KR101958539B1 - Apparatus and method for discriminating a concrete status using a hyperspectral image - Google Patents

Abstract

The concrete state determining apparatus of the present invention may include an ultrasound camera for acquiring an ultrasound image of concrete, a display unit for displaying a concrete image, and a concrete state determining unit functionally connected to the ultrasound camera and the display unit. The concrete state judging unit may extract a spectrum from the obtained ultrasonic image, determine a concrete region in an abnormal state by analyzing the extracted spectrum, and display the abnormal region determined through the display unit on the concrete image.

Description

[0001] APPARATUS AND METHOD FOR DISCRIMINATING A CONCRETE STATUS USING A HYPERSPECTRAL IMAGE [0002]

The present invention relates to an apparatus and a method for determining an abnormal state of concrete based on an ultrasound image.

Degradation of concrete structures can be caused by various causes, and one of these degradation causes can be water (moisture). Factors influencing the durability of concrete structures may be physical and chemical factors. Physical factors affecting durability can be extreme temperature conditions such as surface wear, cracking due to crystal pressure in the pores, freezing and flames. Chemical factors affecting durability may be dissolution of cement due to acid solution, expansion reaction by sulphate or alkali aggregate reaction, corrosion of steel in concrete, concrete in seawater, and so on.

White streaks and / or delamination can be caused by this deterioration. Efflorescence is white crystals generated on the surface of aged concrete. Calcium sulfate, magnesium sulfate, calcium hydroxide, etc. in concrete can be formed by leaching into water and combining with carbon dioxide in the atmosphere. The reason for the occurrence of the whitewater is that the soluble matter in the cement is precipitated from the surface immediately after the concrete is poured, and the soluble matter in the concrete moves to the concrete surface due to intrusion of the excellent and ground water into the concrete structure. The whitewater may occur at the site where the water penetrates into the concrete structure with capillary voids or defects where cracks have occurred. Therefore, it is necessary to perform a detailed inspection of the site where the whiteness occurs and judge the presence of cracks or other defects, so that the fundamental repair of the structure should be given priority. Concrete peeling and peeling can be caused by causes such as freezing and melting. Concrete scaling is a gradual loss of mortar on the concrete surface, and spalling can be a phenomenon that concrete fragments fall off along cracks.

It is necessary to pay close attention to the site of occurrence as a sign indicating the degree of deterioration of the concrete structure. In general, the diagnosis and quantification of the whiteness and degradation of concrete are mainly carried out through visual inspection. It is difficult to completely distinguish it from the pollutant, and it may be difficult to quantify the volume of actual peeling by measuring only the depth and width of the peeling. In addition, there may be a blind spot in the detection of damage if the structure in which the whitewash and backlash are generated is a structure difficult to access by professional workers.

The apparatus and method for determining the state of concrete according to various embodiments of the present invention can provide an apparatus and method for determining an abnormality of concrete by obtaining an ultrasound image of a concrete structure.

The apparatus and method for determining the state of concrete according to various embodiments of the present invention are capable of determining an abnormal state of concrete by analyzing an ultraspectral image of a concrete structure and displaying an abnormal region on a concrete image based on the discriminated result Apparatus and method.

According to another aspect of the present invention, there is provided an apparatus for determining a concrete state, including: an ultrasound camera for acquiring an ultrasound image of concrete; a display unit for displaying a concrete image; And a concrete state determination unit operatively connected to the control unit. The concrete state judging unit may extract a spectrum from the obtained ultrasonic image, determine a concrete region in an abnormal state by analyzing the extracted spectrum, and display the abnormal region determined through the display unit on the concrete image .

According to another aspect of the present invention, there is provided a method for determining a concrete state, the method comprising: obtaining a concrete image through an ultrasound camera; extracting spectra of a set band in the ultrasound image; Analyzing a spectrum corresponding to at least one concrete parameter set in the extracted spectra; determining an abnormal region of concrete based on the analyzed spectrum; And displaying the image to be displayed.

According to the present invention, the concrete state determination apparatus and method can determine the state of concrete based on non-contact, non-destructive basis, and thereby can easily detect the back and fall of concrete without damaging the concrete structure. In addition, by determining the concrete state based on the ultrasound image, it is possible to secure the reliability of the white spot detection as compared with the visual determination method, and to detect a wide range within the range of the focus and resolution. In addition, unmanned aerial vehicles can be used to remotely probe concrete structures that are difficult for people to access (eg, bottom plate, pylon, bridge, etc.).

1A to 1C are views for explaining the operation of an ultrasound camera.
2A to 2E are diagrams showing spectral characteristics of a concrete image.
FIGS. 3A and 3B are views for explaining an operation of acquiring an ultrasonic image for discriminating a concrete state using a specimen. FIG.
FIGS. 4A to 4D are views for explaining the spectral characteristics of the ultra-spectral image of the normal concrete and the white concrete. FIG.
Figures 5A-5E are diagrams illustrating examples of determining concrete conditions based on the ultra spectral spectral characteristics in accordance with various embodiments of the present invention.
6A and 6B are views for explaining another method for determining the state of concrete.
FIG. 7 is a view showing a configuration of a concrete condition determining apparatus according to various embodiments of the present invention. FIG.
8 is a view showing a processor configuration of a concrete condition determining apparatus according to various embodiments of the present invention.
9 is a view showing another configuration of a processor in a concrete condition determining apparatus according to various embodiments of the present invention.
10 is a flow chart illustrating a concrete state determination method in accordance with various embodiments of the present invention.
Figure 11 is a flow chart illustrating one embodiment of a concrete condition determination method in accordance with various embodiments of the present invention
12 is a flow chart illustrating another embodiment of a concrete condition determination method in accordance with various embodiments of the present invention.

Prior to the detailed description of the present invention, the terms or words used in the present specification and claims should not be construed as limited to ordinary or preliminary meaning, and the inventor may designate his own invention in the best way It should be construed in accordance with the technical idea of the present invention based on the principle that it can be appropriately defined as a concept of a term to describe it. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and are not intended to represent all of the technical ideas of the present invention. Therefore, various equivalents It should be understood that water and variations may be present.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that, in the drawings, the same components are denoted by the same reference symbols as possible. Further, the detailed description of known functions and configurations that may obscure the gist of the present invention will be omitted. For the same reason, some of the elements in the accompanying drawings are exaggerated, omitted, or schematically shown, and the size of each element does not entirely reflect the actual size.

The durability of concrete structures can mean the ability to have mechanical and functional capabilities to withstand degraded external forces such as weather, physical / chemical and mechanical actions. Therefore, the durability of the concrete structure may be deteriorated by various deterioration causes. Therefore, the concrete structure may need periodic safety diagnosis. For example, the reinforcement period of bridges can be 15-20 years. Currently, about 40% of the highway bridges that are being used in our country are bridges constructed before 2000, and the demand for maintenance can be increased rapidly in the near future. The maintenance of bridges is now shifting from safety to performance, and the importance of durability evaluation is increasing.

In order to diagnose the safety of concrete structures, there is a need for a method for non - contact and non - destructive discrimination of abnormal state of concrete structures. The abnormal state of the concrete can be white and / or peeling. Concrete whitewash and / or lacquer are an indication of the aging of concrete, so it may be necessary to detect and quantify the white matter and lacquer of concrete.

Various embodiments of the present invention propose devices and methods that can perform diagnostics and quantification of white matter and delamination of concrete structures using hyperspectral images. Various embodiments of the present invention can distinguish ordinary concrete, white papers, and other contaminants from normal concrete by utilizing an ultra-spectral camera, and can display the position and size of the white and / or delaminated on concrete images. The ultrasound camera and concrete discrimination device can be configured in various forms. For example, ultra-spectroscopic cameras can be mounted on a satellite, mounted on satellites, and mounted on unmanned aerial vehicles (UAV, drone, etc.). Therefore, it is possible to diagnose and quantify white matter and peeling in a place where manpower access is dangerous or impossible by utilizing a human body equipped with an ultra-spectral camera.

A hyperspectral image can be high dimensional data that has reflectivity over a wide range of wavelengths over many bands. Ultrasound images can be used for effective band extraction, preprocessing, target detection, and material classification.

1A to 1C are views for explaining the operation of an ultrasound camera.

Referring to FIG. 1A, the ultra-spectral camera

A target 111 that is a scan unit for acquiring one-dimensional spatial information, a first-half optical unit 113 and a slit 115 for acquiring one-dimensional spatial information at a desired position, A collimator lens 117 that makes the one-dimensional information into parallel light before being projected on the dispersion element, a diffractive element 119 that disperses the light, a dispersive element 119 that is collimated, A focusing lens 121 for collecting the collected light and a detector 123 for detecting the condensed optical signals. 1A, the slit 115, the collimator 117, the spectroscope 119, and the condenser 121 may be a spectroscope 125. The spectroscope 125 can perform a function of spectroscopically dividing the light of each point of the line-shaped area into a wavelength band by a special prism and a grading structure.

The push-broom type ultra-spectral camera as shown in FIG. 1A can detect ultraspectral images in three steps of image scanning, image spectroscopy and image merging. The ultrasound camera scans the object (111) in the horizontal axis using the rotating mirror and slit in the first image scanning step, acquires a one-dimensional line image passing through the slit each time, and in the second image spectral step Dimensional spectra can be extracted by spectroscopy of the obtained one-dimensional linear image, and three-dimensional superspectral images can be detected by sequentially collecting the two-dimensional spectra extracted in the last image merging process.

Referring to FIG. 1B, the subject 131 may be a concrete structure. When a subject 131, which is a concrete structure, is photographed using an ultrasound camera, a spectrum for one pixel 133 can be detected with spectra such as reference numeral 135. [ The spectrum of reference numeral 135 may be an example of a band from 400 nm to 700 nm (e.g., a visible light band).

Referring to FIG. 1C, an ultrasound camera can acquire spectra representing the characteristics of a subject through hundreds of spectral channels. In the ultrasound camera, a photographable wavelength band can be determined according to the characteristics of the spectroscope 125. For example, it is possible to detect spectra according to. The ultrasound camera can detect the spectra of the visible light band 151 and / or the infrared light band 153 according to the configuration of the spectroscope 125. A spectroscopic camera in the visible band (400-700 nm) can detect spectra in the visible light region of the subject. The infrared region 153 may include near-infrared (VNIR), short-wavelength-infrared (SWIR), mid-wavelength-infrared (MWIR), long-wavelength-infrared (LWIR), very long- infrared, far-infrared (FIR)) regions.

VNIR (700-1000 nm) can be spectral information related to color and some near-infrared band, and can be used in a visible range where a fine distinction is required with respect to color. SWIR (1000 ~ 2500nm) is a short wavelength infrared band, can be used for chemical difference of materials, analysis of difference in mineral characteristics, analysis of thin inner layer. MWIR and LWIR (2600 ~ 5000nm, 8000 ~ 12000nm) can be used in medium and long wavelength infrared band, and can be used for chemical difference, analysis of difference in thermal property and can not be used at room temperature.

The ultra-spectral camera for determining the state of concrete can use an ultra-spectral camera capable of extracting the spectrum of the SWIR band of the visible light band and / or the infrared light band. The concrete abnormality determination apparatus according to various embodiments of the present invention can use an ultra-spectral camera of visible light band or an ultra-spectral camera of visible light and SWIR band. For example, the concrete condition determination apparatus of the present invention can use an ultra-spectral camera capable of covering visible light and the SWIR band, and ENVI software capable of analyzing spectra obtained from an ultra-spectral camera.

The abnormal condition of concrete will be explained by assuming that it is white

2A to 2E are diagrams showing spectral characteristics of a concrete image.

Referring to FIG. 2A, reference numerals 211 and 213 may be a part of concrete, and may include white mat. When a concrete such as 211 is photographed using a general camera (2D camera), an image such as 213 can be obtained. However, when a concrete such as 215 is photographed using an ultra-spectral camera, ultra-spectral images such as 217 can be obtained.

The color of the ultrasound image extracted from the visible light region (400-740 nm) can be detected as gray in the case of ordinary concrete and the white color can be detected as light gray or white, Gray or dark gray (aggregate exposure). Therefore, in the case of detecting white spot and / or lacuna using only color, the accuracy may be lowered. If concrete is continuously exposed to moisture, the probability of occurrence of white matter can be high. For example, thermal characteristics can be changed depending on the mineral characteristics and moisture of the whitewash area, and thermal characteristics can be changed by the aggregate exposure in the delaminated area. Thus, the spectra can be extracted based on the moisture / thermal properties of white matter and / or delustering using an ultra-spectral camera whose detection region is the NIR region (740nm-1000nm) or the SWIR region (100nm-2500nm).

FIG. 2B is a diagram illustrating the absorption depth and position of the spectrum depending on the absorption rate. When an object is photographed using an ultrasound camera, the absorption band may vary depending on the characteristics of the component contained in the object material. The depth, area and / or location of the absorption band of the ultrasound image can be used to detect the white matter and / or delamination of the concrete.

FIG. 2C is a diagram showing a reflection height and position according to reflectance. FIG. Even if they have the same color, they can have different reflection forms (eg, reflectance peak, increase / decrease of reflectance (ratio), reflectance slope, etc.) depending on the constituents of the target material. Therefore, in a target material having the same color, it is possible to detect white matter and / or delamination of concrete by using different reflection characteristics as described above in analyzing the constituents.

FIG. 2D is a diagram showing the characteristics of the mean and standard deviation of the spectrum. FIG. If there is no characteristic or weak substance to be absorbed in a particular spectrum, the average and standard deviation of the spectrum can be used to detect the white matter and / or delamination of the concrete.

FIG. 2F is a diagram showing a characteristic of the continuity of spectral curves. FIG. The spectra of the ultrasound image can be varied depending on the properties of the material. If the continuity of the spectral curve is utilized, the properties of the regression line of the continuous curve can be used to detect the white matter and / or delamination of the concrete.

FIGS. 3A and 3B are views for explaining a specimen production and an ultra-spectral image acquisition operation for determining the state of concrete.

Referring to FIG. 3A, a specimen for determining the state of concrete can be generated. The resulting specimen may be a white and / or white specimen. White shrubs can occur under low temperature and high humidity conditions. When concrete is exposed to a thin water layer, carbon dioxide gas (CO2) dissolves well and can generate white matter. As shown in FIG. 3A, a large-size concrete (cementious material) 311 is manufactured and a water film 313 is formed on one side (for example, the upper side of the specimen 311) Can be generated. At this time, if fly ash / slag is included in the concrete 311, it is possible to easily produce the fly ash / slag. Further, when the water layer 313 is formed, it is possible to easily produce a whiteness by soaking one surface in warm water of a low height and exposing it to a low atmospheric temperature and a high humidity (for example, using a humidifier).

The back rock specimens can be made of concrete specimens and damaged in various forms to produce specimens with size-separated specimens.

3B, an ultra-spectroscopic camera 331 is installed to detect white spots and / or delamination, and a reflector 333 (for example, barium sulphate) 333 is provided at a position close to the concrete specimen 335 Can be installed. Then, illumination can be installed in the direction of the concrete specimen 335 from the ultra-spectral camera 331. The rough surface to be installed at this time can be provided with two halogen light (for example, Fomex H1000, 650W) on the left and right sides of the ultra-spectral camera 331. Also, the concrete specimen 331 may be a white specimen or a back rock specimen. For example, if it is a white pawn, it may be a specimen containing white papers of various types. The white type can be the white type concentration (dark type, lightly white type), white type (white type with narrow distribution, white type with wide distribution) and the like.

In the experiment, various types of spectra can be obtained by performing imaging and illumination conditions of the ultrasound camera with various options. For example, the ultra-spectral images of the concrete specimen 331 can be obtained by changing the pixel and spectral averaging of the ultrasound camera, the exposure time, the focal distance, the spacing between the specimen and the illumination, and the like. Spectra of the acquired spectroscopic images can be analyzed (e.g., using Envi software and Matlab). At this time, the concrete state determination device can analyze and store peak values of spectra based on normal concrete and abnormal conditions (e.g., white and / or white), average values of spectra, and slope information of spectrum. The peak values, average values, and / or slope information stored at this time are the normal concrete spectrum extracted from the ultra-spectral image obtained at various conditions (e.g., pixel condition, exposure and exposure time condition, illumination condition, Information obtained based on unsteady concrete spectra, and information obtained along with corresponding conditions can be stored and managed as a library.

FIGS. 4A to 4D are views for explaining the spectral characteristics of the ultra-spectral image of the normal concrete and the white concrete. FIG.

The spectra shown in Figs. 4A to 4C can be obtained in the photographing as shown in Fig. 3B. FIG. 4A can be a hyperspectral image spectrum of a white background, FIG. 4B can be a concrete ultrasound image spectrum, and FIG. 4C can be a reflector hyperspectral image spectrum. 4A and a concrete spectrum as shown in FIG. 4B are similar to each other in a visible light band (for example, 400 nm to 700 nm) and a VNIR infrared band (for example, 700 nm to 1000 nm) And it can be seen that there is a large difference in the amount of reflected light. Also, the spectral shape of the reflector has a similar shape to the white and concrete spectrum. Thus, in the case of an ultrasound camera capable of acquiring ultrasound images of the visible and VNIR bands, the spectroscopic spectrum can be normalized to reflect reflectance between 0 and 1.

FIG. 4D is a view showing an example of the regular ultrasonic spectra of the concrete ultrasonic spectra and the white ultrasonic spectra. The concrete specimen 451 may be a specimen including a spruce. Normalization of the concrete ultrasound spectrum as shown in FIG. 4B reveals that it has a higher reflectance than other regions at 550 nm - 770 nm, and has a low reflectance of 0.1 - 0.2. It can be seen from FIG. 4 (a) that normalized white spot spectroscopy spectrum has a constant reflectance in all regions above 550 nm and has a high reflectivity of 0.4 - 0.275.

Concrete specimens can be used to acquire an ultrasound spectral image of concrete and white matter and / or delamination, and to normalize the acquired images. The library can then be determined based on the normalized ultra-spectral spectrum to determine the state of the concrete. The concrete condition determining device according to various embodiments of the present invention can determine the state of a large concrete structure such as a bridge, a building, and the like. Large concrete structures can be photographed with different amounts of light depending on their location (for example, where they can and can not receive sunlight). It is possible to acquire hyperspectral images (e.g., hyperspectral spectra such as concrete, white matter, and thinning) according to various shooting conditions, and use them to correct normalized hyperspectral spectra.

Figures 5A-5E are diagrams illustrating examples of determining concrete conditions based on the ultra spectral spectral characteristics in accordance with various embodiments of the present invention.

5A is a diagram showing an example of determining concrete conditions based on a spectral peak value. The spectral peak value can be the maximum reflectance of the spectrum independent of the band. If a normalized spectrum is used as shown in FIG. 4D, the spectrum of concrete and white matter can be classified at a reflectance of about 0.3. That is, the threshold value can be set to reflectance 0.3, and the white matter and concrete can be classified based on the spectral peak value. In FIG. 5A, 511 may be an image with a background in concrete, and 515 may be a spectral profile of normalized hyperspectral images. At 515, conc can be a concrete spectrum, and effl can be a white matter spectrum. At this time, the normalized concrete and white spectrum can be divided into the boundary between the reflectance values of 0.3 and 0.5. If concrete and whites are discriminated based on the spectral peak value, the result of white matter detection such as 513 can be obtained. When the white spot is detected based on the spectral peak value, it can be detected with a high accuracy in a region where the white spot is concentrated as in 513, and the discrimination result may be deteriorated in a region where the white spot is lightly scattered.

FIG. 5B is a view showing an example of determining the concrete state based on the spectrum average value. FIG. The spectral average value can be brightness (brightness). Also, classification of white and concrete can be performed by setting the threshold value to reflectance of 0.3. In FIG. 5B, reference numeral 521 may be an image including a background in concrete, and reference numeral 525 may be a spectral profile of normalized hyperspectral images. At this time, normalized concrete and whiteweek spectra are set to reflectivity 0.3 as a threshold value, and when concrete and whiteness are discriminated on the basis of the spectrum average value, the whiteness detection result such as 523 can be obtained. When detecting white matter based on the average value of the spectrum, it can detect white matter in a thin part of the white part as in 523, and relatively low accuracy for bright white part.

5C is a diagram showing an example of determining concrete conditions based on the spectral slope. The spectral slope can be varied in relation to the material as a spectrum continuity characteristic. The backscattered spectrum slope can have a slope characteristic that is lower than the slope of the concrete spectrum in the 60 nm or more band. When determining the concrete condition, it is possible to classify the whites using the property that the concrete spectrum has a lower slope than the whitestone spectrum. In FIG. 5C, reference numeral 531 may be an image including a background in concrete, and reference numeral 535 may be a spectral profile of normalized hyperspectral images. At this time, normalized concrete and whiteweek spectra are set to a reflectance of 0.3 as a threshold value, and when the concrete and the whiteness are discriminated based on the spectral slant value, the whiteness detection result such as 533 can be obtained. When detecting a white matter based on the spectral slope, it is possible to detect the white matter well in the thinned portion of the white matter as shown in 533, and it can have a relatively low accuracy in the region in which the white matter appears clearly.

When determining the concrete condition, it is necessary to be able to identify the concentration of the whitewash generated in the concrete (the degree of occurrence of the whiteness deeply or lightly) and the occurrence areas of the whitewash. In this case, when discriminating by the peak value, the average value, or the slope of the spectrum, the discrimination of the whiteness can be made different according to the occurrence of the whiteness. That is, when the concrete state is determined, it may appear as a white-tailed predominantly occurring discrimination result according to the discrimination method, or may appear as a lightly-generated white-tailed position. Therefore, a method of determining the concrete state using a plurality of parameters may be used.

FIG. 5D is a view showing an example of determining the concrete state based on the peak value and the slope of the spectrum. FIG.

When the concrete and the whiteness are discriminated on the basis of the spectral peak value, the whiteness can be detected with high accuracy in the deeply generated portion, but the discrimination result may be deteriorated in the portion where the whitewater is lightly distributed. In addition, when detecting white matter based on the spectral slope, it is possible to detect white matter in a thin portion of the white matter, while having a relatively low accuracy in a region in which the white matter appears clearly. Therefore, if concrete condition is discriminated by using spectrum peak value and slope at the same time, it is possible to accurately discriminate all deeply generated and lightly generated whites.

In FIG. 5D, 541 may be an image with a background in concrete, and 545 may be a spectral profile of normalized hyperspectral images. At this time, normalized concrete and white-tailed spectra are set to a threshold value of 0.3 for reflectance, and after determining the concrete and the whiteness based on the spectral peak value and slope value, summing the two results, . When detecting a white matter based on the spectral peak value and the slope, it is possible to detect the white matter in both the dark and thin portions, as shown in 543.

FIG. 5E is a diagram showing an example of determining the state of concrete based on the average value and the slope of the spectrum. FIG.

When the white spot is detected based on the average or slope of the spectrum, the white spot can be detected even in a portion where the white spot is relatively thin compared to the spectral peak value. It is possible to classify the white matter by summing the results of the spectral average value and the slope method that detect the whiteness of the lighter portion in the spectral peak value.

Figures 5e and 551 can be images containing white matter in concrete, and 555 can be the spectral profile of normalized hyperspectral images. In this case, the normalized concrete and white spectrum can be obtained by setting the reflectance of 0.3 as the threshold value, determining the concrete and the whiteness based on the spectrum mean value and the slope value, and then summing the two results. In the case where the white matter is detected based on the spectral average value and the slope, the white matter occurrence area as shown in 543 can be more accurately detected (as shown in 553 of FIG. 5E, the detection result shown in 543 of FIG. And more accurately detected results).

Although not shown, the concrete state can be determined based on the peak value and the average value of the spectrum, and the concrete state can be determined based on the peak value, the average value, and the slope of the spectrum.

6A and 6B are views for explaining another method for determining the state of concrete.

6A is a diagram showing the relationship between the wavelength and the reflectance in a specific wavelength band (700 nm - 900 nm) in the ultrasonic spectroscopy. The concrete condition discriminator is capable of removing the convex hull in a specific wavelength band (continuum removal) and analyzing the local spectrum of the whitewash (or concrete).

FIG. 6B is a diagram showing the absorption in a specific wavelength band in an ultra spectroscopic spectrum. FIG. Depending on the nature of the components contained in the substance of interest, the extent to which light is absorbed may vary. Concrete may have a high absorptivity in a specific wavelength band, and the light reflectance may drop to a sudden level. For example, concrete may have an increased reflectance in the band below 190 nm wavelength, a higher light absorption rate in the 1900 nm -2000 nm band (1950 nm), and the reflectance may drop sharply, and the reflectance may reach the peak value at 2150 nm , And can be reduced at wavelengths after 2150 nm. The concrete condition discriminator can classify concrete and white matter using the depth or area (absorption depth and / or position) of a specific band with high absorption rate of concrete.

FIG. 7 is a view showing a configuration of a concrete condition determining apparatus according to various embodiments of the present invention. FIG.

Referring to FIG. 7, an ultrasound camera 710 may acquire an ultrasound image of a subject. The subject can be concrete. Ultrasound cameras can acquire ultraspectral images in the visible light band or ultrasound images in the visible and infrared bands (eg, VNIR and SWIR bands).

The memory 720 stores spectral values of concrete generated and corrected by the method described above, spectral values of anomalies (white matter, slope) included in concrete and reference values for classifying them (e.g., a first reference value, a second reference value Etc.). ≪ / RTI > This library may also be provided to correspond to the imaging conditions of the ultrasound camera (e.g., the location of the concrete being photographed (e.g., shaded area, bright area), exposure, number of pixels acquired, etc.).

The processor 700 may extract a spectrum of an ultraspectral image photographed by the ultrasound camera 710 and may analyze the extracted spectra based on the information of the memory 720. In accordance with the analysis result, State can be determined.

The processor 700 includes a spectrum extracting unit 751 for extracting a spectrum from an ultraspectral image output from the ultrasound camera 710, an analysis unit 751 for analyzing at least one parameter for determining concrete and anomalous states in the extracted spectra, A determination section 755 for determining the state of the concrete based on the analysis result of the spectrum and a concrete image processing section 755 for processing the concrete image including the concrete state determined by the determining section 755 so as to be displayed on the concrete image And an image processing unit 757.

The input unit 730 may generate an input for controlling the operation of the concrete determination device. The display unit 740 may display images processed in the processor 700.

In the following description, the subject will be concrete, and the abnormal state will be described as the case of the whitestock.

8 is a view showing a processor configuration of a concrete condition determining apparatus according to various embodiments of the present invention.

Referring to FIG. 8, the ultrasound camera 710 may acquire an ultrasound image of a visible light band and an infrared band of a subject. The subject can be a concrete image, and can be a concrete image containing a white matter.

The spectrum extracting unit 810 may correspond to the spectrum extracting unit 751 in FIG. The spectrum extracting unit 810 can extract a spectrum of a visible ray band or a spectrum of a visible ray and an infrared ray band in an ultrasound image. The spectral corrector 820 may calibrate the extracted spectra based on the imaging conditions of the hyperspectral image. The shooting conditions may be brightness and electromagnetic waves. For example, when the concrete structure is photographed, the spectral corrector 820 determines that the obtained ultrasound image reaches a position where the sunlight reaches directly, a shaded area in which sunlight is not directly reached, or a part of the area is located in a shaded area The exported spectrum can be calibrated based on the measurement of the brightness according to the condition (exposure condition).

The spectrum analyzer 830 may correspond to the spectrum analyzer 753 of FIG. The spectrum analyzer 830 may analyze the at least one parameter feature in the corrected spectrum to produce a result that can classify the concrete and the whiteness. The parameter may be at least one of a peak value, an average value and slopes of the spectrum. The peak value analyzer 861 sets the peak value of the maximum reflectance irrespective of the band in the corrected spectrum, and compares the set peak value with the threshold value. The average value analyzer 863 can compare and analyze the average value and the threshold value of the spectrum. The tilt analyzer 865 can analyze the slope of the spectrum. The slope of the spectrum can be extracted to different values depending on the material depending on the spectrum continuity characteristic. In other words, the slope of the concrete spectrum and the white spectrum in a specific band can have a different slope (the white slope spectrum has a higher slope than the concrete spectrum). The spectrum analyzer 830 may analyze the at least one spectral parameter to generate a result that can classify the concrete and the whiteness.

The determination unit 840 may correspond to the determination unit 755 in Fig. The determining unit 840 can determine whether the data is a whiteness based on at least one analysis result among the analysis results of the spectrum analyzing unit 830 and can generate the location information determined as the whiteness. For example, the determination unit 840 can determine whether the parameter is a parameter based on the analysis results of the two parameters in the spectrum analyzer 830. For example, the determining unit 840 can determine whether or not the image is white based on the analysis result of the spectral peak value and the average value analysis result of the spectrum. For example, the determining section 840 can determine whether or not it is white based on the analysis result of the spectral peak value and the slope analysis result of the spectrum. For example, the determining section 840 can determine whether or not it is white based on the spectral average value analysis result and the slope analysis result. For example, the determination unit 840 can determine whether or not it is white based on the spectral peak value analysis result, the spectrum average value analysis result, and the slope analysis result. The judging unit 840 can judge whether or not the whiteboard is based on the analysis result of the plurality of parameters, and add the determined result values to determine the whiteboard and whiteboard positions.

The image processing unit 950 processes the image photographed by the ultra-spectral camera 710, and can process the white area corresponding to the white matter concentration determined by the determination unit 840 to be included in the concrete image. The image processing unit 850 can display an image including the white area on the display unit 730 and display it, and can control the image to be stored in the memory 720. [

9 is a view showing another configuration of a processor in a concrete condition determining apparatus according to various embodiments of the present invention.

Referring to FIG. 9, the ultrasound camera 710 may acquire an ultrasound image of a visible light band and an infrared band of a subject. The subject can be a concrete image, and can be a concrete image containing a white matter.

The spectrum extracting unit 910 may correspond to the spectrum extracting unit 810 of FIG. The spectrum corrector 920 may correspond to the spectrum corrector 820 of FIG.

The spectrum analyzer 930 may correspond to the spectrum analyzer 830 of FIG. The spectrum analyzer 930 may analyze the at least one parameter feature in the corrected spectrum to produce a result that can classify the concrete and the whiteness. The parameter may be at least one of the reflectance of the spectrum, the absorption rate, and the slopes of the spectrum. The reflectance analyzer 971 may set the peak value and / or the average value of the spectrum, and may compare and analyze the set peak value and / or the average value with the threshold value. The reflectance analyzing unit 971 may correspond to the peak value analyzing unit 961 and the average value analyzing unit 963 of FIG. 8, and may include at least one of them. The absorption rate analyzing section 973 can analyze a signal in a band where the reflectance is rapidly lowered due to the high absorption rate. As shown in FIG. 6, the concrete ultrasound image has a high absorption rate in the 1900 - 2000 nm (1950 nm) wavelength band, and the reflectance may drop sharply. Therefore, by analyzing the spectra of the high absorption rate band, it is possible to generate an analysis result signal for judging whether or not the concrete and the whitewood are free. The slope analyzer 975 may correspond to the slope analysis 865 of FIG. The spectrum analyzer 930 may analyze at least one spectral parameter among reflectance, absorption rate, and spectral slope parameters to generate a result that can classify the concrete and the whiteness.

The determination unit 940 may correspond to the determination unit 840 in FIG. The determination unit 940 can determine whether the analysis result is based on at least one analysis result among the analysis result values of the spectrum analyzer 930 and generate the location information that is determined to be false. For example, the determining section 940 can determine whether the parameter is a parameter based on the analysis results of the two parameters in the spectrum analyzing section 930. For example, the judging unit 940 can judge whether or not it is white based on the analysis result of reflectance and absorption rate. For example, the determining section 940 can determine whether or not the information is based on the spectral reflectance and the slope analysis result. For example, the determining section 940 can determine whether or not a white spot is present based on the absorption rate and the slope analysis result. For example, the determining section 940 can determine whether or not the light source is based on the reflectance, the absorption rate, and the slope analysis result. The reflectance may be the peak value and / or the average value of the spectrum, and the determining section 940 may use one or both of the peak value and the average values. The judging unit 940 can judge whether or not the whiteboard is based on the analysis result of the plurality of parameters, and add the determined result values to determine the whiteboard and whiteboard positions.

The image processing unit 950 processes the image photographed by the ultra-spectral camera 710 and can process the white-tailed area according to the white matter concentration determined by the determination unit 940 to be included in the concrete image. The image processing unit 950 can output an image including the white area to the display unit 730 and display the image, and can control the image to be stored in the memory 720.

The concrete state determining device having the construction as shown in FIGS. 7 to 9 can be configured in various forms. Concrete structures can be bridges, large structures. Such a concrete structure may be difficult to be photographed using a hyperspectral camera due to natural obstacles and height of the structure. Therefore, it is possible to shoot a concrete structure by attaching an ultrasound camera to a unmanned aerial vehicle or a satellite. For example, in the case of an unmanned aerial vehicle (UAV) or a drone), the ultra-spectral camera is separated from the concrete state discrimination device and mounted on the unmanned aerial vehicle, and the unmanned aerial vehicle and the concrete state discrimination device each have a communication part . In this case, the communication unit may use a short-range wireless communication (wifi, wibro, etc.) method or a public wireless communication (LTE, WCDMA, etc.) method. When the unmanned aerial vehicle equipped with ultrasound camera and the concrete status discrimination device are operated in conjunction with each other, it is possible to economically and easily acquire information on the external damage of the concrete in the large concrete structure and to save the maintenance cost of the structure by the database have.

The concrete state determination method according to various embodiments of the present invention includes the steps of photographing the appearance of a concrete structure using an ultrasound camera and analyzing the spectral characteristics of each pixel of the photographed concrete ultrasound image to determine the state of the concrete can do. The ultrasound image obtained through the ultrasound camera includes spectral information (z) in addition to the two-dimensional spatial information (x, y). The spectroscopic information can be correlated with the chemical composition, crystal structure, temperature characteristics, and color of each material, and various spectral characteristics (for example, absorption depth, band ratio, etc.) can be expressed differently. The concrete state determination method according to various embodiments of the present invention can extract the difference in the spectral characteristics of the abnormal state included in the concrete and the concrete in the ultrasound image and analyze the abnormal state to determine the abnormal state included in the concrete. For example, a concrete anomaly can be white and / or cracked.

A method for determining a concrete state according to an embodiment of the present invention includes analyzing spectral characteristics of pixels of a concrete ultrasound image to determine the white pixels included in the concrete, And the area of the whitewash included in the concrete can be displayed.

10 is a flow chart illustrating a concrete state determination method in accordance with various embodiments of the present invention.

Referring to FIG. 10, an ultra-spectroscopic camera (e.g., the ultra-spectroscopic camera 710 of FIG. 7) can take an image of the appearance of the concrete structure for measuring the condition. The processor (e.g., processor 700 of FIG. 7) of the concrete condition determining apparatus may extract the spectrum of the ultra-spectral image in step 1013 when the ultra-spectral image is acquired in step 1011. FIG. In this case, the spectrum extracted from the ultrasound image may be a spectrum having the wavelength and the reflectance as shown in FIGS. 4A and 4B. In step 1013, the processor performs normalization with a spectral profile having a value between 0 and 1 as shown in FIG. can do. The processor can then analyze the spectral characteristics of the spectrum extracted in step 1015 and determine the state of the concrete based on the characteristics of the analyzed spectrum in step 1017. For example, the processor may determine that the pixel is a concrete or anomalous state by analyzing one or more parameters of reflectance, absorption and / or slopes of the spectrum of the corresponding pixel.

The processor can analyze and determine the state of each of the ultra-spectral images by repeating the operations of steps 1015 and 1017 as above. After analyzing the spectral characteristics of all the pixels of the acquired ultraspectral image and judging the state, the processor displays the result of the pixels determined in step 1019 on the display unit (e.g., the display unit 740 of FIG. 7, The processor can overlay the pixels of the abnormal state on the concrete image based on the determination result of the pixels, for example, when measuring the white surface, the displayed image is displayed on the concrete The location where the whitewash has occurred and the area where the whitewash has been generated can be displayed, and the concentration of the whitewater (for example, dark white or light white) can be displayed.

In the following description, the abnormal state of the concrete will be explained by taking the case of the pavement as an example. In the following description, the processor may be the processor 700 of FIG.

11 is a flow chart illustrating one embodiment of a concrete condition determination method in accordance with various embodiments of the present invention.

11, when a concrete ultrasound image is acquired by the ultrasound camera in step 1111, the processor can extract the spectrum from the ultrasound image obtained in step 1113, and the spectrum extracted in step 1115 can be corrected have. At this time, the correction of the spectrum may be correction for the photographing conditions (for example, brightness and / or spectrum of the light source), electromagnetic waves and the like.

The processor may then analyze the corrected spectra based on the corresponding parameters while performing at least one of steps 1117 through 1121. As described in FIGS. 5A to 5C, the slope of the spectrum peak value, the spectrum average value, and the spectrum of the whitewash can have a relatively higher or lower value than the spectral peak value, the spectrum average value, and the slope of the spectrum of the concrete have. Accordingly, the processor sets a reference value (threshold value) (e.g., a first reference value, a second reference value, etc.) of each parameter (peak value, average value, slope, etc.) for distinguishing the white matter and concrete from each other, And the state of the corresponding pixel can be analyzed. In step 1123, the processor may determine the concrete state according to the analysis result.

By repeating the above operation, superspectral images can analyze and judge the state for each pixel. After analyzing the spectral characteristics of all the pixels of the obtained ultraspectral image and judging the state, the processor displays the result of the pixels determined in step 1125 on a display part (for example, the display part 740 of FIG. 7, And may be stored in the memory 720.

12 is a flow chart illustrating another embodiment of a concrete condition determination method in accordance with various embodiments of the present invention.

Referring to FIG. 12, when the concrete ultrasound image is acquired by the ultrasound camera in step 1211, the processor can extract the spectrum from the ultrasound image acquired in step 1213, and the spectrum extracted in step 1215 can be corrected have.

The processor may then analyze the corrected spectra based on the corresponding parameters while performing at least one of steps 1217 through 1221. [ The processor may analyze the spectrum based on the reflection characteristics in step 1217. [ The reflection characteristic can be the peak value of the spectrum and / or the average of the spectrum. The processor can analyze the spectrum based on the peak value, the average value or the peak value and the average value. The processor may analyze the spectrum based on the absorption rate of the spectrum in step 1219. [ As shown in FIG. 6B, the concrete has a high absorptivity in a specific wavelength band, and the reflection characteristic may be rapidly deteriorated. Therefore, the processor can analyze the spectral characteristics that the absorption rate increases in a specific band. Processor 1221 may analyze the slope of the spectrum. In step 1223, the processor may determine the state of the concrete according to the analysis result.

By repeating the above operation, superspectral images can analyze and judge the state for each pixel. After analyzing the spectroscopic characteristics of all the pixels of the obtained ultrasound spectral image to determine the state, the processor displays the result of the pixels determined in step 1225 on a display part (e.g., the display part 740 of FIG. 7, And may be stored in the memory 720.

While the present invention has been described with reference to several preferred embodiments, these embodiments are illustrative and not restrictive. It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit of the invention and the scope of the appended claims.

Claims (14)

A display unit for displaying a concrete ultra-spectral image obtained through an ultra-spectral camera mounted on a unmanned aerial vehicle; And
And a concrete state determiner operatively connected to the ultrasound camera and the display unit,
The concrete state determining unit
A spectrum extracting unit for extracting a spectrum of a predetermined band in the concrete ultrasonic image;
A spectral correcting unit for correcting the extracted spectrum based on photographing conditions of the concrete ultrasonic image;
A spectrum analyzer for analyzing spectra corresponding to a plurality of concrete parameters including a peak value, an average value, and a slope of the spectrum in the corrected spectrum;
A determining unit determining an abnormal region of concrete based on the analyzed spectrum; And
And an image processing unit that performs image processing so that the determined abnormal region is displayed on the concrete ultrasonic image through the display unit,
The spectrum analyzer
Considering whether or not the peak value of the corrected spectrum exceeds a set first reference value, whether the average value of the corrected spectrum exceeds a set second reference value, and whether the slope of the corrected spectrum is higher than a set reference slope, Location,
And the determination unit determines the position, area, and white matter concentration of the abnormal region based on the information including the analyzed white spot position
Concrete condition determination device.


delete delete delete delete The method according to claim 1,
The spectrum analyzer
And analyzing the white spot position by further considering the reflectance and the absorption rate of the corrected spectrum.

delete delete Obtaining an ultrasound image of concrete through an ultra-spectral camera mounted on a unmanned aerial vehicle;
Extracting a spectrum of a predetermined band in the concrete ultrasonic image;
Correcting the extracted spectrum based on a photographing condition of the concrete ultrasonic image;
Analyzing a spectrum corresponding to a plurality of concrete parameters including a peak value, an average value, and a slope of the spectrum in the corrected spectrum;
Determining an abnormal region of concrete based on the analyzed spectrum; And
Performing image processing so that the determined abnormal region is displayed in the concrete ultrasonic image,
Wherein analyzing the spectrum comprises:
Considering whether or not the peak value of the corrected spectrum exceeds a set first reference value, whether the average value of the corrected spectrum exceeds a set second reference value, and whether the slope of the corrected spectrum is higher than a set reference slope, Analyzing the location,
Wherein the determining step comprises:
Determining an area, an area, and a white matter concentration of the abnormal region based on the information including the analyzed white spot position
Concrete condition determination method.

delete delete delete 10. The method of claim 9,
The step of analyzing the spectrum
Further comprising analyzing the white spot location with further consideration of the reflectivity and absorption rate of the corrected spectrum
Concrete condition determination method.

delete

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