JP2020144076A - Inspection system and inspection method - Google Patents

Abstract

To provide a space-saving inspection system capable of swiftly performing defect inspection with high accuracy at low cost.SOLUTION: The inspection system includes: a lighting device 201 for radiating light to the observation surface of an object to be inspected; an image pick-up device 203 for picking up images of the observation surface; and a computer 205 that detects color unevenness and roughness on the observation surface. The image pick-up device 203 has multiple pixels 301 each of which includes: a sub-pixel 303 for receiving light passing through a pupil area 305 of an imaging lens 204; and a sub-pixel 304 for receiving light passing through a pupil area 306. The computer 205 detects roughness by using a first image obtained from the sub-pixel 303 and a second image obtained from the sub-pixel 304.SELECTED DRAWING: Figure 2

Description

The present invention relates to an inspection device and an inspection method for optically inspecting unevenness, color unevenness, etc. on the surface of an object to be inspected.

For example, a rough surface rubber roller used for a toner cartridge or the like is manufactured by passing a core metal (metal rod) through a rubber polished into a cylindrical shape and applying a paint to which fine particles are added. If the surface of the rough rubber roller has irregularities or uneven color (hereinafter collectively referred to as "defects"), the desired function may not be obtained, so the surface is inspected in the production process. .. The unevenness refers to unevenness caused by rubber unevenness, adhesion of polishing residue, non-uniformity of paint, etc., which is functionally unacceptable. Color unevenness is a portion (dirt) in which the color of the surface has changed due to the adhesion of foreign matter or the like, although the shape is not different from that of a good product. Color unevenness also requires inspection in the manufacturing process because it may not be possible to obtain the desired function due to the surface texture being different from that of the non-defective product.

As an example of a method for inspecting unevenness and color unevenness on the surface of an object to be inspected, Patent Document 1 discloses a method for inspecting unevenness and color unevenness on a plate. One inspection method disclosed in Patent Document 1 is obtained by sequentially irradiating an object to be inspected with two lights from different angles and taking an image with a camera having a positional relationship of receiving the specularly reflected light of one of the lights. This is a method of detecting scratches and color unevenness by image processing of the image. Another inspection method disclosed in Patent Document 1 is an image obtained by irradiating an object to be inspected with a single light and taking an image with a camera that receives the specularly reflected light and a camera that receives the diffusely reflected light. This is a method of detecting scratches and color unevenness by the image processing of.

Japanese Unexamined Patent Publication No. 2007-271510

However, in the inspection method disclosed in Patent Document 1, both the inspection method requiring two lights and the inspection method requiring two cameras increase the device cost and the device size. There is a problem that becomes large. In an inspection method that requires two lights, an image is taken with the first light turned on and the second light turned off, then the first light is turned off and the second light is turned on. There is a problem that it takes a long time for the inspection because it is necessary to take an image in this state. In an inspection method that requires two cameras, the inspection result may vary depending on the position accuracy of the two cameras.

An object of the present invention is to provide a low-cost, space-saving inspection device capable of performing defect inspection quickly with high accuracy.

The inspection apparatus according to the present invention includes an illumination means for irradiating an observation surface of an object to be inspected with light, an imaging means for imaging the observation surface, a color unevenness detecting means for detecting color unevenness of the object to be inspected, and the above. The imaging means includes an image pickup lens that forms an image of light from the observation surface, and a plurality of image pickup means that receive light from the image pickup lens to generate an image. The plurality of pixels include an image pickup element composed of the above pixels, and the plurality of pixels each include a first light receiving portion that receives light that has passed through a first region of the emission pupil of the image pickup lens, and an emission pupil of the image pickup lens. It has a second light receiving portion that receives light that has passed through the second region of the above, and the unevenness detecting means is obtained from the first image obtained from the first light receiving portion and the second light receiving portion. It is characterized in that the unevenness is detected by using the obtained second image.

According to the present invention, it is possible to provide a low-cost, space-saving inspection device capable of quickly performing defect inspection with high accuracy.

It is a figure explaining the schematic structure of the rough surface rubber roller and the defect which occurs on the surface. It is a figure explaining the schematic structure of the inspection apparatus which concerns on embodiment of this invention. It is sectional drawing explaining the structure of the image pickup element provided in the camera of an inspection apparatus, and the relationship between a pixel and an image pickup lens. It is a figure which shows the state of the image formation of the object with respect to the image sensor. It is a figure explaining the image corresponding to FIG. It is a flowchart of the defect inspection method by an inspection apparatus. It is a schematic diagram explaining the detection processing method of color unevenness. It is a schematic diagram explaining the unevenness detection processing method.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. First, a rough surface rubber roller, which is an example of an object to be inspected, and a defect generated on the surface of the rough surface rubber roller will be described. The rough surface rubber roller is used for a toner cartridge or the like of a printing device such as an MFP.

FIG. 1 is a diagram illustrating a schematic configuration of a rough surface rubber roller 101 and a defect generated on the surface of the rough surface rubber roller 101. The rough surface rubber roller 101 has a structure in which a metal core metal 103 is inserted and fitted into a cylindrical rubber portion 102. As shown in FIG. 1, the thrust axial direction (length direction) of the rough surface rubber roller 101 is defined as the Y direction. Further, in a plane orthogonal to the Y direction, the X direction and the Z direction orthogonal to each other are defined.

A paint to which fine particles are added is applied to the surface of the rubber portion 102, and as a result, the surface of the rubber portion 102 is a rough surface having fine irregularities. In the production process, the rough surface rubber roller 101 may have unevenness 104 due to adhesion of foreign matter (polishing residue or the like), non-uniformity of paint, or the like. In addition, color unevenness 105 may occur on the traces of peeling after foreign matter adheres to the surface of the rubber portion 102, the portion where the paint has deteriorated, and the like. In an apparatus equipped with a rough surface rubber roller 101 in which these defects are present, there is a high possibility that desired performance cannot be obtained. Therefore, it is necessary to inspect for defects in the production process and remove defective products.

FIG. 2 is a diagram illustrating a schematic configuration of an unevenness and color unevenness inspection device according to an embodiment of the present invention. The inspection device includes a lighting device 201, a camera 202, a computer 205, and a monitor 206. The camera 202 has an image sensor 203 and an image lens 204. Note that FIG. 2 shows a configuration in which the camera 202 / computer 205 and the computer 205 / monitor 206 are connected by cables, respectively, but the configuration of the inspection device is not limited to this. For example, if the control circuit of the image pickup device provided with the lighting device and the monitor has the function of the computer 205, the inspection device can be configured only by the image pickup device.

The core metal 103 of the rough surface rubber roller 101 is held by a rotary gripping member (not shown), and the rough surface rubber roller 101 is rotatably arranged around the Y axis (around the thrust axis). In the inspection device, the observation surface 207 on the surface of the rough rubber roller 101 is irradiated with light from the lighting device 201, and the observation surface 207 irradiated with the light is imaged by the camera 202. The image pickup lens 204 of the camera 202 is arranged so that the observation surface 207 and the image pickup element 203 are in a conjugated relationship with each other. The camera 202 transmits the image data of the image generated by the imaging operation to the computer 205.

For imaging, it is desirable that the entire axial direction of the rough surface rubber roller 101 is included in the imaging range and the entire imaging range is in focus. However, if the entire axial direction of the rough rubber roller 101 cannot be included in the imaging range due to the relationship between the performance of the camera 202 and the size of the rough rubber roller 101, a mechanism for moving the rough rubber roller 101 in the axial direction is provided. Just do it. Details of the configuration of the image sensor 203 will be described later.

The computer 205 acquires an image captured by the camera 202 and displays the acquired image on the monitor 206. The computer 205 is a so-called computer, which includes a storage medium such as a CPU, ROM, RAM, and hard disk, and the storage medium stores a program or the like for executing each process shown in the flowchart of FIG. 6 to be described later. ing. The computer 205 inspects the observation surface 207 for defects by executing a predetermined program and analyzing the image (image data) acquired from the camera 202. The details of the defect inspection method will be described later.

In the image captured by the camera 202, minute irregularities on the surface of the rubber portion 102 can be detected as an image shift described later. Therefore, the lighting device 201 may be a general one, and the light applied to the rough surface rubber roller 101 may be a general white light. On the other hand, when the surface of the object to be inspected has a relatively strong mirror surface or the optical magnification is low, it may be difficult to detect minute irregularities on the rough surface. In that case, the lighting device 201 capable of irradiating the pattern light may be used to detect the image deviation of the projected pattern of the irradiated pattern light. From the viewpoint of improving the inspection performance of color unevenness, it is desirable to perform the inspection by dark field observation. That is, the angle of light irradiation with respect to the normal of the observation surface 207 and the angle of the imaging optical axis are different (the angle formed by the normal of the observation surface 207 and the direction of light irradiation on the observation surface 207 is the normal of the observation surface 207. It is desirable that the angle is different from that of the imaging optical axis).

Next, the image sensor 203 included in the camera 202 will be described. FIG. 3A is a top view (viewed from the −Z direction) of the image sensor 203. Here, the image sensor 203 will be described as a two-dimensional area sensor, but the image sensor 203 is not limited to this, and may be a one-dimensional line sensor. The image sensor 203 has a plurality of pixels 301, and each pixel 301 includes two sub-pixels 303 (first light receiving unit) and sub-pixel 304 (second light receiving unit) that share the microlens 302.

FIG. 3B is a cross-sectional view illustrating the relationship between the pixel 301 and the image pickup lens 204. The pupil region 305 (first region) and the pupil region 306 (second region) of the image pickup lens 204 represent the left half and the right half of the exit pupil of the image pickup lens 204, respectively. The microlens 302 of the pixel 301 controls the light receiving intensity distribution of the sub-pixels 303 and 304 with respect to the incident angle of the light incident on the pixel 301. In the image sensor 203, the light received by the sub-pixel 303 is dominated by the light that has passed through the pupil region 305, and the light received by the sub-pixel 304 is dominated by the light that has passed through the pupil region 306. Has been done. The sub-pixels 303 and 304 can read signals individually. Therefore, it is possible to acquire an image based on the signal read only from the sub-pixel 303 (hereinafter referred to as “A image”) and an image based on the signal read only from the sub-pixel 304 (hereinafter referred to as “B image”).

The principle that makes it possible to determine whether the object to be inspected is on the focal surface or the non-focal surface from the image captured by the image sensor 203 will be described.

FIG. 4A is a diagram showing an image formation of the object 402 with respect to the image sensor 203 when the object 402 is present on the object surface 401 which is a conjugate surface of the image sensor 203. The object 402 is, for example, a color unevenness 105 generated on the surface of the rubber portion 102.

In the case of FIG. 4A, the object 402 exists on the object surface 401. The light emitted from the object surface 401 (the surface of the rubber portion 102) passes through the pupil regions 305 and 306, but is again focused on a point on the image sensor 203. FIG. 5A is a diagram for explaining an image of an object 402 imaged on the image sensor 203 under the conditions of FIG. 4A. The upper row shows the A image 501 of the object 402, and the middle row shows the B image of the object 402. The lower row represents the 502, and the lower row represents the AB image 503 (A image + B image) of the object 402. When the object 402 exists on the object surface 401, the A image 501 and the B image 502 appear at close positions (coordinates) in the image. That is, the A image 501 and the B image 502 appear at a position where the distance between the center of the A image 501 and the center of the B image 502 becomes short.

FIG. 4B is a diagram showing an image formation of the object 402 with respect to the image sensor 203 when the object 402 exists at a position away from the object surface 401 (when the object 402 exists at a defocused position). Is. In the case of FIG. 4B, since the image of the object 402 is formed in front of the image sensor 203, the light passing through the pupil region 305 and the light passing through the pupil region 306 are located in regions separated from each other on the image sensor 203. To reach. FIG. 5B is a diagram for explaining an image of an object 402 imaged on the image sensor 203 under the conditions of FIG. 4B. The upper row shows the A image 511 of the object 402, and the middle row shows the B image of the object 402. 512 is shown in the lower row, and AB image 513 of the object 402 is shown in the lower row. When the object 402 is located away from the object surface 401, the A image 511 and the B image 512 are separated positions (shifted positions) in the image as compared with the case where the object 402 is on the object surface 401. Appears in. That is, the distance between the center of the A image 511 and the center of the B image 512 is longer than the distance between the center of the A image 501 and the center of the B image 502. This phenomenon is so-called image shift. The AB image 513 in which the image shift occurs becomes an overall larger image (blurred image) than the AB image 503.

In addition, in FIG. 4B and FIG. 5B, the case where the image of the object 402 is imaged in front of the image sensor 203 has been described, but the case where the image of the object 402 is imaged behind the image sensor 203. However, the A image and the B image appear at distant positions in the image. The sign of the amount of image deviation is inverted depending on whether the image of the object 402 is imaged in front of the image sensor 203 or behind the image sensor 203.

Next, the inspection flow in the defect inspection method by the inspection device will be described. FIG. 6 is a flowchart of a defect inspection method using an inspection device. FIG. 6 shows that the CPU of the computer 205 (hereinafter simply referred to as “CPU”) expands a predetermined program stored in a storage medium such as a ROM into a RAM and controls the operation of each part of the inspection device. The process (step) indicated by the S number is realized.

When the CPU (computer 205) starts the inspection, the CPU (computer 205) first turns on the lighting device 201 in S601. In S602, the CPU drives the rotary gripping member holding the core metal 103 to rotate the rough surface rubber roller 101. In S603, the CPU captures the entire surface of the rubber portion 102 of the rough surface rubber roller 101 by capturing a predetermined number of images with the camera 202 while rotating the rough surface rubber roller 101. In S603, automatic imaging is performed at predetermined time intervals according to the rotation speed of the rough surface rubber roller 101. In imaging, the rotation speed of the rough surface rubber roller 101 and the shutter speed of the camera 202 are set under conditions that do not cause image blurring due to the rotation of the rough surface rubber roller 101. It should be noted that the rough surface rubber roller 101 may be repeatedly rotated and paused to take an image at the time of the pause.

When the imaging is completed, the CPU stops the rotation of the rotary grip member in S604. Then, in S605, the CPU turns off the lighting device 201. In S606, the CPU performs color unevenness detection processing using the image acquired in S603. Subsequently, in S607, the CPU performs an unevenness detection process using the image acquired in S603, and this process ends.

The color unevenness detection process of S606 and the unevenness detection process of S607 may be executed in the reverse order, or one of the processes may not be performed. Further, the order of lighting the lighting device 201 of S601 and starting rotation of the rough surface rubber roller 101 of S602 may be reversed. Similarly, the order of ending the rotation of the rough surface rubber roller 101 of S604 and turning off the lighting device 201 of S605 may be reversed.

Next, the color unevenness detection process (S606) will be described in detail. The color unevenness detection process is performed using an A + B image (third image) which is an image obtained by adding the A image (first image) and the B image (second image) acquired by the camera 202. .. FIG. 7 is a schematic diagram illustrating a method for detecting color unevenness. FIG. 7A shows a first luminance profile 701 that is an unprocessed luminance profile of the A + B image before image processing, the horizontal axis is pixel coordinates, and the vertical axis is the luminance level. Has been taken. Although the actual A + B image is a two-dimensional image, it will be described here with a one-dimensional profile from the viewpoint of giving a brief explanation.

In the first luminance profile 701, the luminance is extremely high in a part of the pixels, and this portion is the color unevenness signal 702. Further, a global gradation having a long wavelength and a local noise having a short wavelength are superimposed on the first luminance profile 701. FIG. 7B shows the second luminance profile 703 after the first luminance profile 701 is subjected to the large smoothing process. The large smoothing process is to apply a filter process with a relatively large kernel size for the purpose of extracting only the global gradation information. As the kernel size, tens to hundreds of pixels, for example, which are sufficiently larger than the defect to be detected, are used. It can be seen that the color unevenness signal 702 existing in the first luminance profile 701 disappears in the second luminance profile 703 by the large smoothing process.

FIG. 7C shows a third luminance profile 704 after the first luminance profile 701 is subjected to a small smoothing process. Small smoothing is filtering with a relatively small kernel size for the purpose of removing local noise. The kernel size is sufficiently smaller than the defect to be detected, and for example, several pixels to several tens of pixels are used. It can be seen that the local noise existing in the first luminance profile 701 disappears in the third luminance profile 704 by the small smoothing process.

FIG. 7D shows a fourth luminance profile 705, which is the difference between the third luminance profile 704 and the second luminance profile 703. It can be seen that in the fourth luminance profile 705, the global gradation and local noise are removed from the first luminance profile 701, and the color unevenness signal 702 is extracted.

FIG. 7E shows a fifth luminance profile 706 obtained by binarizing the fourth luminance profile 705 with a threshold value 707. In the fifth luminance profile 706, the luminance level of the pixel whose luminance value is the threshold value 707 or more in the fourth luminance profile 705 is set to '255', and the luminance level of the pixel whose brightness value is less than the threshold value 707 is set to '0 (zero). '. The color unevenness region 708 is obtained as a region having a luminance level of '255'. Since the actual image is two-dimensional, the binarized image is further subjected to labeling processing, blob analysis, and the like. As a result, the circumscribing rectangle of the defect region can be calculated as shown in the circumscribing rectangle 520 shown in the lower part of FIG. 5B.

The parameters such as the filter size and the threshold value described above for the color unevenness detection process are finally determined in consideration of the over-detection rate and the false detection rate of defects. In FIG. 7, the case where the brightness of the color unevenness is higher than that of the surroundings is taken up, but the case is not limited to this, and the brightness is smaller than that of the surroundings when the color unevenness is absorbent or when the inspection is performed in a bright field. Color unevenness can also be detected by the same method.

Next, the unevenness detection process (S607) will be described in detail. The unevenness detection process is executed on the A image and the B image acquired by the camera 202. FIG. 8 is a schematic diagram illustrating a method for detecting unevenness. FIG. 8A shows the luminance profile 801 of the A image and the luminance profile 802 of the B image before the image processing in the unevenness detection processing, with the pixel coordinates on the horizontal axis and the luminance level on the vertical axis. There is. Although the actual A image and B image are two-dimensional images, here, from the viewpoint of concise explanation, a one-dimensional profile will be described. Further, although the actual brightness levels of the A image and the B image are about the same, in FIG. 8A, in order to avoid difficulty in distinguishing due to overlapping profiles, they are displayed offset vertically. There is. The A image and the B image may be subjected to shading correction processing or filtering processing as necessary.

The brightness profile 801 of the A image and the brightness profile 802 of the B image show a change in brightness according to minute irregularities caused by particles contained in the paint applied to the surface of the rubber portion 102 of the rough rubber roller 101. .. The regions 803 and 805 correspond to regions without irregularities, and in these regions, the phases of the luminance profile 801 of the A image and the luminance profile 802 of the B image are substantially the same as shown by the broken line. The region 804 corresponds to the uneven region, and as shown by the broken line in this region, the luminance profile 801 of the A image and the luminance profile 802 of the B image are out of phase.

FIG. 8B shows a difference value 808 obtained by taking the difference between the luminance profile 801 of the A image and the luminance profile 802 of the B image. In the region 803 and the region 805, since the phases of the luminance profile 801 of the A image and the luminance profile 802 of the B image are aligned, the difference is almost 0 (zero). On the other hand, in the region 804, since the luminance profile 801 of the A image and the luminance profile 802 of the B image are out of phase, there are many regions where the absolute value of the difference value does not take a value close to zero.

FIG. 8B shows a predetermined positive upper threshold 806 and a negative lower threshold 807. In FIG. 8C, the profile 809 is binarized to '1' in the region where the difference value 808 is below the lower threshold value 807 and the region where the difference value is above the upper threshold value 806, and to '0' in the other regions. It is shown. Here, the absolute values of the lower threshold value 807 and the upper threshold value 806 are set to the same value, and in this case, the region where the absolute value of the difference value 808 is larger than the absolute values of the lower threshold value 807 and the upper threshold value 806 is '1'. In addition, the other areas are binarized to '0'. Although it is possible to extract the region 804 in the profile 809 as well, there are scattered regions whose values are ‘0’ in the region 804 as well.

FIG. 8D shows a profile 810 in which the profile 809 is subjected to morphology processing or the like to be corrected to a region in which the regions 804 are connected. A region 804, which is a concavo-convex region, can be detected from this profile 810.

Next, specific conditions for defect inspection will be described. It is assumed that a line sensor having a pixel pitch of 5.0 μm and a number of pixels of 7500 pixels observes a visual field (inspection area) of 60 mm. The work distance (distance from the line sensor to the object to be inspected) increases or decreases depending on the distance between the principal points of the imaging lens, but here it can be set to approximately 210 mm. In this case, the pixel resolution is 60 (mm) x 1000/7500 (pixel) = 8.0 μm / pixel, and the optical magnification (horizontal magnification) is 5.0 (μm) /8.0 (μm / pixel) = about 0. 63 times, the optical magnification (vertical magnification) is 0.63 x 0.63 = about 0.4 times. Therefore, when the size of the unevenness to be detected is 50 μm, the defocus amount on the image plane side is 50 (μm) × 0.4 = 20 μm.

As described above, according to the present invention, since only one lighting device and one camera are required, it is possible to realize a low-cost, space-saving inspection device. Since there are few components of the inspection device and the device configuration is not complicated, the load on the device maintenance can be reduced. Then, since the defect is detected by automatically performing the imaging process of the object to be inspected and analyzing the imaging data, the defect inspection can be performed quickly. Since the inspection device according to the present invention only requires one lighting device and one camera, the position of the lighting device and the camera with respect to the object to be inspected is the cause as compared with the inspection device using two lighting devices and two cameras. The occurrence of the error is suppressed. This makes it possible to detect defects with high accuracy.

Although the present invention has been described in detail based on the preferred embodiments thereof, the present invention is not limited to these specific embodiments, and various embodiments within the scope of the gist of the present invention are also included in the present invention. included. For example, in the above embodiment, the CPU of the computer 205 starts the defect detection process by executing a predetermined program. However, the present invention is not limited to this, and a PLC (Programmable Logic Controller) may be configured to execute the defect inspection instead of the computer 205.

The present invention supplies a program that realizes one or more functions of the above-described embodiment to a system or device via a network or storage medium, and one or more processors in the computer of the system or device reads and executes the program. It can also be realized by the processing to be performed. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

101 Rough surface rubber roller 102 Rubber part 104 Concavo-convex 105 Color unevenness 201 Lighting device 202 Camera 203 Image sensor 204 Image lens 205 Calculator 301 Pixel 303, 304 Sub-pixel

Claims (14)

Lighting means that irradiates the observation surface of the object to be inspected with light,
An imaging means for imaging the observation surface and
The color unevenness detecting means for detecting the color unevenness of the object to be inspected, and
The unevenness detecting means for detecting the unevenness of the object to be inspected is provided.
The imaging means
An imaging lens that forms an image of light from the observation surface,
It has an image sensor composed of a plurality of pixels that receives light from the image pickup lens and generates an image.
Each of the plurality of pixels receives a first light receiving portion that receives light that has passed through the first region of the exit pupil of the imaging lens and a light that has passed through the second region of the exit pupil of the imaging lens. It has a second light receiving part and
The unevenness detecting means is an inspection apparatus characterized in that the unevenness is detected by using a first image obtained from the first light receiving unit and a second image obtained from the second light receiving unit. The inspection device according to claim 1, wherein the lighting means irradiates the object to be inspected with patterned light. The illuminating means and the imaging means are arranged so that the irradiation angle of the light by the illuminating means with respect to the normal of the observation surface and the angle of the optical axis of the imaging lens are different from each other. 2. The inspection device according to 2. The unevenness detecting means obtains a difference value between the brightness profile of the first image and the brightness profile of the second image, and the brightness level of the difference value is larger than the upper threshold value of the positive value and has a negative value. The inspection apparatus according to any one of claims 1 to 3, wherein a region smaller than the lower threshold value is extracted, and a region in which the extracted regions are connected is detected as the unevenness. Any one of claims 1 to 4, wherein the color unevenness detecting means detects the color unevenness by using a third image obtained by adding the first image and the second image. The inspection device described in the section. The color unevenness detecting means has a luminance level after performing a large smoothing process on the luminance profile of the third image and a luminance level after performing a small smoothing process on the luminance profile of the third image. The inspection device according to claim 5, wherein a region in which the absolute value of the difference between the two is larger than a predetermined threshold value is detected as the color unevenness. The image sensor according to any one of claims 1 to 6, wherein the image pickup device is a line sensor having a pixel pitch of 5.0 μm and a number of pixels of 7,500 pixels, and has a pixel resolution of 8.0 μm / pixel. Inspection device. It is a method of inspecting color unevenness and unevenness on the surface of the object to be inspected.
The step of irradiating the observation surface of the object to be inspected with light and
It has a plurality of pixels that receive light from an image pickup lens that forms an image of light from the observation surface to generate an image, and the plurality of pixels each pass through a first region of an exit pupil of the image pickup lens. A step of imaging the observation surface with an image pickup device having a first light receiving unit that receives light and a second light receiving unit that receives light that has passed through a second region of the exit pupil of the image pickup lens.
A step of storing a first image obtained from the first light receiving unit and a second image obtained from the second light receiving unit.
An inspection method comprising the step of detecting the unevenness using the first image and the second image. The inspection method according to claim 8, wherein in the step of irradiating the object to be inspected with light, the object to be inspected is irradiated with pattern light. According to claim 8 or 9, the angle formed by the normal of the observation surface and the direction of light irradiation on the observation surface is different from the angle formed by the normal and the optical axis of the imaging lens. The described inspection method. In the step of detecting the unevenness, the difference value between the brightness profile of the first image and the brightness profile of the second image is obtained, and the region where the brightness level of the difference value is larger than the upper threshold value of the positive value is determined. The inspection method according to any one of claims 8 to 10, wherein a region smaller than the lower threshold value of a negative value is extracted, and the region in which the extracted regions are connected is detected as the unevenness. A step of storing a third image obtained by adding the first image and the second image, and
The inspection method according to any one of claims 8 to 11, further comprising a step of detecting the color unevenness using the third image. In the step of detecting the color unevenness, the luminance level after the luminance profile of the third image is subjected to the large smoothing process and the luminance level after the luminance profile of the third image is subjected to the small smoothing process. The inspection method according to claim 12, wherein a region in which the absolute value of the difference from the luminance level is larger than a predetermined threshold value is detected as the color unevenness. The invention according to any one of claims 8 to 13, wherein a line sensor having a pixel pitch of 5.0 μm and a number of pixels of 7500 pixels is used as the image sensor, and the pixel resolution is set to 8.0 μm / pixel. Inspection method.

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