JP6745150B2 - Lighting device and image inspection device - Google Patents

Description

The present invention relates to a lighting device and an image inspection device.

For example, Patent Document 1 discloses an image inspection apparatus that irradiates a surface of an object to be inspected with a light-dark pattern in which bright parts and dark parts appear alternately.

Registered Utility Model No. 3197766

In the image inspection apparatus of Patent Document 1, when the inspection target has different types of defects for each of a plurality of inspection target regions, or when the inspection target has a plurality of faces facing different directions, Depending on whether or not there is a case, it may not be possible to perform suitable illumination.

An object of the present invention is to provide an illumination device and an image inspection device that can perform suitable illumination.

In order to achieve the above object, the lighting device according to the first aspect of the present invention is
Illumination for illuminating a first region of the inspection target of the image inspection with the first light-dark pattern and illuminating a second region different from the first region of the inspection target with a second light-dark pattern different from the first light-dark pattern. Means and
Movement control means for moving the first light-dark pattern and the second light-dark pattern relative to the inspection object;
Equipped with
The movement control means moves the first bright-dark pattern and the second bright-dark pattern at different speeds.

In order to achieve the above object, an image inspection apparatus according to a second aspect of the present invention is
The lighting device;
A camera that obtains a plurality of captured images by capturing a plurality of images of the inspection target illuminated by the illumination device,
An inspection unit that inspects the first area and the second area for defects based on the plurality of captured images obtained by the camera;
Equipped with.

According to the present invention, it is possible to preferably perform illumination.

It is a block diagram which shows the structure of the image inspection apparatus which concerns on one Embodiment of this invention. (A) is a front view of a display that displays a bright and dark pattern image. (B) is a front view of a display displaying a plain image. FIG. 13 is a diagram illustrating a configuration example of a computer. It is a figure which shows the mode of movement of the bright part and dark part of a light-dark pattern image. It is a flow chart of an example of image inspection processing. It is a figure explaining a mode when generating an inspection image. It is a figure explaining the comparison of the brightness value of each pixel of a 2nd reference image, and the brightness value of each pixel of a 2nd inspection image. It is a figure which shows another bright/dark pattern image. It is a conceptual diagram for demonstrating an example of the relationship between the light-and-dark pattern image displayed on a display, and the light-and-dark pattern reflected in the inspection target in a captured image. It is a conceptual diagram for demonstrating an example of the relationship between the light-and-dark pattern image displayed on a display, and the light-and-dark pattern reflected in the inspection target in a captured image.

(Structure of the image inspection device 100)
First, the configuration of an image inspection apparatus 100 according to an embodiment of the present invention will be described with reference to FIG. The image inspection device 100 is a device that inspects the appearance of the inspection target K placed on a predetermined table ST and detects a defect. The image inspection apparatus 100 includes a display 110, a camera 120, and a computer 130. The inspection target K is a resin packaging film, a car body, a car bumper, or the like. Defects include scratches, dust, and paint peeling.

The display 110 is a self-luminous type and displays an image to irradiate the inspection object K with the display light L1 representing the image. In this way, the inspection object K is illuminated by the display 110. The display 110 is preferably a liquid crystal display that emits light in a plane by a diffusion plate, an EL (Electro Luminescence) display that emits light in a plane, or the like. The display light L1 is reflected by the inspection object K. Hereinafter, the display light L1 reflected by the inspection object K will be referred to as reflected light L2. The display 110 has a screen that is long in the lateral direction (the direction in which the X axis (see FIG. 2) extends), similar to a general display. The Y-axis direction in FIG. 1 is the vertical direction of the display.

The display 110 displays the light-dark pattern image 11 (FIG. 2A) or the plain image 15 (FIG. 2B) as an image displayed when the inspection target K is illuminated.

The light-dark pattern image 11 includes a plurality of bright portions 11A and a plurality of dark portions 11B that are alternately arranged in the vertical direction. The plurality of bright portions 11A and the plurality of dark portions 11B form a light-dark pattern in which light and dark appear repeatedly (periodically). Each bright part 11A is a rectangular bright region that is long in the lateral direction (X-axis direction), and is, for example, a white region. Each dark portion 11B is a rectangular dark area that is long in the lateral direction (X-axis direction). Each dark portion 11B is darker (having a lower brightness value) than the bright portion 11A, and is, for example, a black region (a region that does not emit display light). At the time of illumination with the light-dark pattern image 11, the inspection target K shows the light-dark pattern shown by the light-dark pattern image 11.

The plain image 15 is, for example, a white image with uniform brightness. Therefore, when illuminated by the plain image 15, the inspection target K is illuminated brightly as a whole.

The camera 120 is, for example, a digital camera using a CCD (charge coupled device) and a CMOS (Complementary Metal Oxide Semiconductor). The camera 120 captures the inspection target K illuminated by the display 110 by receiving the reflected light L2.

As shown in FIG. 3, the computer 130 includes a hard disk 131, a CPU (Central Processing Unit) 132, a RAM (Random Access Memory) 133, an input/output device 134, and an I/O (Input Output) 135. Prepare

The hard disk 131 stores programs and data used in the image inspection processing described later. The hard disk 131 may be replaced with another auxiliary storage device such as a flash memory.

The CPU 132 executes the image inspection process described later by reading the program stored in the hard disk 131 into the RAM 133 and executing the program. The CPU 132 uses the data stored in the hard disk 131 (for example, the image data of the light-dark pattern image 11 and the image data of the plain image 15) when executing the image inspection processing described later. The computer 130 may include a GPU (Graphics Processing Unit) or a DSP (Digital Signal Processor) instead of or in addition to the CPU 132. In this case, the GPU or DSP may execute at least a part of the image inspection process. The image inspection process may be performed by, for example, one or more processors executing a program. At least a part of the image inspection processing may be performed by a processing circuit such as a logic circuit that does not depend on a program (in this case, the computer 130 includes the processing circuit).

Programs and data stored in the hard disk 131 are read into the RAM 133. The RAM 133 is the main memory of the CPU 132. Further, the RAM 133 holds data (image data described later and the like) generated during execution of the image inspection process. The RAM may include VRAM (Video RAM) or the like. The RAM 133 may be a flash memory or the like.

The input/output device 134 includes a display device such as a display, a voice output device, a keyboard, a mouse, and the like. The display device displays a predetermined image under the control of the CPU 132. The audio output device outputs audio under the control of the CPU 132. When the keyboard and the mouse are operated, they supply the CPU 132 with a signal according to the operation content. The CPU 132 performs processing according to the supplied signal.

The display 110 and the camera 120 are connected to the I/O 135. The CPU 132 supplies the video signal to the display 110 via the I/O 135. The display 110 displays an image based on the supplied video signal. In this way, the CPU 132 controls the display 110 by supplying the video signal. Further, the CPU 132 supplies a control signal for instructing photographing to the camera 120 to the display 110. When the control signal is supplied, the camera 120 performs a shooting operation and shoots the inspection target K illuminated by the display 110. The camera 120 supplies image data indicating a captured image obtained by the capturing to the computer 130. The image data supplied to the computer 130 is input to the I/O 135 and held in the RAM 133.

(Image inspection processing)
Next, the image inspection process executed by the CPU 132 will be described with reference to FIG. Note that steps S101 to S109 are defect detection using the light-dark pattern image 11 (FIG. 2A). The defect detection is suitable for detecting defects such as scratches on the inspection target K. Steps S111 to S118 are defect detection using the plain image 15 (FIG. 2B). The defect detection is suitable for detecting defects such as dust adhering to the inspection target K and paint peeling off of the inspection target K.

The CPU 132 first executes a first photographing process by illumination using the bright and dark pattern image 11 (step S101).

In the first shooting process, the CPU 132 controls the display 110 based on the image data stored in the hard disk 131 to display the bright-dark pattern image 11 on the display 110, and the bright portion 11A and the dark portion 11B of the bright-dark pattern image 11 ( The light/dark pattern indicated by the light/dark pattern image 11 is moved. The CPU 132 moves the bright portion 11A and the dark portion 11B by one cycle in the direction in which they are lined up (here, the vertical direction). For example, the CPU 132 slides the bright portion 11A and the dark portion 11B downward from the state of FIG. As a result, the bright portion 11A or the dark portion 11B at the lowest position gradually disappears downward, and a new bright portion 11A or the dark portion 11B gradually appears from the upper portion (FIG. 4(A)→(B)→ (See (C)→(D)→(E)). Then, when the bright portion 11A and the dark portion 11B are in the same state as the state of FIG. 4A as shown in FIG. 4E, the movement of the bright portion 11A and the dark portion 11B ends. As described above, “moving the bright portion 11A and the dark portion 11B (bright/dark pattern) by one cycle” means that the bright/dark pattern of the bright portion 11A and the dark portion 11B in a certain state is the initial pattern (FIG. 4(A)). Until the light-dark pattern of the light portion 11A and the dark portion 11B that changes due to the movement of the light portion 11A and the dark portion 11B becomes the same as the initial pattern (or until the photographing by the camera 120 described later ends), the light portion 11A and the dark portion 11B. To move (bright and dark pattern).

Further, in the first shooting process, the CPU 132 also controls the camera 120 while the bright/dark pattern image 11 is being displayed, and the camera 120 shoots the inspection target K a predetermined number of times at regular intervals. For example, the illumination time in the initial state of FIG. 4A is set as the first image capturing timing, and thereafter, the inspection target K is imaged at regular intervals. For example, the RAM 133 is provided with a timer whose timer value is updated every predetermined period, and the camera 120 is caused to take an image every time the timer value becomes one of a plurality of predetermined values. In this way, the camera 120 obtains a plurality of captured images of the inspection object K. It should be noted that each of the plurality of captured images is an image of the inspection target K in which the bright and dark patterns corresponding to the bright portion 11A and the dark portion 11B are reflected on the surface, and each light and dark pattern reflected in the inspection target K is different in each image. ing. In particular, the bright portion 11A and the dark portion 11B pass through each portion of the inspection target K (including the defective portion). Note that the plurality of captured images are captured images 1 to N (N is a natural number of 2 or more). The camera 120 supplies the image data 1 to N indicating the captured images 1 to N to the computer 130. The CPU 132 holds the image data 1 to N in the RAM 133. In this embodiment, the captured images 1 to N are grayscale images. For example, the camera 120 may obtain a grayscale image as a captured image, or the camera 120 may obtain a color image and the CPU 132 may convert it into a grayscale image by image processing. The captured images 1 to N may be images obtained by the CPU 132 subjecting the images captured by the camera 120 to predetermined image processing (e.g., emphasis processing).

After step S101, the CPU 132 generates the difference image S based on the image data 1 to N, that is, the captured images 1 to N (step S102). Specifically, the CPU 132 compares the luminance values of the pixels located at the same coordinates of the captured images 1 to N (for example, takes any value of 0 to 255 corresponding to 256 gradations), and determines the coordinates. The maximum luminance value (for example, the luminance value when illuminated by the bright portion 11A) and the minimum luminance value (for example, the luminance value when illuminated by the dark portion 11B) are specified for each of the pixels located at. Then, the CPU 132 generates a maximum brightness value image in which maximum brightness values are collected for each pixel located at each coordinate, and a minimum brightness value image in which minimum brightness values are collected for each pixel located at each coordinate. Then, the CPU 132 takes the difference between the maximum brightness value image and the minimum brightness value image to generate the difference image S.

For example, when the brightness of the pixel at the coordinates (x, y) of the i-th image is Pxy(i), the CPU 132 determines that the maximum brightness value image Qxy is Qxy=max(Pxy(i)) and the minimum brightness value image Rxy. From Rxy=min(Pxy(i)) (i=1, 2, 3... N). Further, the CPU 132 obtains the difference image Sxy by Sxy=max(Pxy)-min(Pxy). For example, when the brightness value of the upper left pixel is highest in the captured image 1 and lowest in the captured image N, the brightness value of the upper left pixel of the captured image 1 is changed to the brightness of the upper left pixel of the captured image N. The value obtained by subtracting the value becomes the brightness value of the upper left pixel of the difference image S.

The CPU 132 calculates the value of the maximum brightness value-the minimum brightness value for each pixel without generating the maximum brightness value image and the minimum brightness value image, and generates the difference image S by using each calculated value as the brightness value of each pixel. You may.

Here, the usage of the conventional difference image S will be described. In general, when a defect such as a flaw appears in a captured image, the difference between the maximum luminance value and the minimum luminance value is smaller than the difference in brightness in a normal portion having no defect. That is, the luminance value of the portion in which the defect is shown in the difference image S is smaller than the luminance value of the normal portion. This is because each brightness value of the difference image S is the difference between the maximum brightness value and the minimum brightness value. Conventionally, by utilizing such a thing, a pixel having a luminance value that is equal to or larger than a threshold value in the difference image S is “1” (white), and a pixel having a luminance value that is less than the threshold value is “0” (black). The generated image is generated and the pixel region of "0" is detected as a defect. However, if the inspection object K has undulations, the inspection object K may not be uniformly illuminated by the display 110. Specifically, in the inspection object K, a bright region and a dark region (a region darker than the bright region) may occur in the region illuminated by the bright portion 11A (or the dark portion 11B). In such a case, the brightness value (difference between the maximum brightness value and the minimum brightness value) of the portion corresponding to the dark area in the difference image is generally lower than that of the portion corresponding to the bright area (normally). Even the part will be low). Therefore, in the conventional method, the entire dark area is erroneously detected as a defect. In this embodiment, in order to eliminate such inconvenience, the following processing is performed based on the difference image S.

The CPU 132 uniformizes the brightness value of each pixel of the difference image S in each fixed range to generate a first reference image (step S103). For example, the CPU 132 divides each pixel of the difference image S into a pixel group of 16×16 pixels, and uniformizes the brightness of each pixel in each pixel group based on the brightness value of each pixel of the pixel group. .. For example, the CPU 132 equalizes the brightness values of the 16×16 pixels by setting the median value, the average value, and the like as the brightness values of the 16×16 pixels (see FIG. 6). The image thus obtained is the first reference image. The homogenization based on the median or the average value is also referred to as averaging.

Further, the same homogenization as in step S103 is performed in a range narrower than the first reference image (for example, a pixel group of 4×4 pixels) to generate a first inspection image (step S104). The values (median value, average value, etc.) used for equalization may be the same or different between the first reference image and the first inspection image.

After that, the CPU 132 specifies the dark area in the first reference image as an area not to be processed by the image inspection (step S105). For example, the CPU 132 specifies an area in which a predetermined number or more of pixels having a predetermined luminance value or less are gathered among the pixels forming the first reference image. In such an area, the difference between the brightness when illuminated by the bright portion 11A and the brightness when illuminated by the illumination 11B is small. Therefore, the area is highly likely to be an area that is originally dark and in which an area other than the inspection object K (for example, the stand ST) appears. Therefore, the area is treated as an area that is not the processing target of the image inspection. The area is specified by a labeling process or the like.

After that, the CPU 132 excludes the area outside the processing target from the images of the first reference image and the first inspection image (step S106). For example, the CPU 132 deletes the area that is not the processing target from the first reference image and the first inspection image. Alternatively, the CPU 132 holds the information of the pixels in the non-processing target area in the RAM 133, and excludes the pixel specified by the held information from the processing target in step S107 described later. The images from which the areas other than the processing target are excluded in step S106 are referred to as the second reference image and the second inspection image. Areas that are not the processing target may be excluded based on the first inspection image.

After that, the CPU 132 compares the brightness values of the pixels of the same coordinates in the second reference image and the second inspection image, respectively, and generates a binarized image according to the comparison result (step S107). For example, as shown in FIG. 7, the CPU 132 compares the luminance values of the pixels having the XY coordinates (50, 100) with each other, and determines the pixel (50, 100) as “0” (black) or according to the comparison result. Set to "1" (white). The CPU 132 performs such processing on all pixels and generates a binarized image.

Here, the second reference image is one in which the luminance values of the 16×16 pixels of the difference image S (that is, the luminance values in a wide range) are made uniform (step S103), and the luminance value of the portion in which the defect appears It is an image with less influence of. The second reference image is a reference indicating a distribution of luminance (maximum luminance value-minimum luminance value in the captured images 1 to N) in the difference image S in units of 16×16 pixels (pixel group to be uniformed). It can be said that the image. On the other hand, the second inspection image is one in which the luminance values of the 4×4 pixels (that is, the narrow range (the range narrower than the second reference image)) of the difference image S are made uniform (step S104), and the defect is It is an image that is affected by the brightness value of the reflected portion. Then, by comparing the brightness values of the second reference image and the second inspection image, the brightness value of a certain pixel in the difference image S (the maximum brightness value-the minimum brightness value in the captured images 1 to N) and the brightness value of the certain pixel What relationship does the degree of the brightness value (maximum brightness value-minimum brightness value in the captured images 1 to N) of a plurality of surrounding pixels (strictly speaking, the 16×16 pixels including the certain pixel) have? It can be grasped locally whether there is. When the luminance value of a certain pixel is lower than the luminance value of the surroundings, the certain pixel is considered to be the pixel in the portion where the defect appears. Therefore, in step S107, the CPU 132 compares the brightness values of the pixels of the same coordinates in the second reference image and the second inspection image, and the brightness value of the second inspection image is lower than the brightness value of the second reference image. Pixels in a portion lower than a predetermined standard are set to “0” (black), and pixels in other portions are set to “1” (white). The above criteria are derived in advance by, for example, experiments so that defects can be detected with high accuracy. As described above, in this embodiment, it is possible to capture a portion (a portion that seems to be a defect) in which the luminance is locally reduced in the difference image S. Therefore, even when the dark area (relatively dark area even when illuminated) occurs in the inspection object K, not the entire dark area but the part in which the defect appears is accurately represented in the binarized image. It can be a black area. That is, the defect can be detected with high accuracy in the subsequent processing.

For example, in step S107, the CPU 132 takes the ratio of the brightness values of the pixels of the same coordinates of the second reference image and the second inspection image (the brightness value of the pixels of the second reference image is the denominator), and the ratio is obtained. Is greater than or equal to a predetermined value, the pixel value of the pixel at that coordinate is set to “1” (white pixel), and the pixel values of the other pixels (pixels whose ratio is less than the predetermined value) are set to “0” (black pixel). Pixel) binarized image is generated. The predetermined value is derived in advance by, for example, an experiment so that the defect can be detected with high accuracy.

After that, the CPU 132 determines the presence or absence of a defect based on the binarized image (step S108), and records the determination result in the RAM 133 (step S109). For example, labeling is performed on black pixels of the binarized image, and a group of black pixels identified by labeling and having a predetermined number of pixels or more is determined as a defect. When a defect is detected by this determination, an image in a predetermined range including a group of the pixels is cut from the binarized image or the difference image S, and the cut image (hereinafter, referred to as a defective image) and information indicating that there is a defect. The determination result is stored in a predetermined area of the RAM 133. When no defect is detected, that effect (no defect) is stored in the processing area of the RAM 133 as a determination result.

Next, the CPU 132 executes a second photographing process by illumination using the plain image 15 (step S111). In the second photographing process, the CPU 132 controls the display 110 based on the image data stored in the hard disk 131 to display the plain image 15 on the display 110, and also controls the camera 120 so that the camera 120 controls the inspection target K. Take a picture. The number of shots may be one. Let it be a photographed image X obtained by the photographing. The camera 120 supplies the image data X indicating the captured image X to the computer 130. The CPU 132 holds the image data X in the RAM 133. The photographed image X held in the RAM 133 is also a grayscale image as in the above. The captured image X may be an image obtained by the CPU 132 performing predetermined image processing (e.g., emphasis processing) on the image captured by the camera 120.

After that, the CPU 132 makes the luminance values of the pixels of the captured image X uniform in each fixed range and generates a third reference image (step S112). Further, the same homogenization as in step S112 is performed in a narrower range than the third reference image to generate a third inspection image (step S113). Steps S112 and S113 are the same processing as steps S103 and S104 (the difference image S is changed to the captured image X). At least one of the homogenization range and the value (median value, average value, etc.) adopted in the homogenization may be different in step S103 and step S104.

After that, the CPU 132 identifies a dark region in the third reference image as a region outside the processing target of the image inspection (step S114), and identifies the identified region outside the processing target from the respective images of the third reference image and the third inspection image. Exclude (step S115). Here, the images after exclusion are the fourth reference image and the fourth inspection image. Then, the CPU 132 compares the luminance values of pixels at the same coordinates in the fourth reference image and the fourth inspection image, generates a binarized image according to the comparison result (step S116), and determines the presence/absence of a defect candidate. (Step S117), and the determination result is recorded (step S118). Steps S114 to S118 are similar to the processing of steps S105 to S109. In particular, in step S118, when a defect is detected, an image in a predetermined range including a collection of pixels detected as a defect is cut out from the binarized image or the captured image X, and a cut image (hereinafter, referred to as a defective image) is displayed. The defect information is stored as a determination result in a predetermined area of the RAM 133. When no defect is detected, that effect (no defect) is stored in the processing area of the RAM 133 as a determination result. Even if the dark area (relatively dark area even when illuminated by the bright portion 11A) is generated in the inspection object K by the steps S114 to S118, the defect is not the entire dark area, as described above. The portion corresponding to can be accurately set as the black area in the binarized image, and the defect can be detected with high accuracy.

After that, the CPU 132 refers to the determination result stored in the predetermined area of the RAM 133 (step S120). When the referenced determination result includes information indicating that there is a defect (step S120; Yes), the CPU 132 causes the display device of the input/output device 134 to display a defective image stored in the RAM 133 as the determination result, or A notification indicating that there is a defect is executed by outputting a voice indicating that there is a defect from the voice output device of the input/output device 134 (step S121). When the referred determination result includes information indicating that there is no defect (step S120; No), or after step S121, the CPU 132 ends the image inspection process. Note that when step S120; No, the CPU 132 may output information indicating no defect from the input/output device 134.

(Explanation of effects of the present embodiment)
In this embodiment, by comparing the luminance value of each pixel of the second reference image with the luminance value of each pixel of the second inspection image (step S107), the luminance value of a certain portion in the difference image S (image pickup) Since the maximum luminance value-first luminance value in images 1 to N and the degree of luminance value of the surrounding portion (average luminance value etc.) are locally compared, the luminance value when there is a defect Can be appropriately captured regardless of whether or not the certain portion is located in the dark region (a relatively dark region even when illuminated) in the inspection object K. In particular, as described above, by taking the ratio of the brightness value of each pixel of the second reference image and the brightness value of each pixel of the second inspection image, the decrease in the brightness value can be appropriately captured. Therefore, in the present embodiment, the portion corresponding to the defect can be converted into a black image in the binarized image with higher accuracy than in the conventional method, and the dark region is generated in the inspection target K. Even if it does, the accuracy of defect detection is good.

In addition, in the present embodiment, the captured image X is also compared with the luminance value of each pixel of the fourth reference image and the luminance value of each pixel of the fourth inspection image, and a binary image corresponding to the comparison result is generated. Since the image is generated, even if a portion having different brightness occurs in the inspection object K illuminated by the plain image 15, the defect can be detected with high accuracy in the same manner as described above.

In addition, in this embodiment, defect detection using the light-dark pattern image 11 (steps S101 to S109) and defect detection using the plain image 15 (steps S111 to S118) are performed. Defect detection using the light-dark pattern image 11 is suitable for detection of defects (for example, scratches) whose reflectance is significantly different from that of a non-defect portion. On the other hand, in the defect detection using the plain image 15 (defect detection by surface illumination with uniform brightness), the defect whose reflectance is not different from that of the non-defective part (for example, adhesion of dust such as dust, coating) It is suitable for detecting such as peeling). Therefore, many defects can be accurately detected by performing the above-mentioned two defect detections. In particular, in this embodiment, since the two defects are detected by displaying the image on the display 110, the two defects can be detected with a simple configuration.

Further, in this embodiment, the non-processing target area is excluded from each reference image and each inspection image (steps S106 and S115). Therefore, the burden of the subsequent processing for detecting defects (steps S107 and S116) is reduced. Further, it is possible to prevent erroneous detection of a part or all of the non-processing target area as a defect.

(Other examples of light and dark patterns)
The light and dark pattern image used in the first photographing process may not be the light and dark pattern image 11 described above. Hereinafter, variations of the light and dark pattern image will be described. It should be noted that the description overlapping with the description of the above-described embodiment, such as the description of the bright part and the dark part, is appropriately omitted.

(Bright and dark pattern image 20)
The bright/dark pattern image 20 of FIG. 8 has a first pattern image 21 and a second pattern image 22. The first pattern image 21 is displayed in the region R1 on the left side of the alternate long and short dash line. The second pattern image 22 is displayed in the region R2 on the right side of the alternate long and short dash line. The first pattern image 21 and the second pattern image 22 are simultaneously displayed in different areas on the same screen of the display 110.

The first pattern image 21 includes a plurality of bright portions 21A and a plurality of dark portions 21B that are alternately arranged in the lateral direction (X-axis direction). The plurality of bright portions 21A and the plurality of dark portions 21B form a light-dark pattern in which light and dark appear repeatedly (periodically). Each bright portion 21A and each dark portion 21B has a strip shape (rectangular shape) having the Y-axis direction as a long direction. The bright portion 21A and the dark portion 21B (bright/dark pattern) of the first pattern image 21 gradually move (slide) in the right direction (the positive direction of the X axis), as shown in FIGS. With this movement, a new bright part 21A or dark part 21B gradually appears from the left side of the region R1, and the rightmost bright part 21A or dark part 21B already displayed in the region R1 is located on the right side (one point) of the region R1. It gradually disappears with the chain line as the limit.

The second pattern image 22 includes a plurality of bright portions 22A and a plurality of dark portions 22B, which are alternately arranged in the lateral direction (X-axis direction). The plurality of bright portions 22A and the plurality of dark portions 22B form a light-dark pattern in which light and dark appear repeatedly (periodically). Each of the bright portions 22A and each of the dark portions 22B has a strip shape (rectangle) having the Y-axis direction as a long direction. The bright portion 22A has a narrower width (length in the X-axis direction) than the bright portion 21A. The dark portion 22B is also narrower than the dark portion 21B. In this way, the second pattern image 22 has a different pattern from the first pattern image 21, and in particular, the second pattern image 22 is an image of a pattern in which the repetition cycle of light and dark is smaller. Similarly to the light-dark pattern of the first pattern image 21, the light portion 22A and the dark portion 22B (light-dark pattern) of the second pattern image 22 gradually move (slide) in the right direction (the positive direction of the X axis) (FIG. 8). (See (A) to (E)). With this movement, a new bright portion 22A or dark portion 22B gradually appears from the left side (dotted line) of the area R2, and the rightmost bright portion 22A or dark portion 22B that is already displayed in the area R2 becomes the area R2. Gradually disappears with the right side of the limit.

The CPU 132 controls the display 110 to move the bright portion 21A and the dark portion 21B (bright/dark pattern) of the first pattern image 21 by one cycle, and at the same time, moves the bright portion 22A and the dark portion 22B (bright/dark pattern) of the second pattern image 22. It is moved by one cycle (see FIGS. 8A to 8E). The computer 130 simultaneously starts the movements of one cycle of each of the two light and dark patterns, and moves the two patterns at the same speed. Therefore, the moving speeds of the bright portion 21A and the dark portion 21B of the first pattern image 21 are faster than the moving speeds of the bright portion 22A and the dark portion 22B of the second pattern image 22.

In general, the light-dark pattern is suitable for detecting a defect having a small area when the width of the light portion and the width of the dark portion are narrow (the cycle of light-dark repetition is small) (on the contrary, it is difficult to detect a defect having a large area). Become). On the contrary, if the width of the bright portion and the width of the dark portion are wide (the cycle of repeating the light and dark is large), it is suitable for detecting a defect having a large area (on the contrary, it becomes difficult to detect a defect having a large area). .. In the light-dark pattern image 20, the second pattern image 22 has a smaller cycle of light and dark repetition than the first pattern image 21, so that fine defects are detected in the second pattern image 22 and the first pattern image 21 is detected. Therefore, a large defect can be detected. Therefore, when it is desired to detect a large defect in a part (first region) of the inspection object K and a fine defect in another part (second region), the first pattern image 21 is set to the first region. By displaying the second pattern image 22 in the second area, the defect can be preferably detected. Further, two objects having different defects to be detected can be collectively set as the inspection target K.

Further, although it is possible to move each light portion and each dark portion of the first pattern image 21 and the second pattern image 22 at the same speed, in such a case, the light portion 21A and the dark portion of the first pattern image 21 are moved. It takes time to move one cycle of 21B. By increasing the moving speed of the bright portion 21A and the dark portion 21B of the first pattern image 21, the moving period for one cycle can be shortened, and the time required for the image inspection for one inspection object K can be shortened. it can.

(Bright and dark pattern image 30)
Next, the light and dark pattern image 30 will be described with reference to FIG. Each of the plurality of bright portions and the plurality of dark portions of the light-dark pattern in FIG. 9 has a strip shape (rectangle) in which the direction in which the X axis extends is the long direction. The bright parts and the dark parts of the light-dark pattern image 30 are arranged alternately along the Y-axis direction.

The inspection object K (depicted as the surface of the inspection object in FIG. 9) has a horizontal surface and an inclined surface (the normal direction of the inclined surface is the normal direction of the screen of the display 110 (optical axis direction) as its surface. ) And a surface inclined in a direction orthogonal to the above). When illuminating such an inspection object K, when displaying the light-dark pattern image 39 having the same shape (same width) and the dark portion on the display 110, the light and darkness in the image of the inspection object K captured by the camera 110. The width of the bright portion and the dark portion of the pattern (the pattern reflected in the inspection object K) is different between the inclined surface and the horizontal surface (see FIG. 9B). Specifically, the width of the bright portion and the dark portion reflected on the inclined surface is wider than the width of the bright portion and the dark portion reflected on the horizontal plane. Then, the detection accuracy of the defect may be different between the horizontal surface and the inclined surface.

On the other hand, the light-dark pattern image 30 has a first pattern image 31 (a pattern that illuminates an inclined surface) and a second pattern image 32 (a pattern that illuminates a horizontal plane). The width of each of the bright part and the dark part of the first pattern image 31 is narrower than the width of each of the bright part and the dark part of the second pattern image 32 (the cycle of repeating light and dark is small). With such a configuration, even if the inspection object K has an inclined surface as shown in FIG. 9, the widths of the bright and dark portions of the light-dark pattern captured by the camera on the surface of the inspection object K have the same length. (It is possible to make the boundary between the light portion and the dark portion at equal intervals) (see FIG. 9A). This makes it possible to keep the defect detection accuracy constant.

(Bright and dark pattern image 40)
Next, the light and dark pattern image 40 will be described with reference to FIG. The description of the plurality of bright parts and the plurality of dark parts of the light-dark pattern of FIG. 10 is based on the description of FIG. 9.

The inspection object K has, as its surface, a horizontal plane and an inclined surface (a surface inclined in a direction in which the normal direction of the inclined surface is away from the direction orthogonal to the normal direction (optical axis direction) of the screen of the display 110). Have. When illuminating such an inspection target K, when displaying the light-dark pattern image 49 having the same shape (same width) and the dark portion on the display 110, the light and dark in the image of the inspection target K captured by the camera 110. The width of the bright portion and the dark portion of the pattern (the pattern reflected on the inspection object K) is different between the inclined surface and the horizontal surface (see FIG. 10B). Specifically, the width of the bright part and the dark part reflected on the inclined surface is narrower than the width of the bright part and the dark part reflected on the horizontal plane. Then, the detection accuracy of the defect may be different between the horizontal surface and the inclined surface. In addition, the width of the dark portion may be different from the width of the bright portion in each of the light and dark patterns. In such a case, in the case of FIG. Only the dark portion may be reflected on the inclined surface, and the defect detection accuracy may be degraded.

On the other hand, the light-dark pattern image 40 has a first pattern image 41 (a pattern that illuminates an inclined surface) and a second pattern image 42 (a pattern that illuminates a horizontal plane). The width of each of the bright part and the dark part of the first pattern image 41 is wider than the width of each of the bright part and the dark part of the second pattern image 42 (the cycle of repeating the light and dark is large). With such a configuration, even if the inspection object K has an inclined surface as shown in FIG. 11, the widths of the bright and dark portions of the light-dark pattern captured by the camera on the surface of the inspection object K have the same length. Can be done (borders between light and dark areas can be evenly spaced). The above inconveniences can be solved, such as the defect detection accuracy can be kept constant.

(Summary of the light-dark pattern image 30 and the light-dark pattern image 40)
When it is desired to set the light-dark pattern reflected on the inspection object K in the captured image obtained by the camera 120 to a desired pattern, for example, the display 110 displays an image of the light-dark pattern that is the desired pattern and illuminates the inspection object K. Then, the illuminated inspection object K is photographed by the camera 120. Then, the light-dark pattern shown in the image of the inspection object K obtained by the image pickup by the camera 120 may be the light-dark pattern shown by the light-dark pattern image displayed on the display 110 (the shape of the pattern is appropriately adjusted). ). This is effective, for example, when the optical axis of the display 110 and the optical axis of the camera 120 are inclined by the same angle with respect to the horizontal plane.

The inspection object K has a first surface and a second surface, and the second surface (the inclined surface in FIG. 9, the horizontal surface in FIG. 10) is closer to the first surface (the horizontal surface in FIG. 9, the inclined surface in FIG. 10). In addition, its normal direction (the normal direction of the top portion when the first surface is convex or the normal direction of the bottom when the first surface is concave) is perpendicular to the normal direction (optical axis direction) of the screen of the display 110. When it is close (when the angle formed by both directions is close to 90 degrees), the first surface is illuminated with a cycle of light and dark of the light-dark pattern that illuminates the second surface (the light-dark pattern of the illumination light that is irradiated on the second surface). It is preferable to make it smaller than the repetition cycle of light and dark of the bright and dark pattern (the bright and dark pattern of the illumination light with which the first surface is irradiated) (see FIGS. 9 and 10). Accordingly, it is possible to prevent the cycle of light and dark repetition of the light and dark pattern reflected on the inspection object K in the captured image from being significantly different between the first surface and the second surface.

(Modification)
The present invention is not limited to the above embodiment, and various modifications (including deletion of constituent elements) can be made to the above embodiment. Hereinafter, modified examples will be described, but at least some of the modified examples may be combined.

(Modification 1)
The image inspection processing may be performed by changing each of the inspection images to the difference image S and the captured image X. That is, step S104 may be omitted, and the difference image S may be used instead of the first inspection image in the processing of step S105 and subsequent steps, and step S113 may be omitted and the third inspection image may be replaced in the processing of step S114 and subsequent steps. Alternatively, the captured image X may be used. However, in this case, for example, noise or the like generated in units of a small number of pixels may not be reduced (the noise and the like can be reduced by generating an inspection image). Further, when generating each of the inspection images, the CPU 132 converts a plurality of pixels included in the range in which the brightness values are uniformized into one pixel (the brightness value takes a value after the uniformization), and An inspection image may be generated. At this time, with respect to the reference image, it is preferable to convert a plurality of pixels included in the same range as the uniformized range when the inspection image is generated into one pixel. As a result, the number of pixels can be reduced and the processing can be reduced.

(Modification 2)
When the reference image and the inspection image are generated (steps S103, S104, S112, and S113), the range of pixels for uniforming the brightness value (the number of pixels), the value used for the uniforming, and the like are set by the user Good. For example, when the user operates the keyboard and the mouse of the input/output device 134 to specify the range of pixels (the number of pixels) for uniformizing the brightness value and the method for uniformizing the brightness value, the CPU 132 thereafter specifies the specified content. Perform image inspection processing. Note that the value used for equalization is, for example, a value to be replaced when equalizing the luminance values, and is the median value of the luminance values of each pixel to be equalized, the average value of each luminance value, and each luminance value. Of the luminance values and the minimum value of the luminance values. Note that, when equalizing, noise or the like is taken into consideration, and for example, among the brightness values, a large value equal to or larger than the first criterion such as the maximum value and/or a small value equal to or smaller than the second criterion such as the minimum value are set. After excluding, the median value, the average value, the maximum value, and the minimum value may be taken.

(Modification 3)
In the defect detection in the above-described embodiment, the CPU 132 detects a portion whose brightness value is decreasing as a defect, but may detect a portion whose brightness value is increasing as a defect. The CPU 132 uses the same inspection image and reference image to generate a plurality of binarized images by changing the binarization reference and the like, and a portion where the luminance value is lowered and a portion where the luminance value is raised are generated. Each of the above may be detected as a defect.

(Modification 4)
In the binarized image, the defect may be “white” and the normal part may be “black”. Further, the presence/absence of a defect may be determined without generating a binarized image. For example, in step S107, the CPU 132 takes the ratio of the luminance values of the pixels of the same coordinates in the second reference image and the second inspection image, specifies the pixels whose ratio is less than the predetermined value, and sets the specified pixel group. If is a predetermined number or more of pixels, it may be determined that there is a defect. It should be noted that the ratio of the luminance values of the pixels at the same coordinates in each of the second reference image and the second inspection image being equal to or greater than or less than the predetermined value is a calculation obtained by multiplying or adding a coefficient to the ratio. Including that the value is above or below a specific value. For example, if the value calculated by inserting the predetermined value instead of the ratio in the equation for calculating the calculated value is the specific value, it can be said that the ratio is equal to or higher than or lower than the predetermined value.

(Modification 5)
It is not necessary to exclude the area that is not the processing target from the reference image and the inspection image. That is, steps S105 to S106 and S114 to S115 may be omitted.

(Modification 6)
The shape of the bright portion and the dark portion of each light-dark pattern may be, for example, a shape in which the bright portion and the dark portion alternately (periodically) appear in a plane perpendicular to the optical axis direction (illumination direction) of the illumination light. Good. For example, a light-dark pattern in which bright portions and dark portions alternately appear in all directions in a plane perpendicular to the irradiation direction may be used. The bright part may be brighter than the dark part. One of the width of the bright portion and the dark portion (the length along the direction in which the light/dark pattern is moved) may be different from the other width. Each of the light and dark patterns is one of one bright portion and one dark portion, one bright portion and two dark portions, two bright portions and one dark portion, a plurality of bright portions and a plurality of bright portions. It should be composed of. Even in the case of one bright portion and one dark portion, a new bright portion or dark portion may be displayed due to the movement of the light and dark pattern, so a bright and dark pattern including one bright portion and one dark portion. Also, the light and dark patterns are cyclical, with one bright portion and one dark portion as one cycle.

(Modification 7)
The light-dark pattern shown by the first pattern image 21 and the like and the light-dark pattern shown by the second pattern image 22 and the like may move in different directions. The bright portion 21A of the first pattern image 21 and the bright portion 22A of the second pattern image 22 may be elongated along different directions.

(Modification 8)
Instead of the display, a mask having a slit forming a bright part and a lamp arranged on the back of the mask may be used.

(Modification 8)
The bright and dark patterns may have three or more different patterns depending on the shape of the inspection object K and the like. For example, the light and dark pattern image may be composed of three or more pattern images respectively showing different light and dark patterns. In addition, the moving direction of the bright and dark patterns such as the bright portion (the direction in which the bright and dark are repeated) may be different for each of the plurality of bright and dark patterns.

(Modification 9)
One inspection object K may be composed of a plurality of products or the like. For example, the illumination target of the first pattern image may be one product of the inspection target K, and the illumination target of the second pattern image may be another product of the inspection target K.

(Modification 10)
The defect detection method is not limited to the above method, and an appropriate method can be adopted. For example, the defect detection using the bright and dark pattern image 11 and the defect detection using the plain image 15 are performed by one display 110, but the image processing method (defect detection algorithm) may be another method. Good. By using the display 110 for illumination, different modes of illumination can be easily performed, and defect detection using the light-dark pattern image 11 (defect detection using illumination with a stripe pattern) and defect using the plain image 15 can be performed. Detection (defect detection using surface illumination with uniform brightness) can be easily performed.

(Modification 11)
Although the light-dark pattern is moved in the above embodiment, the light-dark pattern may be moved relative to the inspection object K, and the inspection object K may be moved.

(Modification 12)
An image of a light-dark pattern such as the light-dark pattern image 11 and a uniformly bright image such as the plain image 15 are displayed together on the display 110, and each image separately illuminates different regions of the inspection object K. You may. As a result, appropriate illumination can be performed according to the defect to be detected.

(Modification 13)
Instead of the plain image 15, an image having a certain pattern or the like (an image having a non-light and dark pattern different from the light and dark pattern image 11 and the like may be used) may be used. Even such an image may be advantageous in detecting a predetermined type of defect. By displaying a plurality of types of images in the same display area at different timings and illuminating the same area as in the image inspection process, it is possible to detect defects of different types with high accuracy.

(Structure disclosed in this specification)
Hereinafter, a configuration taking the above-described embodiment and modified examples as an example will be described. At least some of the following configurations may be combined. It should be noted that the image processing performed by each configuration described below may include any other image processing.

(1) An image inspection apparatus (for example, an image inspection apparatus) that performs an image inspection for inspecting the presence or absence of a defect in the inspection object using an inspection object image (for example, a difference image S or a captured image X) obtained by imaging the inspection object. 100. Incidentally, the computer 130 of them may be regarded as an image inspection apparatus).
Generating a first comparison image (for example, various reference images) in which the brightness of a plurality of pixels forming the inspection target image is equalized for each first pixel group based on the brightness of each pixel included in the first pixel group. First generating means (for example, the CPU 132 that executes at least step S103 or S112),
The brightness of the plurality of pixels forming the inspection target image is equalized for each second pixel group having a smaller number of pixels than the first pixel group based on the brightness of each pixel included in the second pixel group. Second generation means (for example, the CPU 132 that executes at least step S104 or S113) that generates two comparison images (for example, various inspection images);
The brightness of each of the plurality of pixels forming the first comparison image and the brightness of each of the plurality of pixels forming the second comparison image are compared between pixels at the same position, and the relationship between the two brightnesses is based on a predetermined reference. Defect detection means (for example, the CPU 132 that executes steps S107 to S108 or S116 to S117) that detects a defect based on the presence or absence of satisfying pixels,
An image inspection apparatus including.

The inspection target image is an image of the inspection target such as an image obtained based on a plurality of captured images like the difference image S, an image obtained by performing a predetermined image processing on the captured image, in addition to the captured image of the inspection target. Any image can be used. Although the inspection target image is the difference image S and the captured image X in the above-described embodiment, it may be an image after performing appropriate image processing on these images. Further, the generation of the first comparison image by the first generation means may include image processing other than homogenization. This also applies to the second generation means. The image processing other than the homogenization may include the processing of excluding the non-processing target images from the first and second comparison images by the processing of steps S105 to S106 or S114 to S115.

(2) The defect detection unit is a pixel at the same position with a ratio of the brightness of each of the plurality of pixels forming the first comparison image and the brightness of each of the plurality of pixels forming the second comparison image. Taken by each other, a defect is detected based on the presence or absence of a pixel whose ratio satisfies a certain criterion (for example, less than the predetermined value) (for example, the CPU 132 that executes steps S107 to S108 or S116 to S117),
You may do it.

(3) The first generation unit averages the brightness of the plurality of pixels for each of the first pixel groups (for example, the CPU 132 that executes step S103 or S112),
You may do it.

(4) The second generation unit averages the brightness of the plurality of pixels for each of the second pixel groups (for example, the CPU 132 that executes step S104 or S113),
You may do it.

The averaging may be performed by taking the median value or the average value of the brightness of each pixel included in the first pixel group or the second pixel group.

(5) Acquisition unit (for example, CPU 132 that executes step S101) that acquires a plurality of photographed images of the inspection target, in which the states of the light and dark patterns reflected on the surface of the inspection target are different. When,
Inspection target image generation means for generating the inspection target image in which the difference between the minimum brightness and the maximum brightness of the brightness of each pixel at the same position in the plurality of captured images acquired by the acquisition means is defined as the brightness of each pixel. (For example, the CPU 132 that executes step S102),
May be further provided.

(6) The defect detection unit identifies a pixel group having a luminance less than a fixed value among the pixels of the first comparison image, and identifies the identified pixel group from the first comparison image and the second comparison image. The brightness of each of the plurality of pixels that form the first comparison image that are excluded and that exclude the pixel group, and the brightness of each of the plurality of pixels that form the second comparison image that exclude the pixel group , Are compared between pixels at the same position (for example, the CPU 132 that executes steps S105 to S106 or S114 to S115),
You may do it.

(7) First illumination control means (for example, the CPU 132 that executes step S101) that illuminates the inspection target by displaying a moving image of the light and dark pattern (for example, the light and dark pattern image 11) on the display,
Second illumination control means (for example, CPU 132 that executes step S111) that illuminates the inspection target by displaying an image of a non-bright/dark pattern (for example, a solid image 15) on the display,
The inspection target illuminated by the image of the light-dark pattern is captured by a camera a plurality of times, and a plurality of first captured images (for example, captured images 1 to N) in which the inspection target is captured are obtained from the camera, and First image acquisition means (for example, CPU 132 that executes step S101) that obtains a first image (for example, difference image S) based on the first captured image of
A second image acquisition in which the inspection target illuminated by the image of the non-bright and dark pattern is captured by the camera, and a second captured image of the inspection target is obtained as a second image (for example, captured image X) from the camera. Means (for example, the CPU 132 that executes step S111),
The image processing apparatus inspects using the first image as the inspection target image and inspects using the second image as the inspection target image (for example, the CPU 132 that executes an image inspection process),
You may do it.

(8) A program that causes a computer to execute the processing performed by each component of the image processing apparatus. The program may be provided (installed) in a computer by being recorded in various storage media such as a CD (Compact Disc), or may be provided (installed) in the computer via a network such as the Internet ( Other programs are the same).

(9) An image inspection apparatus (for example, the image inspection apparatus 100. For example, the image inspection apparatus 100, which inspects the inspection object for defects by using an inspection object image (for example, the difference image S or the captured image X) obtained by imaging the inspection object. Of these, the computer 130 may be regarded as an image inspection device.)
A generation unit (for example, various reference images) that generates a comparison image in which the brightness of a plurality of pixels forming the inspection target image is made uniform for each pixel group based on the brightness of each pixel included in the pixel group. Generating means for generating (for example, the CPU 132 that executes at least step S103 or S112),
The brightness of each of the plurality of pixels forming the comparison image and the brightness of each of the plurality of pixels forming the inspection target image are compared between pixels at the same position, and the relationship between the two brightnesses satisfies a predetermined criterion. Defect detection means for detecting a defect based on the presence or absence of a pixel (for example, modified example 1),
An image inspection apparatus including.

The description of the inspection target image and the generation of the comparison image by the generation unit is based on the description of the inspection target image and the generation of the first comparison image by the first generation unit.

(10) A program that causes a computer to execute the processing performed by each component of the image processing apparatus.

(11) While illuminating a first region (for example, a part of the inspection target K) of the inspection target of the image inspection with the first light-dark pattern, the second light-dark pattern different from the first light-dark pattern causes the inspection target of the inspection target to be Illumination means (for example, the display 110 that displays the light-dark pattern image 20, 30, or 40) that illuminates a second area (for example, another part of the inspection target K) different from the first area,
Movement control means for moving the first bright-dark pattern and the second bright-dark pattern relative to the inspection target (for example, CPU 132 that controls the display image displayed on the display 110 (moves the bright-dark pattern)). When,
A lighting device including.

The illuminating means includes a configuration for displaying both the first light-dark pattern and the second light-dark pattern, and also for displaying three or more light-dark patterns. A program that causes the computer 130 that controls the display 110 to implement the function of the lighting device (a program that causes the computer to display or move the first light-dark pattern and the second light-dark pattern). May be realized by

(12) The illumination unit uses the display light (display light indicating each image) when displaying the image of the first bright-dark pattern and the image of the second bright-dark pattern, and the first region and the second region. Is a display that illuminates (for example, the display 110 that displays the light-dark pattern image 20, 30, or 40),
You may do it.

(13) The movement control means moves the first bright-dark pattern and the second bright-dark pattern at different speeds (see, for example, FIG. 8),
You may do it.

(14) The first light-dark pattern and the second light-dark pattern are patterns in which light and dark are periodically repeated (see, for example, FIGS. 8 and 10),
The cycle of repeating the light and dark of the first light-dark pattern is larger than the cycle of repeating the light-dark of the second light-dark pattern (see, for example, FIGS. 8 and 10),
You may do it.

(15) The normal line direction of the second region is closer to the optical axis of the illuminating unit than the normal line direction of the first region (for example, see FIG. 10),
You may do it.

(16) One of the above lighting devices (for example, the display 110 and the CPU 132),
A camera (for example, a camera 120) that obtains a plurality of captured images by capturing a plurality of images of the inspection target illuminated by the illumination device,
An inspection unit that inspects the first region and the second region for defects based on the plurality of captured images obtained by the camera (for example, the CPU 132 that performs steps S102 to S108). ,
Image inspection device (for example, image inspection device 100).

11 bright and dark pattern image 11A bright part 11B dark part 15 plain image 20, 30, 40 bright and dark pattern image 21, 31, 41 first pattern image 22, 32, 42 second pattern image 100 image inspection device 110 display 120 camera 130 computer 132 CPU

Claims (5)

Illumination for illuminating a first region of the inspection target of the image inspection with the first light-dark pattern and illuminating a second region different from the first region of the inspection target with a second light-dark pattern different from the first light-dark pattern. Means and
Movement control means for moving the first light-dark pattern and the second light-dark pattern relative to the inspection object;
Equipped with
The movement control means moves the first light-dark pattern and the second light-dark pattern at different speeds,
Lighting equipment. The illumination unit is a display that illuminates the first region and the second region with display light when displaying the image of the first light-dark pattern and the image of the second light-dark pattern.
The lighting device according to claim 1. The first light-dark pattern and the second light-dark pattern are patterns in which light and dark are periodically repeated,
A cycle of repeating light and dark of the first light and dark pattern is larger than a cycle of repeating light and dark of the second light and dark pattern,
The lighting device according to claim 1 or 2. The normal direction of the second area is closer to the optical axis of the illumination means than the normal direction of the first area.
The lighting device according to claim 3 . A lighting device according to claim 1-4 any one,
A camera that obtains a plurality of captured images by capturing a plurality of images of the inspection target illuminated by the illumination device,
An inspection unit that inspects the first area and the second area for defects based on the plurality of captured images obtained by the camera;
An image inspection apparatus including.

Images