, and a multi-spectral sensor or other sensors with integrated multi-spectral acquisition function can be integrated in the terminal, so as to collect more data than the conventionally integrated RGB sensor in the terminal. Rich spectral information for skin color recognition.

Step 2, the terminal turns off the LED light, and obtains the second spectral response curve of the skin to be tested under the current ambient light.

It should be understood that the first spectral response curve and the second spectral response curve are equivalent to the spectral response curves of the skin to be tested under two kinds of illumination. One light is on the light source and ambient light, and the other light is on the ambient light only.

Step 3: The terminal performs noise cancellation processing on the first spectral response curve and the second spectral response curve, and obtains a third spectral response curve after filtering out ambient light interference. For example, including but not limited to noise cancellation processing using vector operations.

Step 4. The terminal corrects and calculates the spectral response curve of the face according to the light intensity distribution information (or energy distribution function) of the LED lamp, the filter function model of the known multispectral sensor, and the light reflection model of the face skin. .

For example, through the third spectral response curve and the formula Y(λ)=∫F(λ)R(λ)I(λ)dλ, the fourth spectral response curve of the skin color of the tested skin can be obtained by learning.

Among them, F(λ) is the filter function of the multispectral sensor, or the response function of the light sensor itself at the wavelength λ, which can be corrected by the filter response model; R(λ) can be the light reflection of the face skin in this step. Model function, there are many kinds of modeling in the prior art; I(λ) is the energy distribution function of the light source (ie, the light intensity distribution information). Y(λ) is the frequency domain expression of the third spectral response curve.

Step 5: The terminal acquires user input information, where the input information is used to indicate the target lighting environment.

For example, the target lighting environment may include lighting environments under different lighting conditions such as sunlight, incandescent lamps, and tungsten lamps.

For example, before the terminal acquires the user's input information, it may display options of multiple candidate lighting scenes to the user through the man-machine interface, and determine the target lighting scene selected by the user from the multiple candidate lighting scenes through the user's input information.

Step 6: The terminal determines an illumination mapping model corresponding to the target illumination environment according to the target illumination environment. The light mapping model is used to indicate the mapping relationship between the fourth spectral response curve and the CIE XYZ domain. The terminal obtains the value of the fourth spectral response curve mapped to the CIE XYZ domain according to the illumination mapping model.

For example, the terminal may acquire pre-learned illumination mapping models under multiple candidate illumination environments. According to the target lighting environment selected by the user, the target lighting environment is selected from a plurality of candidate lighting environments, and the value of the fourth spectral curve mapped to the CIE XYZ domain is obtained according to the lighting mapping model corresponding to the target lighting environment.

It should be noted that, in steps 1 to 4, the spectral information is processed in the frequency domain, and a spectral response curve in the frequency domain is obtained. In order to be compatible with or support the application of spectral detection in the traditional three-color gamut in the prior art. Finally, the spectral response results in the frequency domain can be converted to values in the L*a*b domain. For example, in this step, the spectral response curve in the frequency domain can also be directly converted into the value in the L*a*b domain.

As a preferred solution, since the CIE XYZ domain has a better linear relationship with the frequency domain, according to the illumination mapping model, the fourth spectral response curve can be obtained and converted to the value of the CIE XYZ domain, and then the value of the CIE XYZ domain can be converted. to the value of the L*a*b domain. As a result, a value in the L*a*b domain with higher accuracy and closer to the color of the object to be measured can be obtained.

Optionally, in the scheme of Fig. 4, it also includes:

Step 7. After the terminal obtains the value of the L*a*b domain of the fourth spectral response curve of the skin color of the skin to be tested, the terminal can compare the value of the L*a*b domain corresponding to the fourth spectral response curve with a variety of values. The L*a*b values of the skin beautifying products (for example, liquid foundation) are matched, and according to a predetermined matching rule, the target skin beautifying product with the color number that best matches the skin color of the tested skin is selected, and the user is recommended.

Optionally, a database of skin-beautifying products under different lighting environments can be constructed locally, and steps 1-6 in FIG. 4 can also be used for the database construction of skin-beautifying products. For example, the method in Figure 4 can be used to obtain the spectral response curves of skin beautifying products under different lighting environments, and determine the values mapped to the CIE XYZ domain, and then convert them into L*a*b values. And the test results (CIE XYZ value or L*a*b value) of various skin care products can be saved in the local or cloud database.

Wherein, the above-mentioned predetermined matching rule may be a matching algorithm. For example, a matching algorithm such as the minimum error method and the shortest Euclidean distance method may be used, which is not limited in this embodiment of the present invention.

The method for spectral detection according to the embodiment of the present invention is described in detail above with reference to FIG. 1 to FIG. 4 , and the terminal of the embodiment of the present invention will be described in detail below with reference to FIG. 5 to FIG. 7 .

FIG. 5 is a schematic block diagram of a terminal according to an embodiment of the present invention. It should be understood that the terminal 500 in FIG. 5 can execute the steps of the methods in FIG. 2 to FIG. 4 . In order to avoid repetition, details are not described here. The terminal 500 includes:

an acquisition module 510, configured to acquire the first spectral response curve of the object to be measured under the light source and the current ambient light through the light sensor;

A determination module 520, configured to determine the second spectral response curve of the current ambient light;

The determining module 520 is further configured to determine a third spectral response curve according to the first spectral response curve and the second spectral response curve, where the third spectral response curve is the filter of the object to be tested. The spectral response curve after the disturbance of the current ambient light;

The determining module 520 is further configured to determine a fourth spectral response curve of the target attribute of the object to be measured according to the third spectral response curve.

After the first spectral response curve of the object to be measured is obtained, the second spectral response curve of the ambient light is determined, and the interference of the ambient light in the first spectral response curve is eliminated according to the second spectral response curve, so as to obtain a better spectral characteristic. Accurate spectral response results improve the efficiency of terminal spectral detection.

Based on the same inventive concept, since the principle of solving the problem of the mobile terminal is similar to the method in the method embodiment of the present invention, the implementation of the terminal can refer to the implementation of the method, and the repetition will not be repeated.

FIG. 6 is a schematic block diagram of a terminal according to an embodiment of the present invention. It should be understood that the terminal in FIG. 6 can perform each step of the method in FIG. 2 to FIG. 4 . In order to avoid repetition, details are not described here, and the terminal 600 includes:

a memory 610 for storing programs;

The processor 620 is configured to execute the program stored in the memory 610. When the program is executed, the processor 620 is configured to obtain the first spectral response of the object to be measured under the light source and the current ambient light through the light sensor curve; determine the second spectral response curve of the current ambient light; determine a third spectral response curve according to the first spectral response curve and the second spectral response curve, the third spectral response curve is the A spectral response curve of the object to be measured after filtering out the interference of the current ambient light; and a fourth spectral response curve of the target attribute of the object to be measured is determined according to the third spectral response curve.

After the first spectral response curve of the object to be measured is obtained, the second spectral response curve of the ambient light is determined, and the interference of the ambient light in the first spectral response curve is eliminated according to the second spectral response curve, so as to obtain a better spectral characteristic. Accurate spectral response results improve the efficiency of terminal spectral detection.

Based on the same inventive concept, since the principle of solving the problem of the mobile terminal is similar to the method in the method embodiment of the present invention, the implementation of the terminal can refer to the implementation of the method, and the repetition will not be repeated.

FIG. 7 is a schematic structural diagram of a system chip according to an embodiment of the present invention. The system chip 700 in FIG. 7 includes an input interface 710, an output interface 720, at least one processor 730, and a memory 740. The input interface 710, the output interface 720, the processor 730, and the memory 740 are connected through a bus. The processor 730 is configured to execute the code in the memory 740, and when the code is executed, the processor 730 implements the methods in FIGS. 2 to 4 . Based on the same inventive concept, since the principle of solving the problem of the mobile terminal is similar to the method in the method embodiment of the present invention, the implementation of the terminal can refer to the implementation of the method, and the repetition will not be repeated.

Additionally, the terms "system" and "network" are often used interchangeably herein. The term "and/or" in this article is only an association relationship to describe the associated objects, indicating that there can be three kinds of relationships, for example, A and/or B, it can mean that A exists alone, A and B exist at the same time, and A and B exist independently B these three cases. In addition, the character "/" in this document generally indicates that the related objects are an "or" relationship.

It should be understood that, in this embodiment of the present invention, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean that B is only determined according to A, and B may also be determined according to A and/or other information.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. Interchangeability, the above description has generally described the components and steps of each example in terms of function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of the present invention.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, for the specific working process of the above-described systems, devices and units, reference may be made to the corresponding processes in the foregoing method embodiments, and details are not repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may also be electrical, mechanical or other forms of connection.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solutions in the embodiments of the present invention.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or a part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: U disk, removable hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes.

In order to make the application documents concise and clear, the technical features and descriptions in one of the above embodiments can be understood to be applicable to other embodiments, and will not be repeated in other embodiments.

Claims (10)

1. a method for spectral detection, is characterized in that, comprises: The terminal obtains the first spectral response curve of the object to be measured under the light source and the current ambient light through the light sensor, and the light source is arranged in the terminal; determining, by the terminal, a second spectral response curve of the object to be measured under the current ambient light; The terminal determines a third spectral response curve according to the first spectral response curve and the second spectral response curve, where the third spectral response curve is the interference of the object to be measured that filters out the current ambient light After the spectral response curve; The terminal determines, according to the third spectral response curve, a fourth spectral response curve of the target attribute of the object to be measured; Wherein, the terminal determines the second spectral response curve of the object to be measured under the current ambient light, including: obtaining, by the terminal, the second spectral response curve of the object to be measured under the current ambient light through the light sensor; The light sensor is a multispectral sensor. 2. The method of claim 1, wherein the terminal determines a fourth spectral response curve of the target attribute of the object to be measured according to the third spectral response curve, comprising: The terminal determines the fourth spectral response curve according to the third spectral response curve, the filter function model of the light sensor, the reflection model of the target attribute of the object to be measured, and the energy distribution function of the light source. 3 . The method according to claim 2 , wherein the terminal uses the third spectral response curve, the filter function model of the light sensor, the reflection model of the target attribute of the object to be measured, and the The energy distribution function of the light source determines the fourth spectral response curve, including: The terminal determines the fourth spectral response curve according to the formula Y(λ)=∫F(λ)R(λ)I(λ)dλ, where Y(λ) represents the third spectral response curve, F( λ) represents the filter function model of the light sensor, the R(λ) represents the reflection model of the target property of the object to be measured, and the I(λ) represents the energy distribution function of the light source. 4. The method according to any one of claims 1 to 3, wherein the method further comprises: The terminal determines the target lighting scene; The terminal determines, according to the target illumination scene, an illumination mapping model between the fourth spectral curve and the CIE XYZ domain; The terminal determines, according to the illumination mapping model, the value of the fourth spectral curve mapped to the CIEXYZ domain. 5. The method according to claim 4, wherein determining the target lighting scene by the terminal comprises: obtaining, by the terminal, user input information, where the input information is used to indicate the target lighting scene; The terminal determines the target illumination scene from a plurality of candidate illumination scenes according to the input information, and the plurality of candidate illumination scenes and a plurality of illumination mapping models have a corresponding relationship; The terminal determines, according to the target illumination scene, an illumination mapping model between the fourth spectral curve and the CIE XYZ domain, including: The terminal determines, according to the corresponding relationship, the illumination mapping model corresponding to the target illumination scene. 6. A terminal, characterized in that, comprising: an acquisition module, used for acquiring the first spectral response curve of the object to be measured under the light source and the current ambient light through the light sensor; a determination module, configured to determine the second spectral response curve of the object to be measured under the current ambient light; The determining module is further configured to determine a third spectral response curve according to the first spectral response curve and the second spectral response curve, where the third spectral response curve is the filter of the object to be tested to remove the current spectral response curve. The spectral response curve after the interference of ambient light; The determining module is further configured to determine a fourth spectral response curve of the target attribute of the object to be measured according to the third spectral response curve; Wherein, the determining module is specifically configured to obtain the second spectral response curve of the object to be measured under the current ambient light through the optical sensor; The light sensor is a multispectral sensor. 7 . The terminal according to claim 6 , wherein the determining module is specifically configured to reflect the third spectral response curve, the filter function model of the optical sensor, and the target attribute of the object to be measured. 8 . The model and the energy distribution function of the light source determine the fourth spectral response curve. 8. The terminal according to claim 7, wherein the determining module is specifically configured to determine the fourth spectrum according to the formula Y(λ)=∫F(λ)R(λ)I(λ)dλ a response curve, wherein Y(λ) represents the third spectral response curve, F(λ) represents the filter function model of the light sensor, and R(λ) represents the reflection model of the target attribute of the object to be measured, The I(λ) represents the energy distribution function of the light source. 9. The terminal according to any one of claims 6 to 8, wherein the determining module is further configured to determine a target lighting scene; according to the target lighting scene, determine the fourth spectral curve and the CIE XYZ an illumination mapping model between domains; according to the illumination mapping model, determine the value of the fourth spectral curve mapped to the CIE XYZ domain. 10. The terminal according to claim 9, wherein the determining module is specifically configured to acquire user input information, the input information being used to indicate the target lighting scene; The target lighting scene is determined from the candidate lighting scenes, and the multiple candidate lighting scenes and multiple lighting mapping models have correspondences; according to the correspondences, the lighting mapping models corresponding to the target lighting scenes are determined.