JP7481200B2 - Evaluation system, evaluation method, and evaluation program - Google Patents

Description

One aspect of the present disclosure relates to an evaluation system, an evaluation method, and an evaluation program.

Technologies for evaluating concrete surfaces are known. For example, Patent Document 1 describes a method for detecting concave deformations that appear on the surface of a structure. Patent Document 2 describes a method for using a water-based paint that has a visible light transmittance of 50% or more at wavelengths of 360 to 750 nm and a haze of 70 or less, making it easy to visually check the concrete surface after construction.

JP 2017-211314 A JP 2019-7312 A

A mechanism for evaluating coatings applied to concrete surfaces is desirable.

An evaluation system according to one aspect of the present disclosure includes an image acquisition unit that acquires a captured image of a concrete surface to which a light-transmitting covering has been applied, a pixel value acquisition unit that sets a target area within the captured image and acquires pixel values corresponding to each of a plurality of pixels that constitute the target area, a standard setting unit that sets a pixel reference value for each of the plurality of pixels, a calculation unit that calculates the difference between the pixel value and the pixel reference value for each of the plurality of pixels, and an evaluation unit that evaluates the transmittance of the covering on the concrete surface based on the difference between each of the plurality of pixels.

In this aspect, the difference between the pixel value and the pixel reference value is calculated for each pixel in a target area set in the captured image, and the transparency of the covering body on the concrete surface is evaluated based on the difference. By considering the pixel value difference for each of the multiple pixels, the covering body can be appropriately evaluated.

According to one aspect of the present disclosure, a coating applied to a concrete surface can be evaluated. For example, the permeability of the coating can be evaluated.

FIG. 1 is a diagram illustrating an example of a functional configuration of an evaluation system according to an embodiment. FIG. 1 is a diagram illustrating an example of a general hardware configuration of a computer used for an evaluation system according to an embodiment. 4 is a flowchart showing an example of the operation of the evaluation system according to the embodiment. FIG. 13 is a diagram showing an example of setting a target region. FIG. 13 is a diagram showing an example of setting a target region. FIG. 13 is a diagram showing an example of evaluating transmittance. FIG. 13 is a diagram showing an example of evaluating transmittance. FIG. 13 is a diagram showing an example of evaluating transmittance. FIG. 13 illustrates an example of evaluating transparency using multiple target regions. FIG. 13 illustrates an example of evaluating transparency using multiple target regions.

Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In the description of the drawings, identical or equivalent elements are given the same reference numerals, and duplicate descriptions will be omitted.

[System Overview]
The evaluation system 1 according to the embodiment is a computer system for evaluating the permeability of a coating on a concrete surface. The evaluation system 1 may perform the evaluation on the concrete surface of any structure. For example, the structure may be a test specimen or a commonly used work (e.g., a building, a bridge, etc.). In one aspect of the present disclosure, the permeability of a coating applied to a concrete surface can be evaluated.

In this disclosure, a covering refers to a material that is applied to a concrete surface so as to cover the surface. A covering applied to a concrete surface adheres to the surface. For example, coverings are used to prevent concrete from spalling or to reinforce the concrete surface. However, the purpose of a covering is not limited to this. In this disclosure, a covering has optical transparency. Optical transparency refers to the property of transmitting light. Since a covering on a concrete surface has optical transparency, at least a portion of the light incident on the covering is reflected by the concrete surface and exits from the covering. Therefore, a person can see the concrete surface covered by the covering. There is no limitation on the components or combination of components that constitute a covering having optical transparency. For example, the covering may include an epoxy compound and a fiber-reinforced plastic (FRP).

The transmittance of a covering is an index that indicates the strength or level of the light transmittance of the covering. The stronger or higher the light transmittance, the higher the transmittance. The higher the transmittance of a covering, the more transparent the covering is, and the more clearly a person can see the concrete surface covered with the covering. In other words, the higher the transmittance, the higher the visibility of the concrete surface. Hereinafter, the transmittance of a covering will also be referred to simply as "transmittance." "Evaluating the transmittance of a covering" refers to a process that determines how high the transmittance is. In other words, evaluating the transmittance is a process that determines the degree of visibility of the concrete surface covered with the covering (i.e., how clearly the concrete surface can be seen).

The evaluation system 1 evaluates the transparency by analyzing a photographed image (hereinafter simply referred to as the "photographed image") of a concrete surface to which a covering body is applied. The photographed image is obtained by an imaging device such as a camera. The photographed image may be a still image or a frame image constituting a moving image. The evaluation system 1 sets a target area within the photographed image, and evaluates the transparency based on the difference between the pixel values corresponding to each of the multiple pixels constituting the target area and the pixel reference values of each of the multiple pixels. The target area refers to a portion that constitutes at least a part of the photographed image. The pixel value refers to a physical property value corresponding to the color of a pixel in the photographed image. On the other hand, the pixel reference value refers to a reference value used for comparison with the pixel value. More specifically, the pixel reference value is a pixel value obtained when a concrete surface to which no covering body is applied is photographed, or when it is assumed that such photography has been performed.

[System Configuration]
FIG. 1 is a diagram showing an example of the functional configuration of an evaluation system 1. The evaluation system 1 includes, as functional components, an image acquisition unit 11, a pixel value acquisition unit 12, a reference setting unit 13, a calculation unit 14, and an evaluation unit 15. The image acquisition unit 11 is a functional module that acquires a captured image. The pixel value acquisition unit 12 is a functional module that acquires a plurality of pixel values corresponding to a plurality of pixels that constitute a target area of the captured image. The reference setting unit 13 is a functional module that sets a plurality of pixel reference values corresponding to the plurality of pixels. The calculation unit 14 is a functional module that calculates the difference between the pixel value and the pixel reference value for each of the plurality of pixels. The evaluation unit 15 is a functional module that evaluates the transmittance based on the respective differences between the plurality of pixels.

Figure 2 is a diagram showing an example of a general hardware configuration of a computer 100 used for the evaluation system 1. For example, the computer 100 includes a processor 101, a main memory unit 102, an auxiliary memory unit 103, a communication control unit 104, an input device 105, and an output device 106. The processor 101 executes an operating system and application programs. The main memory unit 102 is composed of, for example, a ROM and a RAM. The auxiliary memory unit 103 is composed of, for example, a hard disk or a flash memory, and generally stores a larger amount of data than the main memory unit 102. The communication control unit 104 is composed of, for example, a network card or a wireless communication module. The input device 105 is composed of, for example, a keyboard, a mouse, etc. The output device 106 is composed of, for example, a monitor and a speaker.

Each functional module of the evaluation system 1 is realized by an evaluation program 110 pre-stored in the auxiliary memory unit 103. It is realized by loading the evaluation program 110 onto the processor 101 or the main memory unit 102 and executing the evaluation program 110. The processor 101 operates the communication control unit 104, the input device 105, or the output device 106 in accordance with the evaluation program 110, and reads and writes data in the main memory unit 102 or the auxiliary memory unit 103. Data or databases required for processing are stored in the main memory unit 102 or the auxiliary memory unit 103.

The evaluation program 110 may be provided by being permanently recorded on a non-transitory recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. Alternatively, the evaluation program 110 may be provided via a communication network as a data signal superimposed on a carrier wave.

The evaluation system 1 may be configured with one computer 100, or may be configured with multiple computers 100. When multiple computers 100 are used, these computers 100 are connected via a communication network such as the Internet or an intranet to logically construct a single evaluation system 1. The evaluation system 1 may be constructed as a client-server system, or may be constructed on a stand-alone computer.

[System Operation]
An example of the operation of the evaluation system 1 will be described with reference to Fig. 3. Fig. 3 is a flow chart showing an example of the operation of the evaluation system 1 as a process flow S1.

In step S11, the image acquisition unit 11 acquires a captured image. The method of acquiring the captured image is not limited. For example, the image acquisition unit 11 may receive the captured image from an imaging device or another computer. Alternatively, the image acquisition unit 11 may access a given database or file system to read the captured image. Alternatively, the image acquisition unit 11 may acquire a captured image input by a user of the evaluation system 1. The acquired captured image may be a color image or a grayscale image.

In step S12, the pixel value acquisition unit 12 sets one or more target regions within the captured image. The pixel value acquisition unit 12 sets a portion consisting of a set of multiple consecutively arranged pixels as the target region. The shape and dimensions of the target region are not limited and may be set according to any policy. For example, the pixel value acquisition unit 12 may set the entire captured image as the target region, or may set only a part of the captured image as the target region. The shape of the target region may be, for example, a rectangle, another polygon, a circle, an ellipse, or a line.

In one example, the pixel value acquisition unit 12 may set a portion of the concrete surface that captures a pattern as the target region. A pattern on a concrete surface refers to any shape that is visible to humans. The pattern may be the result of a physical phenomenon that occurs naturally on the concrete surface, such as a crack, dent, or hole. Alternatively, the pattern may be an artificially applied shape, such as a mark (e.g., a figure, letter, etc.) made by painting or printing.

Figure 4 shows some examples of setting the target area. Figure 4 shows a captured image 200 of a concrete surface printed with horizontal lines, diagonal lines, and black rectangles. The pixel value acquisition unit 12 may set the entire captured image 200 as the target area, and target area 201 is an example of this. Alternatively, the pixel value acquisition unit 12 may set a target area that is a part of the captured image 200 and only a part of it overlaps with the pattern, and target area 202 is an example of this. Alternatively, the pixel value acquisition unit 12 may set a target area that is a part of the captured image 200 and the entirety of it overlaps with the pattern, and target areas 203 and 204 are examples of this. The entire target area 203 overlaps with the black rectangle, and the entire target area 204 overlaps with the diagonal lines.

Figure 5 also shows some examples of setting the target area. Figure 5 shows a captured image 210 of a concrete surface printed with a crack scale. The pixel value acquisition unit 12 may set the entire captured image 210 as the target area, and target area 211 is an example of this. Alternatively, the pixel value acquisition unit 12 may set a target area that is a part of the captured image 210 and only a part of it overlaps with the pattern, and target area 212 is an example of this. Alternatively, the pixel value acquisition unit 12 may set a target area that is a part of the captured image 210 and the entirety of it overlaps with the pattern, and target area 213 is an example of this.

Returning to FIG. 3, in step S13, the pixel value acquisition unit 12 acquires pixel values of each pixel in the target region. More specifically, the pixel value acquisition unit 12 acquires pixel values corresponding to each of the multiple pixels.

The pixel value acquisition unit 12 may acquire a grayscale pixel value indicating the brightness of each pixel constituting the target area. The grayscale pixel value is expressed in 8 bits and therefore takes any integer value between 0 (black) and 255 (white). In one example, the pixel value acquisition unit 12 may convert a color image depicting the target area into a grayscale image and acquire the pixel values (i.e., grayscale pixel values) of each of the multiple pixels in the converted target area. That is, the pixel value acquisition unit 12 may convert the RGB values, which are the original pixel values, into grayscale pixel values for each of the multiple pixels in the target area. When the captured image is a grayscale image, the pixel value acquisition unit 12 acquires the grayscale pixel values of each of the multiple pixels in the target area directly from the captured image.

Alternatively, the pixel value acquisition unit 12 may convert the original pixel values of each pixel constituting the target area into a binary value and acquire the converted pixel values (binary pixel values). That is, the pixel value acquisition unit 12 may convert the image depicting the target area into a binary image. In one example, the pixel value acquisition unit 12 converts each pixel value (grayscale pixel value) of the grayscale image depicting the target area into a binary value. For example, the pixel value acquisition unit 12 converts each grayscale pixel value into either a first pixel value Px1 or a second pixel value Px2 based on a given boundary value Vb. In one example, the pixel value acquisition unit 12 converts a grayscale pixel value that is less than the boundary value Vb into a first pixel value Px1, and converts a grayscale pixel value that is equal to or greater than the boundary value Vb into a second pixel value Px2. The method of setting the boundary value Vb is not limited. For example, the boundary value Vb may be a fixed value such as 128, or may be dynamically set. The method of setting the first pixel value Px1 and the second pixel value Px2 is also not limited, and may be set according to any policy. In one example, the boundary value Vb may be 128, the first pixel value Px1 may be 0 (black), and the second pixel value Px2 may be 255 (white). Alternatively, the first pixel value Px1 and the second pixel value Px2 may be represented by the simpler binary values 0 and 1.

Alternatively, the pixel value acquisition unit 12 may acquire the RGB values of color pixels as pixel values for each pixel that constitutes the target region.

In step S14, the reference setting unit 13 sets pixel reference values for each pixel in the target region. The method for setting the pixel reference values is not limited, and may be designed according to any policy.

In one example, the reference setting unit 13 may set a pixel reference value based on a reference image that depicts the concrete surface before the covering is applied. The reference setting unit 13 acquires the reference image, sets a reference region within the reference image that depicts the same portion as the target region, and sets a pixel reference value for each of the multiple pixels that make up the reference region.

The reference setting unit 13 may obtain the reference image in any manner. For example, the reference setting unit 13 may receive the reference image from an imaging device or another computer. Alternatively, the reference setting unit 13 may access a given database or file system to read the reference image. Alternatively, the reference setting unit 13 may obtain the reference image input by a user of the evaluation system 1.

The reference setting unit 13 sets a reference area in the reference image. For example, when the target area 201 shown in FIG. 4 is set, the reference setting unit 13 sets a reference area that shows the same part as the target area 201. When the target area 203 shown in FIG. 4 is set, the reference setting unit 13 sets a reference area that shows the same part as the target area 203. When the target area 212 shown in FIG. 5 is set, the reference setting unit 13 sets a reference area that shows the same part as the target area 212. In order to associate the pixel values of each of the multiple pixels that make up the target area with the pixel reference value, the reference setting unit 13 performs a process of matching the size and orientation of the reference area to the target area (a process of matching the number and arrangement of pixels between the reference area and the target area) as necessary.

The reference setting unit 13 sets pixel reference values for each pixel in the reference region. For example, the reference setting unit 13 may set pixel reference values using a method similar to that used to acquire individual pixel values constituting the target region. When the target region is represented by a set of grayscale pixel values, the reference setting unit 13 sets individual pixel reference values by grayscale pixel values. In one example, the reference setting unit 13 may convert a color image depicting the reference region into a grayscale image and acquire the grayscale pixel values of each of the multiple pixels in the converted reference region. When the acquired reference image is a grayscale image, the reference setting unit 13 acquires the grayscale pixel values of each of the multiple pixels in the reference region directly from the reference image.

When the pixel values of the target region are represented by a set of binary pixel values, the reference setting unit 13 sets individual pixel reference values by the binary pixel values. The reference setting unit 13 converts the pixel values of each pixel constituting the reference region into binary values and obtains the converted pixel values. In one example, the reference setting unit 13 converts each grayscale pixel value of a grayscale image depicting the reference region into binary values. For example, the reference setting unit 13 converts each grayscale pixel value into either a first pixel value Px1 or a second pixel value Px2 based on the boundary value Vb. This conversion is similar to the method of obtaining binary pixel values for each pixel in the target region. The specific values of the boundary value Vb, the first pixel value Px1, and the second pixel value Px2 are set in the same way as when obtaining the binary pixel values of the target region.

When the pixel values of the target area are expressed as RGB values, the reference setting unit 13 sets individual pixel reference values by RGB values. The reference setting unit 13 obtains the RGB values of each pixel from a color image that depicts the reference area.

The reference setting unit 13 may set a pixel reference value for each of the multiple pixels that make up the target region without using a reference image. For example, the reference setting unit 13 may set individual pixel reference values according to user input. In this case, too, the pixel reference value may be set by a grayscale pixel value, may be set by a binary value consisting of a first pixel value Px1 and a second pixel value Px2, or may be set by an RGB value.

In step S15, the calculation unit 14 calculates the difference between the pixel value and the pixel reference value for each pixel in the target region. In one example, this difference is expressed by an absolute value. When the pixel value and the pixel reference value are expressed by a binary value, the calculation unit 14 calculates the difference between the two binary values. When the pixel value and the pixel reference value are expressed by a grayscale pixel value, the calculation unit 14 calculates the difference between the two grayscale pixel values (i.e., the difference in brightness). When the pixel value and the pixel reference value are expressed by an RGB value, the calculation unit 14 calculates the color difference ΔE* between the two color pixels. If the RGB values of the pixel value are expressed as (R ₁ , G ₁ , B ₁ ) and the RGB values of the pixel reference value are expressed as (R ₂ , G ₂ , B ₂ ), the color difference ΔE* is obtained by the following formula (1).

In step S16, the evaluation unit 15 evaluates the transmittance of the covering body based on the calculated differences. This evaluation method is not limited, and the evaluation unit 15 may evaluate the transmittance using any method.

In one example, the evaluation unit 15 may evaluate the transparency based on a proportion R of pixels that make up the target region, the difference between the pixel value and the pixel reference value being equal to or less than a given threshold value Th. The evaluation unit 15 may use the proportion R as is as an evaluation result for the transparency. Alternatively, the evaluation unit 15 may evaluate the transparency based on whether the proportion R is equal to or greater than a given evaluation reference value Ea.

For example, if the ratio R is equal to or greater than the evaluation reference value Ea, the evaluation unit 15 evaluates the transmittance as good, and if the ratio R is less than the evaluation reference value Ea, the evaluation unit 15 evaluates the transmittance as bad. The specific value of the evaluation reference value Ea is not limited, and may be set based on any policy. A relatively low difference between the pixel value and the pixel reference value at a certain pixel means that the appearance of the concrete surface is the same or similar before and after the covering is applied. Therefore, a relatively low difference means that the transmittance of the covering is relatively high. On the other hand, a relatively high difference at a certain pixel means that the appearance of the concrete surface has changed due to the application of the covering. This change in appearance is caused by the relatively low transmittance of the covering. Therefore, a relatively high ratio R means that the transmittance of the covering is relatively high in the entire target area. On the other hand, a relatively low ratio R means that the transmittance of the covering is relatively low in the entire target area.

Alternatively, the evaluation unit 15 divides the target region into multiple small regions, and calculates, for each small region, the proportion Rs of pixels whose difference between the pixel value and the pixel reference value is equal to or less than a given threshold value Th. The evaluation unit 15 then determines at least one of the average value Av and the variance Vr of the multiple proportions Rs obtained for the multiple small regions. The evaluation unit 15 may use at least one of the average value Av and the variance Vr as is as the evaluation result for the transparency. Alternatively, the evaluation unit 15 may compare the average value Av and the variance Vr with given evaluation reference values Eb and Ec, respectively, to evaluate the transparency. The specific values of the evaluation reference values Eb and Ec are not limited, and may be set based on any policy.

For example, the evaluation unit 15 may evaluate the transmittance as good if the average value Av is less than the evaluation reference value Eb and the variance Vr is less than the evaluation reference value Ec, and may evaluate the transmittance as poor otherwise. A relatively large average value Av regardless of the variance Vr means that the appearance of the target area has changed overall due to the application of the covering. That is, in this case, it can be said that the transmittance of the covering is low overall. Also, a relatively large variance Vr regardless of the average value Av means that there is a small area in which the appearance of the target area has changed due to the application of the covering. That is, it can be said that the transmittance of the covering is relatively low in a part of the target area. On the other hand, a relatively small average value Av and a relatively small variance Vr mean that the appearance of the target area is the same or similar overall before and after the covering is applied. That is, in this case, it can be said that the transmittance of the covering is relatively high throughout the entire target area.

Figure 6 is a diagram showing an example of evaluating transparency based on the difference between a pixel value and a pixel reference value. In this example, the target area 204 shown in Figure 4 is represented by 30 pixels. Assume that the pixel value of each pixel in the target area 204 is represented by two values, black and white. In response to the acquisition of such pixel values, it is assumed that each reference pixel value is all black, and in Figure 6, a set of the pixel reference values is represented as the reference area 221. Therefore, for a certain pixel in the target area 204, if the pixel value is black, the difference between the pixel value and the pixel reference value is 0, and if the pixel value is white, the difference is greater than 0. Assume that the threshold value Th is 0. As an example, it is assumed that data 231 is obtained as a set of pixel values obtained from the target area 204. This data 231 shows 21 black pixels and 9 white pixels, so the ratio R of pixels whose difference is equal to or less than the threshold value Th (= 0) is 0.7 (70%). As another example, it is assumed that data 232 is obtained from the target area 204. This data 232 shows 15 black pixels and 15 white pixels, so R = 15/30 = 0.5 (50%).

Figure 7 is a diagram showing another example of evaluating transparency based on the difference between a pixel value and a pixel reference value. In this example, the target area 213 shown in Figure 5 is represented by 40 pixels. Assume that the pixel value of each pixel in the target area 213 is represented by two values, black and white. In response to the acquisition of such pixel values, it is assumed that each reference pixel value is all black, and in Figure 7, a set of the pixel reference values is represented as the reference area 241. Therefore, for a certain pixel in the target area 213, if the pixel value is black, the difference between the pixel value and the pixel reference value is 0, and if the pixel value is white, the difference is greater than 0. Assume that the threshold value Th is 0. As an example, it is assumed that data 251 is obtained as a set of pixel values obtained from the target area 213. This data 251 indicates 32 black pixels and 8 white pixels, so the ratio R of pixels whose difference is equal to or less than the threshold value Th (= 0) is 0.8 (80%). As another example, it is assumed that data B252 is obtained from the target area 213. This data 252 shows 12 black pixels and 28 white pixels, so R = 12/40 = 0.3 (30%). As yet another example, assume that data 253 was obtained from target region 213. This data 253 shows 8 black pixels and 32 white pixels, so R = 8/40 = 0.2 (20%).

In the examples of Figures 6 and 7, if the evaluation reference value Ea is 0.3 (30%), the evaluation unit 15 evaluates the transmittance to be good in the cases of data 231, 232, 251, and 252, and evaluates the transmittance to be poor when data 253 is obtained.

Figure 8 is a diagram showing yet another example of evaluating the transparency based on the difference between the pixel value and the pixel reference value. In this example, the pixel value of each pixel in the target region 212 shown in Figure 5 is represented by two values, black and white. Also, the pixel reference value of each pixel in the reference region 261 corresponding to the target region 212 is represented by two values, black and white. In Figure 8, each pixel is represented by a small dot. In this example, in order to evaluate the transparency, the evaluation unit 15 divides the target region 212 into 15 small regions 212a, and divides the reference region 261 into 15 small regions 261a corresponding to the small regions 212a. For a certain pixel in the target region 212, if the pixel value is the same as the pixel reference value, the difference is 0, and if the pixel value is different from the pixel reference value, the difference is greater than 0. The threshold value Th is 0. As an example, it is assumed that data 271 is obtained as a set of pixel values obtained from the target region 212. In this case, the evaluation unit 15 may determine that the average value Av of the multiple ratios Rs corresponding to each small region 212a is less than the evaluation reference value Eb and that the variance Vr of the multiple ratios Rs is less than the evaluation reference value Ec, and evaluate the transparency as good. As another example, assume that data 272 is obtained from the target region 212. In this case, the evaluation unit 15 may determine that the average value Av is equal to or greater than the evaluation reference value Eb, and evaluate the transparency as poor. Alternatively, the evaluation unit 15 may determine that the variance Vr is equal to or greater than the evaluation reference value Ec, and evaluate the transparency as poor.

Returning to FIG. 3, in step S17, the evaluation unit 15 outputs the evaluation result. There are no limitations on the method of outputting the evaluation result. For example, the evaluation unit 15 may display the evaluation result on a monitor, may store it in a specified database, or may transmit it to another computer system. Alternatively, the evaluation system 1 may use the evaluation result to perform further processing. There are no limitations on the method of expressing the evaluation result. For example, the evaluation unit 15 may output an evaluation result that indicates the transparency as a numerical value, or may output an evaluation result that indicates whether the transparency is good or bad.

As described above, multiple target regions may be set in step S12. In this case, the processes of steps S13 to S17 may be performed for each of the multiple target regions, and the transmittance of the covering body may be evaluated in each target region. Alternatively, in step S16, a single transmittance of the covering body as a whole may be evaluated based on the respective proportions R of the multiple target regions.

Figure 9 is a diagram showing an example of evaluating the transparency using multiple target regions. In this example, in step S12, the pixel value acquisition unit 12 sets rectangular target regions 301-305 in the captured image 300. The target regions 301-305 have the same length but different widths. For example, the widths of the target regions 301-305 may be set taking into account the typical width of cracks that may occur on a concrete surface.

In step S13, the pixel value acquisition unit 12 acquires the individual pixel values within each of the target regions 301 to 305. In this example, the pixel value acquisition unit 12 acquires the individual pixel values as binary pixel values (0 (black) or 255 (white)).

In step S14, the reference setting unit 13 sets reference areas 311 to 315 corresponding to the target areas 301 to 305. Reference areas 311, 312, 313, 314, and 315 correspond to the target areas 301, 302, 303, 304, and 305, respectively. In the example of FIG. 9, the reference setting unit 13 sets the individual pixel values of the reference areas 311 to 315 to 0 (black).

In step S15, the calculation unit 14 calculates the difference between the pixel value and the pixel reference value for each target region. The calculation unit 14 performs this calculation between the target region 301 and the reference region 311, between the target region 302 and the reference region 312, between the target region 303 and the reference region 313, between the target region 304 and the reference region 314, and between the target region 305 and the reference region 315.

In step S16, the evaluation unit 15 evaluates the transmittance of the covering body based on the calculated differences. The evaluation unit 15 calculates the ratio R for each of the target regions 301-305, and determines whether each ratio R is equal to or greater than the evaluation reference value Ea. In one example, the evaluation unit 15 may evaluate the transmittance based on a combination of the ratio R and the width of the target region. For example, if the ratio R is less than the evaluation reference value Ea for a target region less than 0.5 mm wide and the ratio R is equal to or greater than the evaluation reference value Ea for a target region 0.5 mm wide or greater, the evaluation unit 15 may evaluate the transmittance as "a transmittance sufficient to detect a pattern 0.5 mm wide or greater."

Figure 10 shows another example of evaluating transparency using multiple target regions. In this example, in step S12, the pixel value acquisition unit 12 sets target regions 321 to 325 of the same shape and size within the captured image 320.

In step S13, the pixel value acquisition unit 12 acquires the individual pixel values within each of the target regions 321 to 325. In this example, the pixel value acquisition unit 12 acquires the individual pixel values as grayscale pixel values.

In step S14, the reference setting unit 13 sets reference areas 331 to 335 corresponding to the target areas 321 to 325. Reference areas 331, 332, 333, 334, and 335 correspond to target areas 321, 322, 323, 324, and 325, respectively. In the example of FIG. 10, the reference setting unit 13 sets the individual pixel values of the reference areas 331 to 335 to 0 (black).

In step S15, the calculation unit 14 calculates the difference between the pixel value and the pixel reference value for each target region. The calculation unit 14 performs this calculation between the target region 321 and the reference region 331, between the target region 322 and the reference region 332, between the target region 323 and the reference region 333, between the target region 324 and the reference region 334, and between the target region 325 and the reference region 335.

In step S16, the evaluation unit 15 evaluates the transmittance of the covering body based on the calculated differences. The evaluation unit 15 calculates the ratio R for each of the target regions 321-325, and determines whether each ratio R is equal to or greater than the evaluation reference value Ea. In one example, the evaluation unit 15 may evaluate the transmittance based on a combination of the ratio R and the brightness. For example, the evaluation unit 15 may evaluate the "transmittance to a degree that allows detection of the brightness or contrast corresponding to the target regions 323-325."

[effect]
As described above, an evaluation system according to one aspect of the present disclosure includes an image acquisition unit that acquires a captured image of a concrete surface to which a light-transmitting covering body has been applied, a pixel value acquisition unit that sets a target area within the captured image and acquires pixel values corresponding to each of a plurality of pixels that make up the target area, a reference setting unit that sets a pixel reference value for each of the plurality of pixels, a calculation unit that calculates the difference between the pixel value and the pixel reference value for each of the plurality of pixels, and an evaluation unit that evaluates the transmittance of the covering body on the concrete surface based on the difference between each of the plurality of pixels.

An evaluation method according to one aspect of the present disclosure is executed by an evaluation system including at least one processor. This evaluation method includes the steps of acquiring a photographed image of a concrete surface to which a light-transmitting covering has been applied, setting a target area within the photographed image and acquiring pixel values corresponding to each of a plurality of pixels constituting the target area, setting pixel reference values for each of the plurality of pixels, calculating the difference between the pixel value and the pixel reference value for each of the plurality of pixels, and evaluating the transparency of the covering on the concrete surface based on the difference between each of the plurality of pixels.

An evaluation program according to one aspect of the present disclosure causes a computer to execute the steps of acquiring a photographed image of a concrete surface to which a light-transmitting covering has been applied, setting a target area within the photographed image and acquiring pixel values corresponding to each of a plurality of pixels constituting the target area, setting pixel reference values for each of the plurality of pixels, calculating the difference between the pixel value and the pixel reference value for each of the plurality of pixels, and evaluating the transparency of the covering on the concrete surface based on the difference between each of the plurality of pixels.

In this aspect, the difference between the pixel value and the pixel reference value is calculated for each pixel in a target area set in the captured image, and the transparency of the covering body on the concrete surface is evaluated based on this difference. By considering the pixel value difference for each of multiple pixels, the covering body can be appropriately evaluated. For example, by considering multiple differences corresponding to multiple pixels, the transparency can be evaluated all at once in a two-dimensional area rather than at a specific point.

In the evaluation system according to another aspect, the evaluation unit may evaluate the transmittance based on the proportion of pixels among the plurality of pixels whose difference is equal to or less than a given threshold value. By taking such a proportion into consideration, the transmittance of the covering body can be quantitatively evaluated.

In the evaluation system according to another aspect, the evaluation unit may evaluate the transparency based on whether the ratio is equal to or greater than a given evaluation standard value. The higher the ratio, the higher the transparency in the target area. By comparing the ratio with the evaluation standard value, the evaluation result regarding the transparency can be shown in an easy-to-understand manner.

In an evaluation system according to another aspect, the evaluation unit may divide the target area into a plurality of small areas, calculate a ratio for each of the plurality of small areas, and evaluate the transmittance based on at least one of the average value and the variance of the plurality of ratios corresponding to the plurality of small areas. By adopting the average value and the variance of the plurality of ratios corresponding to the plurality of small areas constituting the target area, the transmittance can be evaluated taking into account the distribution or variation of the transmittance in the target area.

In the evaluation system according to another aspect, the evaluation unit may evaluate the transmittance as good if the mean value is less than a given first evaluation reference value and the variance is less than a given second evaluation reference value, and may evaluate the transmittance as poor otherwise. By comparing both the mean value and the variance with the reference values, the evaluation result regarding the transmittance can be shown in an easy-to-understand manner.

In the evaluation system according to another aspect, the reference setting unit may acquire a reference image showing the concrete surface before the covering is applied, set a reference area in the reference image showing the same part as the target area, and set a pixel reference value for each of the multiple pixels that make up the reference area. By using such a reference image, the change in the appearance of the concrete surface that actually occurs before and after the covering is applied can be obtained as the difference between the pixel value and the pixel reference value. Therefore, the transmittance of the covering can be evaluated more accurately.

In the evaluation system according to another aspect, the pixel value acquisition unit may convert each of the original pixel values of the multiple pixels to one of a first pixel value and a second pixel value based on the boundary value, and the reference setting unit may set each of the pixel reference values of the multiple pixels to one of the first pixel value and the second pixel value. By binarizing the pixel value and the pixel reference value, the difference between the pixel value and the pixel reference value is simplified. Therefore, the transmittance of the covering body can be evaluated by simpler calculations and determinations.

[Modification]
The present disclosure has been described in detail above based on the embodiments. However, the present disclosure is not limited to the above embodiments. The present disclosure can be modified in various ways without departing from the spirit and scope of the present disclosure.

When comparing the magnitude of two numbers within a computer, either of the two criteria "greater than or equal to" and "greater than" may be used, or either of the two criteria "less than or equal to" and "less than". The choice of criteria does not change the technical significance of the process of comparing the magnitude of two numbers.

In this disclosure, the expression "at least one processor executes a first process, executes a second process, ... executes an nth process" or a corresponding expression is a concept that includes cases where the entity executing the n processes from the first process to the nth process (i.e., the processor) changes midway. In other words, this expression is a concept that includes both cases where all n processes are executed by the same processor and cases where the processor changes among the n processes according to an arbitrary policy.

The processing procedure of the method executed by at least one processor is not limited to the example in the above embodiment. For example, some of the steps (processing) described above may be omitted, or each step may be executed in a different order. In addition, any two or more of the steps described above may be combined, or some of the steps may be modified or deleted. Alternatively, other steps may be executed in addition to each of the steps described above.

1...Evaluation system, 11...Image acquisition unit, 12...Pixel value acquisition unit, 13...Standard setting unit, 14...Calculation unit, 15...Evaluation unit, 100...Computer, 101...Processor, 102...Main memory unit, 103...Auxiliary memory unit, 104...Communication control unit, 105...Input device, 106...Output device, 110...Evaluation program, 200...Captured image, 201-204...Target area, 210...Captured image, 211-213...Target area , 212a...small area, 221...reference area, 231, 232...data, 241...reference area, 251-253...data, 261...reference area, 261a...small area, 271, 272...data, 300...captured image, 301-305...target area, 311-315...reference area, 320...captured image, 321-325...target area, 331-335...reference area, S1...processing flow, S11-S17...steps.

Claims (9)

an image acquisition unit for acquiring an image of a concrete surface to which a light-transmitting covering body is applied;
a pixel value acquisition unit that sets a target area within the captured image and acquires pixel values corresponding to each of a plurality of pixels that constitute the target area;
a reference setting unit that sets pixel reference values for each of the plurality of pixels;
a calculation unit that calculates a difference between the pixel value and the pixel reference value for each of the plurality of pixels;
an evaluation unit for evaluating a transparency of the covering body on the concrete surface based on the difference between each of the plurality of pixels;
An evaluation system comprising: the evaluation unit evaluates the transparency based on a ratio of pixels among the plurality of pixels, the difference of which is equal to or smaller than a given threshold value;
The evaluation system according to claim 1 . the evaluation unit evaluates the transmittance based on whether the ratio is equal to or greater than a given evaluation reference value.
The evaluation system according to claim 2 . The evaluation unit,
Dividing the region of interest into a plurality of subregions;
Calculating the ratio for each of the plurality of small regions;
evaluating the transmittance based on at least one of an average value and a variance of a plurality of the ratios corresponding to the plurality of small regions;
The evaluation system according to claim 2 . the evaluation unit evaluates the transmittance as good if the average value is less than a given first evaluation reference value and the variance is less than a given second evaluation reference value, and evaluates the transmittance as poor in other cases.
The evaluation system according to claim 4. The reference setting unit,
obtaining a baseline image of the concrete surface before the coating is applied;
A reference area that captures the same part as the target area is set in the reference image;
setting the pixel reference value for each of the plurality of pixels constituting the reference region;
The evaluation system according to any one of claims 1 to 5. the pixel value acquisition unit converts each of the original pixel values of the plurality of pixels into one of a first pixel value and a second pixel value based on a boundary value;
the reference setting unit sets each of the pixel reference values of the plurality of pixels to either the first pixel value or the second pixel value;
The evaluation system according to any one of claims 1 to 6. 1. A method of assessment performed by an assessment system having at least one processor, comprising:
Obtaining an image of a concrete surface to which a light-transmitting coating has been applied;
A step of setting a target area within the captured image and acquiring pixel values corresponding to each of a plurality of pixels constituting the target area;
setting a pixel reference value for each of the plurality of pixels;
calculating a difference between the pixel value and the pixel reference value for each of the plurality of pixels;
assessing a transparency of the coating on the concrete surface based on the difference of each of the plurality of pixels;
Evaluation methods including. Obtaining an image of a concrete surface to which a light-transmitting coating has been applied;
A step of setting a target area within the captured image and acquiring pixel values corresponding to each of a plurality of pixels constituting the target area;
setting a pixel reference value for each of the plurality of pixels;
calculating a difference between the pixel value and the pixel reference value for each of the plurality of pixels;
assessing a transparency of the coating on the concrete surface based on the difference of each of the plurality of pixels;
An evaluation program that causes a computer to execute the above.

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