Inspection support device and inspection support method

Abstract

To efficiently inspect loose irregularities and local gloss unevenness generated on an object surface by using an image obtained by imaging an object.SOLUTION: An inspection support device 10 calculates the brightness gradient of each pixel forming an evaluation object image when generating an inspection image in which a defect generated on the surface of an evaluation object is emphasized on the basis of the evaluation object image obtained by imaging the evaluation object by an imaging unit 20, calculates the brightness gradient angle of each pixel forming the evaluation object image on the basis of the calculated brightness gradient, stores color scheme information associated with color information for each brightness gradient angle, and generates the inspection image in which the color information is applied to each pixel forming the evaluation object image on the basis of the brightness gradient angle of each pixel forming the evaluation object image and the stored color scheme information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an inspection support device and an inspection support method that can efficiently detect gradual irregularities and local gloss unevenness occurring on the surface of an object using an image of the object. [Background technology]

[0002] Conventionally, because various scratches and dents occur on objects such as vehicles, techniques for inspecting the surface of an object using an image of the object have been known. For example, Patent Document 1 discloses a technique in which the brightness of each pixel forming an image of the object is binarized using a predetermined threshold value, pixels with a brightness below this threshold value are determined to be pixels where irregular defects appear, and the amount of change in brightness of each pixel is calculated, the calculated amount of change in brightness of each pixel is binarized using another predetermined threshold value, and pixels with a brightness change above this threshold value are determined to be pixels where irregular defects appear. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 9-304292 Summary of the Invention [Problem to be solved by the invention]

[0004] However, even if the brightness of each pixel forming an image is binarized using a predetermined threshold value as in Patent Document 1, if the brightness between adjacent pixels changes gradually, it is difficult to set an appropriate threshold value because the brightness difference between pixels is small. Similarly, when calculating the amount of change in brightness of each pixel, if the brightness difference between pixels is small, only a small amount of change is obtained, making it difficult to set an appropriate threshold value.

[0005] As a result, it is difficult to detect defects that involve gradual changes in brightness, such as unevenness on the painted surface of an object or localized unevenness in gloss. Therefore, how to efficiently detect gradual unevenness and localized unevenness in gloss on the surface of an object using captured images has become an important issue.

[0006] The present invention has been made to solve the problems (issues) associated with the above-mentioned conventional technology, and aims to provide an inspection support device and an inspection support method that can efficiently detect gradual irregularities and local gloss unevenness that occur on the surface of an object using an image of the object. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the object, the present invention provides an inspection support device that generates an inspection image that emphasizes defects that occur on the surface of an object to be evaluated, based on an image of the object to be evaluated captured by an imaging unit, and is characterized by comprising: a brightness gradient calculation means that calculates the brightness gradient of each pixel that forms the image to be evaluated; a brightness gradient angle calculation means that calculates the brightness gradient angle of each pixel that forms the image to be evaluated, based on the brightness gradient calculated by the brightness gradient calculation means; a storage means that stores color information that corresponds to color information for each brightness gradient angle; and an inspection image generation means that generates an inspection image in which color information is assigned to each pixel that forms all or a part of the image to be evaluated, based on the brightness gradient angle of each pixel that forms the image to be evaluated calculated by the brightness gradient angle calculation means and the color information stored in the storage means.

[0008] Furthermore, in the above invention, the present invention is characterized in that, when a coordinate system of the image to be evaluated consists of an X axis and a Y axis, the brightness gradient calculation means calculates a brightness gradient in the X direction and a brightness gradient in the Y direction of each pixel forming the image to be evaluated, and the brightness gradient angle calculation means calculates, as a brightness gradient angle, an arctangent function of the ratio of the brightness gradient in the axial direction to the brightness gradient in the Y direction.

[0009] Furthermore, in the above invention, the present invention is characterized in that the brightness gradient calculation means calculates the brightness gradient of each pixel forming the image to be evaluated by applying a predetermined differential filter to the image to be evaluated.

[0010] Further, in the above-mentioned invention, the present invention is characterized in that the brightness gradient angle of each pixel forming the evaluation target image calculated by the brightness gradient angle calculation means is , given The apparatus further includes a defective area identification means for identifying a defective area of ​​the object to be evaluated based on a reference brightness gradient angle of each pixel forming a reference image, and the inspection image generation means generates an inspection image in which color information is assigned to each pixel forming the defective area based on the brightness gradient angle of each pixel forming the defective area identified by the defective area identification means and the color scheme information stored in the storage means.

[0011] Furthermore, in the above invention, the present invention is characterized in that the inspection image generating means determines that a pixel forms the defective area when the difference between the brightness gradient angle of each pixel forming the image to be evaluated and the reference brightness gradient angle of the reference image corresponding to each pixel is equal to or greater than a predetermined threshold value.

[0012] The present invention also provides an inspection support method for an inspection support device that generates an inspection image emphasizing defects occurring on the surface of an evaluation object based on an evaluation object image captured by an imaging unit, the inspection support method including: a brightness gradient calculation step in which the inspection support device calculates a brightness gradient of each pixel forming the evaluation object image; a brightness gradient angle calculation step in which the inspection support device calculates a brightness gradient angle of each pixel forming the evaluation object image based on the brightness gradient calculated in the brightness gradient calculation step; a storage step in which the inspection support device stores color information in a storage unit, the color information correlating each brightness gradient angle; and a storage step in which the inspection support device stores the brightness gradient angle of each pixel forming the evaluation object image calculated in the brightness gradient angle calculation step and the brightness gradient angle of each pixel forming the evaluation object image calculated in the brightness gradient angle calculation step. Department and a test image generating step of generating a test image in which color information is assigned to each pixel forming all or part of the image to be evaluated, based on the color scheme information stored in the test image generating step. [Effects of the Invention]

[0013] According to the present invention, it is possible to efficiently detect gradual irregularities and local gloss unevenness occurring on the surface of an object using an image of the object. [Brief explanation of the drawings]

[0014] [Figure 1] FIG. 1 is a functional block diagram showing the configuration of the examination support device according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the conversion data illustrated in FIG. [Figure 3] FIG. 3 is a flowchart showing a processing procedure of the inspection support device shown in FIG. [Figure 4] FIG. 4 is a flowchart showing the procedure for generating the test image shown in FIG. [Figure 5] FIG. 5 is a diagram showing an example of an evaluation object image and an inspection image of the inspection support device shown in FIG. [Figure 6] FIG. 6 is a functional block diagram showing the configuration of the examination support device according to the second embodiment. [Figure 7] FIG. 7 is a flowchart showing the processing procedure of the inspection support device shown in FIG. [Figure 8] FIG. 8 is a flowchart showing the procedure for generating the gradient map shown in FIG. [Figure 9] FIG. 9 is a diagram showing an example of an inspection image including a defective area. DETAILED DESCRIPTION OF THE INVENTION

[0015] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of an inspection support device and an inspection support method according to the present invention will be described in detail below with reference to the accompanying drawings.

[0016] [Embodiment 1] <Configuration of the examination support device> First, a description will be given of the configuration of an inspection support device according to the present embodiment 1. In the present embodiment 1, a case will be described in which an inspection image is generated to which color information according to the brightness gradient angle of each pixel forming an image to be evaluated (hereinafter referred to as "image to be evaluated").

[0017] Fig. 1 is a functional block diagram showing the configuration of an examination support device according to embodiment 1. As shown in Fig. 1, the examination support device 10 includes a display unit 11, an input unit 12, a storage unit 14, a control unit 15, and an imaging unit 20. The display unit 11 is a display interface such as a liquid crystal display that displays various types of information. The input unit 12 is an input interface such as a mouse or keyboard.

[0018] The storage unit 14 is a storage device such as a hard disk drive or nonvolatile memory, and stores the conversion data 14a. The conversion data 14a is data that associates a brightness gradient angle with color information (RGB code).

[0019] The control unit 15 is a control unit that controls the entire inspection support device 10, and has an image acquisition processing unit 16, a grayscale image generation unit 17, an inspection image generation processing unit 18, and a display processing unit 19. In practice, by loading these programs into the CPU and executing them, the image acquisition processing unit 16, the grayscale image generation unit 17, the inspection image generation processing unit 18, and the display processing unit 19 will execute their respective corresponding processes.

[0020] The image acquisition processing unit 16 is a processing unit that controls the imaging unit 20 to capture an image of the surface S of the evaluation object 100, and acquires the captured image of the surface S of the evaluation object 100. The evaluation object 100 is, for example, the body of a car.

[0021] The grayscale image generating unit 17 is a processing unit that converts the color image acquired by the image acquisition processing unit 16 into a grayscale image (black and white grayscale image). To convert an RGB color image into grayscale, for example, the value obtained by multiplying the R image by a predetermined coefficient r, the value obtained by multiplying the G image by a predetermined coefficient g, and the value obtained by multiplying the B image by a predetermined coefficient b may be added together (rR+gG+bB). Alternatively, the RGB color system may be converted into the Lab color system and lightness L may be used. Various other well-known conversion methods may also be used.

[0022] The test image generation processing unit 18 has a brightness gradient calculation unit 18a, a brightness gradient angle calculation unit 18b, and a test image generation unit 18c. The brightness gradient calculation unit 18a calculates the brightness gradient of each pixel of the grayscale image generated by the grayscale image generation unit 17 by applying a differential operator. As this differential operator, a first-order differential operator such as Sobel or Roberts, or a second-order differential operator can be used. For example, if a Sobel differential operator in the X direction is applied to calculate the brightness gradient V in the X direction, X , and then apply the Sobel differential operator in the Y direction to generate the brightness gradient V in the Y direction. Y Generate.

[0023] The brightness gradient angle calculation unit 18b calculates the brightness gradient V in the X direction. X and the brightness gradient in the Y direction V Y The ratio of the calculated brightness gradients was calculated, and the arctangent function (tan -1 (V X / V Y )) to calculate the brightness gradient angle.

[0024] The test image generation unit 18c is a processing unit that generates a color image (test image) by referring to the conversion data 14a stored in the memory unit 14 and associating a color scheme with the brightness gradient angle of each pixel calculated by the brightness gradient angle calculation unit 18b.

[0025] The display processing unit 19 is a processing unit that displays the test image generated by the test image generation processing unit 18 on the display unit 11. The display processing unit 19 may overlay and display the test image on the grayscale image generated by the grayscale image generation unit 17.

[0026] <Conversion data> Next, an example of the conversion data 14a shown in Fig. 1 will be described. Fig. 2 is a diagram showing an example of the conversion data 14a shown in Fig. 1. As shown in Fig. 2, the brightness gradient angle is associated with an RGB color code.

[0027] Here, a brightness gradient angle of 0 degrees corresponds to R "255", G "0", and B "127", a brightness gradient angle of 30 degrees corresponds to R "255", G "0", and B "255", a brightness gradient angle of 60 degrees corresponds to R "127", G "0", and B "255", a brightness gradient angle of 90 degrees corresponds to R "0", G "0", and B "255", a brightness gradient angle of 120 degrees corresponds to R "0", G "127", and B "255", and a brightness gradient angle of 150 degrees corresponds to R "0", G "255", and B "255".

[0028] <Processing procedure of the examination support device> Next, a description will be given of the processing procedure of the inspection support device 10 shown in Fig. 1. Fig. 3 is a flowchart showing the processing procedure of the inspection support device 10 shown in Fig. 1. As shown in Fig. 3, the inspection support device 10 first acquires an evaluation target image of the surface S of the evaluation target object 100 captured by the imaging unit 20 (step S101).

[0029] Then, the inspection support device 10 performs a noise removal process on the evaluation target image as pre-processing (step S102). For this noise removal process, for example, a known smoothing filter, median filter, or the like may be applied.

[0030] Then, the noise-removed image to be evaluated is converted into a monochrome image (grayscale image) (step S103). To convert an RGB color image into grayscale, for example, the R image is multiplied by a predetermined coefficient r, the G image is multiplied by a predetermined coefficient g, and the B image is multiplied by a predetermined coefficient b, and the result is calculated as (rR+gG+bB).

[0031] Thereafter, a test image generation process is performed to generate a test image from the grayscale image (step S104), and the generated test image is displayed on the display unit 11.

[0032] <Inspection image generation process procedure> Next, the test image generation process shown in Fig. 3 will be described. Fig. 4 is a flowchart showing the processing procedure of the test image generation process shown in Fig. 3. As shown in Fig. 4, the test support device 10 selects any pixel that forms the generated grayscale image (step S201).

[0033] Then, the inspection support device 10 calculates the brightness gradient V in the X direction of the selected pixel. X (step S202), and calculate the brightness gradient V Y (Step S203). Then, the inspection support device 10 calculates the brightness gradient V in the X direction. X and the brightness gradient in the Y direction V Y Ratio of (V X / V Y ) and calculate the arctangent function tan -1 (V X / V Y ) is calculated as the brightness gradient angle (step S204).

[0034] Then, the inspection support device 10 converts the brightness gradient angle into color information based on the conversion data 14a and sets it as the pixel value of the corresponding pixel in the inspection image (step S205). If there are unprocessed pixels (step S206: No), the next pixel is selected (step S207) and the process proceeds to step S202. On the other hand, if all pixels have been processed (step S206: Yes), the process proceeds to step S105 in FIG. 3.

[0035] <Examples of evaluation target images and inspection images> Next, an example of an evaluation object image and an inspection image of the inspection support device 10 shown in Fig. 1 will be described. Fig. 5 is a diagram showing an example of an evaluation object image and an inspection image of the inspection support device 10 shown in Fig. 1. As shown in Fig. 5(a), the evaluation object image captured by the imaging unit 20 is an image in which it is difficult to visually recognize unevenness or local gloss unevenness on the painted surface of the evaluation object 100.

[0036] In contrast, if the evaluation image of Fig. 5(a) is processed by the inspection support device 10, as shown in Fig. 5(b), conversion is performed based on the brightness gradient angle at each pixel, resulting in an inspection image in which the color of the area where the brightness gradient angle changes changes. Furthermore, the color change is particularly noticeable at defect areas P1 and P2, where the brightness gradient angle changes discontinuously.

[0037] As described above, in this embodiment 1, when generating an inspection image that emphasizes defects on the surface of an object to be evaluated based on an image of the object to be evaluated captured by the imaging unit 20, the inspection support device 10 calculates the brightness gradient of each pixel that forms the image to be evaluated, calculates the brightness gradient angle of each pixel that forms the image to be evaluated based on the calculated brightness gradient, stores color information that associates color information with each brightness gradient angle, and generates an inspection image in which color information is assigned to each pixel that forms the image to be evaluated based on the brightness gradient angle of each pixel that forms the image to be evaluated and the stored color information.As a result, it is possible to efficiently detect gradual irregularities and localized gloss unevenness on the surface of the object to be evaluated.

[0038] [Embodiment 2] In the first embodiment, the brightness gradient angles of all pixels forming the image to be evaluated are converted into RGB codes. In the second embodiment, however, a test image is generated by identifying a defective area of ​​the object to be evaluated and coloring the pixels forming the identified defective area according to the brightness gradient angles. Note that the same components as those in the first embodiment are designated by the same reference numerals, and detailed descriptions thereof will be omitted.

[0039] <Configuration of the inspection support device 30> Next, a description will be given of the configuration of the test support device 30 according to the present embodiment 2. Fig. 6 is a functional block diagram showing the configuration of the test support device 30 according to the present embodiment 2. As shown in Fig. 6, the test support device 30 has a display unit 11, an input unit 12, a storage unit 34, a control unit 35, and an imaging unit 20.

[0040] The storage unit 34 is a storage device such as a hard disk drive or nonvolatile memory, and stores the conversion data 14a and the reference gradient angle map 34a. The reference gradient angle map 34a is data obtained by calculating the brightness gradient angle from the brightness gradient of each pixel forming a reference image obtained by capturing an image of the evaluation object 100 without defects.

[0041] The control unit 35 is a control unit that controls the entire inspection support device 10, and includes the image acquisition processing unit 16, the grayscale image generation unit 17, the inspection image generation processing unit 36, and the display processing unit 19. In practice, by loading these programs into the CPU and executing them, the image acquisition processing unit 16, the grayscale image generation unit 17, the inspection image generation processing unit 36, and the display processing unit 19 will execute their respective corresponding processes.

[0042] The inspection image generation processing unit 36 ​​includes a brightness gradient calculation unit 18a, a brightness gradient angle calculation unit 18b, a defective area identification processing unit 36a, and an inspection image generation unit 18c. The defective area identification processing unit 36a compares a reference gradient angle map 34a created in advance with the brightness gradient angle data of the evaluation object 100 calculated by the brightness gradient angle calculation unit 18b, and performs processing to identify the area, including its surroundings, as a defective area if the difference between the reference gradient angle map 34a and the calculated brightness gradient angle is equal to or greater than a threshold value.

[0043] <Processing Procedure of the Inspection Support Device 30> Next, a description will be given of the processing procedure of the inspection support device 30 shown in Fig. 6. Fig. 7 is a flowchart showing the processing procedure of the inspection support device 30 shown in Fig. 6. As shown in Fig. 7, the inspection support device 30 first acquires an evaluation target image of the surface S of the evaluation target 100 captured by the imaging unit 20 (step S301).

[0044] Thereafter, the inspection support device 30 performs pre-processing to remove noise from the evaluation target image (step S302). For this noise removal process, for example, a known smoothing filter, median filter, or the like may be applied.

[0045] Then, the noise-removed image to be evaluated is converted into a monochrome image (grayscale image) (step S303). To convert an RGB color image into grayscale, for example, the R image is multiplied by a predetermined coefficient r, the G image is multiplied by a predetermined coefficient g, and the B image is multiplied by a predetermined coefficient b, and the result is calculated as (rR+gG+bB). A grayscale image is generated (step S303).

[0046] Then, the inspection support device 30 generates a gradient angle map based on the grayscale image (step S304). After that, the brightness gradient angle of the gradient angle map is compared with the brightness gradient angle of the reference gradient angle map 34a, and if the difference between the acquired brightness gradient angle and the brightness gradient angle of the reference gradient angle map 34a is equal to or greater than a predetermined threshold, the pixel is determined to be defective, and the area including the surrounding area is determined to be a defective area (step S305).

[0047] Then, the inspection support device 30 selects any pixel that forms the defective area (step S306), and converts the brightness gradient angle of the selected pixel into color information based on the conversion data 14a (step S307). If an unprocessed pixel exists (step S308: No), the inspection support device 30 selects the next pixel (step S309), and proceeds to step S306.

[0048] In response to this, if the inspection support device 30 has finished processing all pixels that form the defective area (step S308: Yes), it displays the inspection image on the display unit 11 (step S310) and ends the processing.

[0049] <Procedure for generating gradient angle map> Next, a description will be given of the procedure for generating the gradient angle map shown in Fig. 7. Fig. 8 is a flowchart showing the procedure for generating the gradient map shown in Fig. 7. As shown in Fig. 8, the inspection support device 30 selects any pixel that forms a grayscale image (step S401).

[0050] Then, the inspection support device 30 calculates the brightness gradient V in the X direction of the selected pixel. X (step S402), and calculate the brightness gradient V Y (Step S403). Then, the inspection support device 30 calculates the brightness gradient V in the X direction. X and the brightness gradient in the Y direction V Y Ratio of (V X / V Y ) and calculate the arctangent function tan -1 (V X / V Y) is calculated as the brightness gradient angle (step S404).

[0051] If the selected pixel is not the last pixel (step S405: No), the inspection support device 30 selects the next pixel (step S406) and proceeds to step S402. If the processing of the last pixel is completed (step S405: Yes), the inspection support device 30 proceeds to step S305 in FIG.

[0052] Next, an example of an inspection image including a defective region will be described. Fig. 9 is a diagram showing an example of an inspection image including a defective region. As shown in Fig. 9, the inspection support device 30 creates a reference gradient angle map 34a in advance from a reference image of an evaluation object 100 having no defects on its surface.

[0053] Subsequently, the inspection support device 30 generates a gradient angle map of the inspection target image of the evaluation object 100 captured by the imaging unit 20. The inspection support device 30 then compares the reference gradient angle map 34a with the gradient angle map. In Figure 9, surface defects exist in surface defects P3 and P4, and the difference between the reference gradient angle map 34a and the gradient angle map exceeds the threshold value. Therefore, the area including surface defects P3 and P4 is determined to be a defective area, and color information is assigned only to the pixels in this area.

[0054] As described above, in the second embodiment, defective areas of the object to be evaluated are identified based on the brightness gradient angle of each pixel forming the image to be evaluated and the reference brightness gradient angle of each pixel forming the reference image, and an inspection image is generated in which color information is assigned to each pixel forming the defective area based on the brightness gradient angle and color information of each pixel forming the defective area. Therefore, the image to be evaluated can be used to efficiently inspect for gradual irregularities and local gloss unevenness that have occurred on the surface of the object.

[0055] The configurations illustrated in the above embodiments are merely functional schematics and are not necessarily physically configured as shown. In other words, the distribution and integration of each device is not limited to that illustrated, and all or part of the devices can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. [Industrial Applicability]

[0056] The inspection support device and inspection support method according to the present invention are suitable for efficiently inspecting gradual irregularities and localized gloss unevenness on the surface of an object using an image of the object. [Explanation of symbols]

[0057] 10 Inspection support equipment 11 Display section 12 Input section 14 Storage section 14a Conversion Data 15 Control Unit 16 Image acquisition processing section 17 Grayscale image generation unit 18 Inspection image generation processing unit 18a Lightness gradient calculation section 18b Lightness gradient angle calculation section 18c Inspection image generation unit 19 Display processing section 20 Imaging unit 30 Inspection support equipment 34 Storage section 34a Reference gradient angle map 35 Control Unit 36 Inspection image generation processing unit 36a Defective area identification processing section 100 Evaluation Objects P1, P2, P3, P4 Defect surface S surface

Claims

1. 1. An inspection support device that generates an inspection image that highlights defects occurring on a surface of an evaluation object based on an evaluation object image captured by an imaging unit of the evaluation object, a brightness gradient calculation means for calculating a brightness gradient of each pixel forming the evaluation target image; a brightness gradient angle calculation means for calculating a brightness gradient angle of each pixel forming the image to be evaluated based on the brightness gradient calculated by the brightness gradient calculation means; a storage means for storing color scheme information in which color information is associated with each brightness gradient angle; a test image generating means for generating a test image in which color information is added to each pixel forming the whole or part of the image to be evaluated, based on the brightness gradient angle of each pixel forming the image to be evaluated calculated by the brightness gradient angle calculating means and the color arrangement information stored in the storage means; and An inspection support device comprising:

2. The brightness gradient calculation means When the coordinate system of the image to be evaluated is made up of an X axis and a Y axis, a brightness gradient in the X direction and a brightness gradient in the Y direction of each pixel forming the image to be evaluated are calculated; The brightness gradient angle calculation means The arctangent function of the ratio of the brightness gradient in the X direction to the brightness gradient in the Y direction is calculated as the brightness gradient angle.

2. The inspection support device according to claim 1.

3. The brightness gradient calculation means 3. The inspection support device according to claim 1, wherein a brightness gradient of each pixel forming the evaluation target image is calculated by applying a predetermined differential filter to the evaluation target image.

4. a defect area specifying means for specifying a defect area of ​​the object to be evaluated based on the brightness gradient angle of each pixel forming the image to be evaluated calculated by the brightness gradient angle calculating means and the reference brightness gradient angle of each pixel forming a predetermined reference image, The inspection image generating means A test image is generated in which color information is assigned to each pixel forming the defective area based on the brightness gradient angle of each pixel forming the defective area identified by the defective area identifying means and the color information stored in the storage means.

4. The inspection support device according to claim 1, wherein:

5. The inspection image generating means 5. The inspection support device according to claim 4, wherein a pixel is determined to be a pixel forming the defective area when a difference between a brightness gradient angle of the pixel forming the image to be evaluated and a reference brightness gradient angle of the reference image corresponding to the pixel is equal to or greater than a predetermined threshold value.

6. 1. An inspection support method for an inspection support device that generates an inspection image that highlights defects occurring on a surface of an evaluation object based on an evaluation object image captured by an imaging unit of the evaluation object, comprising: a brightness gradient calculation step in which the inspection support device calculates a brightness gradient of each pixel forming the evaluation target image; a brightness gradient angle calculation step in which the inspection support device calculates a brightness gradient angle of each pixel forming the evaluation target image based on the brightness gradient calculated in the brightness gradient calculation step; a storage step in which the inspection support device stores color information in a storage unit, the color information being associated with each brightness gradient angle; an inspection image generating step in which the inspection support device generates an inspection image in which color information is added to each pixel forming all or a part of the evaluation target image, based on the brightness gradient angle of each pixel forming the evaluation target image calculated in the brightness gradient angle calculating step and the color scheme information stored in the storage unit; An inspection support method comprising:

Images