JP2021139817A - Workpiece surface inspection device, surface inspection system, surface inspection method, and program - Google Patents

Abstract

To provide a workpiece surface inspection device, etc., with which it is possible to prevent a decrease in efficiency due to the fact that the inspection of glossiness is carried out in a separate step from a workpiece surface defect detection step.SOLUTION: The workpiece surface inspection device comprises: image acquisition means 52 which, while a workpiece 1 that is the object of surface defect detection is illuminated by illumination light of light-dark pattern having at least a pair of light and dark parts, acquires the images in the inspection range of the workpiece 1 having been sequentially imaged by imaging means 4; detection means 53 for detecting surface defects on the basis of the images acquired by the image acquisition means and repeating a detection process until inspection for the inspection range is completed; and feature quantity calculation means 54 for calculating the feature quantity of pertaining to the gloss of workpiece surface using the images acquired by the image acquisition means 52, in parallel with surface defect detection process by the detection means 53, until inspection for the inspection range is completed.SELECTED DRAWING: Figure 8

Description

The present invention is a surface inspection device for a work, which detects surface defects of a work such as a vehicle body based on an image obtained when an image is taken by an imaging means, and calculates a feature amount related to the glossiness of the work surface. Regarding surface inspection systems, surface inspection methods and programs.

As described above, with the work such as the painted surface of the vehicle body irradiated with at least a pair of light and dark patterns by the lighting device, a plurality of images of the measured portion of the work are imaged, and the captured plurality of images are used. A technique for detecting surface defects of a work has been conventionally known (for example, Patent Document 1). Surface defects on the painted surface of the car body include paints and dust that have already hardened in the painted paint film, such as lumps, and dripping and swelling of the paint material, such as dripping. There are holes and dents that are partially formed on the coating film due to the repulsion of the paint that does not adhere uniformly, or scratches that occur when an object comes into contact with the surface.

International Publication WO2018 / 221006

However, the visual inspection of the painted surface of an automobile at a factory not only detects surface defects, but also quantitatively monitors the gloss of the surface. Conventionally, it is a separate process independent of the detection of surface defects. The gloss is inspected, which increases the number of visual inspection processes and is not efficient.

Although Patent Document 1 discloses the detection of surface defects, it does not describe the inspection of gloss.

The present invention has been made in view of such a technical background, and it is possible to prevent a decrease in efficiency due to a step of detecting surface defects of the work and a step of inspecting the gloss of the work surface in separate steps. It is an object of the present invention to provide a surface inspection device, a surface inspection system, a surface inspection method and a program.

The above object is achieved by the following means.
(1) With the work to be detected of surface defects illuminated with illumination light having a light-dark pattern having at least a pair of bright parts and dark parts, images sequentially captured by an imaging means for the inspection range of the work are acquired. The image acquisition means, the detection means that detects surface defects based on the image acquired by the image acquisition means, and repeats the detection process until the inspection for the inspection range is completed, and the inspection for the inspection range. By the end, the feature amount calculation means for calculating the feature amount related to the glossiness of the work surface using the image acquired by the image acquisition means in parallel with the surface defect detection process by the detection means. A work surface inspection device characterized by being equipped with.
(2) The surface defect detected by the detection means is a surface defect of the painted appearance of an automobile, and the feature amount related to the glossiness calculated by the feature amount calculating means is the glossiness of the painted appearance of the automobile. The work surface inspection apparatus according to item 1 above, which is a related feature quantity.
(3) The work surface inspection device according to item 1 or 2 above, wherein the feature amount calculating means calculates a feature amount related to glossiness using a single image acquired by the image acquiring means.
(4) The feature amount calculation means is a plurality of images taken by the image pickup means and acquired by the image acquisition means when the positional relationship between the work and the light / dark pattern of the illumination light is relatively changed. The surface inspection apparatus for a workpiece according to item 1 or 2 above, wherein a feature amount related to glossiness is calculated using a composite image obtained by synthesizing the above.
(5) The work surface inspection apparatus according to any one of items 1 to 4 above, wherein the feature amount calculating means calculates a feature amount of a gloss value from a feature amount related to the calculated glossiness.
(6) An imaging means for sequentially imaging the inspection range of the work in a state where the work to be detected for surface defects is illuminated with illumination light having a light-dark pattern having at least a pair of bright parts and dark parts, and the above items 1 to 5. A surface inspection system comprising the work surface inspection apparatus according to any one of the above.
(7) The surface defect detected by the detection means is a surface defect of the painted appearance of an automobile, and the feature amount related to the glossiness calculated by the feature amount calculating means is a characteristic of the glossiness of the painted appearance of the automobile. The surface inspection system for the workpiece according to item 6 above, which is the amount.
(8) A moving means for moving the illumination light of the light / dark pattern relative to the work is provided, and the imaging means moves the light / dark pattern relative to the work by the moving means. The work surface inspection system according to item 6 or 7 above, wherein the inspection range of the work is sequentially imaged.
(9) A step of sequentially imaging the inspection range of the work by an imaging means in a state where the work to be detected for surface defects is illuminated with illumination light having a light-dark pattern having at least a pair of bright and dark parts, and the imaging. A surface defect is detected based on an image acquisition step of acquiring an image captured by the means by the image acquisition means and an image acquired by the image acquisition step, and detection processing is performed until the inspection of the inspection range is completed. By the time the repeated detection step and the inspection of the inspection range are completed, the surface defect detection process by the detection step is performed in parallel, and the image acquired by the image acquisition step is used to relate to the glossiness of the work surface. A surface inspection method for a workpiece, which comprises a feature amount calculation step for calculating a feature amount to be performed.
(10) The surface defect detected in the detection step is a surface defect of the painted appearance of an automobile, and the feature amount related to the glossiness calculated in the feature amount calculation step is the glossiness of the painted appearance of the automobile. The method for surface inspection of a work according to item 9 above, which is a related feature amount.
(11) The work surface inspection method according to item 10 above, further comprising a correction step for correcting the painted portion in which the surface defect is detected, and the feature amount calculation step is executed for the corrected portion after the correction of the painted portion.
(12) In a state where the work to be detected for surface defects is illuminated with illumination light having a light-dark pattern having at least a pair of bright parts and dark parts, images sequentially captured by an imaging means for the inspection range of the work are acquired. The detection step of detecting surface defects based on the image acquisition step and the image acquired by the image acquisition step, and repeating the detection process until the inspection of the inspection range is completed, and the inspection of the inspection range are completed. In parallel with the surface defect detection process by the detection step, the feature amount calculation step of calculating the feature amount related to the glossiness of the work surface using the image acquired by the image acquisition step is performed. A program that lets a computer run.
(13) The surface defect detected by the detection step is a surface defect of the painted appearance of an automobile, and the feature amount related to the glossiness calculated by the feature amount calculation step is a characteristic of the glossiness of the painted appearance of the automobile. The program according to the preceding item 12, which is a quantity.
(14) In the feature amount calculation step, the computer is made to execute a process of calculating a feature amount related to glossiness using a single image imaged by the imaging means and acquired by the image acquisition step. The program according to 13.
(15) In the feature amount calculation step, a plurality of images taken by the imaging means and acquired by the image acquisition means when the positional relationship between the work and the light / dark pattern of the illumination light is relatively changed. The program according to any one of items 12 to 14 above, which causes the computer to execute a process of calculating a feature amount related to glossiness using a composite image obtained by combining the above.
(16) The program according to any one of items 12 to 15 above, in which the feature amount calculation step calculates the feature amount of the gloss value from the feature amount related to the calculated glossiness.

According to the inventions described in the preceding paragraphs (1), (6) and (9), an image is taken in a state where the work to be detected for surface defects is illuminated with a light-dark pattern having at least a pair of bright and dark parts. Images of the inspection range of the workpieces sequentially imaged by the means are acquired, surface defects are detected based on the acquired images, and the detection process is repeated until the inspection of the inspection range is completed. Further, by the time the inspection of the inspection range is completed, the feature amount related to the glossiness of the work surface is calculated using the image acquired by the image acquisition means in parallel with the surface defect detection process.

In this way, since the feature amount related to the glossiness is calculated in parallel with the surface defect detection process, it is necessary to inspect the gloss in a separate process completely independent of the work surface defect detection process. Therefore, the processing efficiency of the entire inspection process is improved and the processing time is shortened. Further, conventionally, the process of detecting surface defects of a work is performed on the entire number of works, and the gloss inspection may be performed on some of the works, but it is acquired in parallel with the detection of surface defects. By calculating the feature amount related to the glossiness using the image, the glossiness can be inspected for the entire number of workpieces, which leads to the improvement of quality.

According to the inventions described in the preceding paragraphs (2), (7) and (10), the feature amount related to the glossiness of the painted appearance of the automobile is calculated in parallel with the detection of the surface defect of the painted appearance of the automobile. be able to.

According to the invention described in the preceding paragraph (3), since the feature amount related to the glossiness is calculated using the single image acquired by the image acquisition means, the calculation time of the feature amount related to the glossiness is short. It's done.

According to the invention described in the previous section (4), a feature amount related to glossiness is used by using a composite image obtained by synthesizing a plurality of images when the positional relationship between the work and the illumination light of the light / dark pattern is relatively changed. Therefore, it is possible to perform a highly accurate calculation.

According to the invention described in the preceding paragraph (5), the feature amount of the gloss value can be calculated from the feature amount related to the calculated glossiness.

According to the invention described in the preceding paragraph (11), the feature amount related to the glossiness is calculated after the painted portion where the surface defect is detected is corrected.

According to the invention described in the previous section (12), in a state where the work to be detected for surface defects is illuminated with illumination light having a light-dark pattern having at least a pair of bright parts and dark parts, the inspection range of the work is sequentially measured by an imaging means. The captured image is acquired, surface defects are detected based on the acquired image, and the detection process is repeated until the inspection of the inspection range is completed, and the surface defects are detected by the time the inspection of the inspection range is completed. In parallel with the detection process of, the computer can be made to execute a process of calculating the feature amount related to the glossiness of the work surface using the acquired image.

According to the invention described in the preceding paragraph (13), it is possible to cause a computer to execute a process of calculating a feature amount related to the glossiness of the painted appearance of an automobile in parallel with the detection of surface defects of the painted appearance of the automobile. can.

According to the invention described in the previous section (14), a computer can be made to execute a process of calculating a feature amount related to glossiness using a single image acquired by the image acquisition step.

According to the invention described in the previous section (15), a process of calculating a feature amount related to glossiness using a plurality of images when the positional relationship between the work and the light / dark pattern of the illumination light is relatively changed. , Can be run by a computer.

According to the invention described in the preceding paragraph (16), a computer can be made to execute a process of calculating a feature amount of a gloss value from a feature amount related to the calculated glossiness.

It is a perspective view which shows the structural example of the surface inspection system of the work which concerns on one Embodiment of this invention. It is a figure which shows the state which displayed the lighting pattern on the display surface of the lighting apparatus in the surface inspection system of FIG. (A) to (E) are diagrams showing an example of an illumination pattern. (A) to (C) are diagrams showing other lighting pattern examples. It is a figure which shows still another lighting pattern example. It is a perspective view which shows the modification of the surface inspection system of the work shown in FIG. It is a block diagram which shows the structure of the surface inspection apparatus. It is a flowchart which shows an example of the process of the surface inspection method by the surface inspection system of the work shown in FIG. It is a flowchart which shows the other example of the process of the surface inspection method by the surface inspection system of the work shown in FIG. (A) to (C) are diagrams for explaining the first calculation process of the feature amount related to the glossiness. It is a figure for demonstrating the 1st feature amount calculation process in more detail. (A) to (C) are diagrams for explaining the second calculation process of the feature amount related to the glossiness. It is a figure for demonstrating the 2nd calculation process in more detail. It is a graph used to explain other feature amount calculation processing related to glossiness.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.

FIG. 1 is a perspective view showing a configuration example of a surface inspection system for a work according to an embodiment of the present invention. In this embodiment, the work 1 is a vehicle body, the portion to be measured of the work 1 is a painted surface on the vehicle body surface, surface defects on the painted surface are detected, and a feature amount related to the glossiness of the painted surface is calculated. Show the case. Generally, the surface of the vehicle body is subjected to base treatment, metallic coating, clear coating, etc. to form a coating film layer with a multi-layer structure. Defects occur. As the surface defects, as described above, there are bumps, sagging, repellents, scratches and the like. In this embodiment, it is applied to the detection of such surface defects and the calculation of the feature amount related to the glossiness, but the work 1 is not limited to the vehicle body and may be a work other than the vehicle body. Further, the portion to be measured may be a surface other than the painted surface.

This inspection system includes a work moving mechanism 2 composed of, for example, a conveyor that continuously moves the work 1 in the direction of arrow F at a predetermined speed, a lighting device 3 that illuminates a part to be measured of the work 1, and an illuminated object to be measured. The image pickup device 4 that images the part and the image of the part to be measured imaged by the image pickup device 4 are acquired to detect the surface defect, and in parallel with this detection process, the feature amount related to the glossiness is calculated. It is provided with a surface inspection device 5 for performing.

In order to detect surface defects, the illuminating device 3 needs to irradiate the measured portion of the work 1 with a light-dark pattern having at least a pair of bright parts and dark parts. The type of the lighting device 3 is not limited as long as it can irradiate a light-dark pattern having at least a pair of bright parts and dark parts. As an example of the lighting device 3, as shown in FIGS. 2 and 3A, a part of the planar light emitting portion is covered with a black mask in the moving direction of the work 1, so that the lighting device 3 is covered with a black mask. An LED lighting device or the like that illuminates the measured portion with a pair of stripe patterns of the dark portion 32 and the uncovered bright portion 31 can be mentioned.

The illumination pattern is not limited to that shown in FIGS. 2 and 3 (A), and may be a stripe pattern in which a plurality of pairs of bright areas 31 and dark areas 32 exist as shown in FIG. 3 (B). However, as shown in FIG. 6C, the lighting device 3 may have a striped pattern of a bright portion 31 and a dark portion 32 formed in the vertical direction.

Further, the lighting pattern may be a checkered pattern instead of a striped pattern. For example, FIG. 3 (D) shows an example of a checkered pattern having a bright portion 31 and a dark portion 32 in the vertical diagonal direction, respectively, and in FIG. 3 (E), three or more bright portions 31 and dark portions 32 are arranged alternately. An example of the checkered pattern is shown.

Further, the bright portion 31 and the dark portion 32 do not have to be at equal intervals or equal areas, and as shown in FIGS. 4A to 4C, at least one of the intervals or the areas of the bright portion 31 and the dark portion 32 is different. Is also good.

Further, the formation of the dark portion 32 does not need to be formed by masking a part of the light emitting surface of the lighting device 3. For example, as shown in FIG. 5, only the bright portion 31 is formed by the lighting device 3. A light-dark pattern may be formed by forming a dark portion 32 around the lighting device 3. Further, instead of masking a part of the light emitting surface of the lighting device 3, the lighting patterns of the bright portion 31 and the dark portion 32 may be formed by changing the light emitting state of the light emitting surface.

Further, in the example of FIG. 1, the work 1 is configured to be continuously moved by the moving device 2, but as shown in FIG. 6, the work 1 is fixed and the lighting device 3 is continuously moved by the moving mechanism 2. It may be configured. In this case, the image pickup device 4 may or may not move together with the lighting device 3.

Further, both the work 1 and the lighting device 3 may move at different moving speeds so that one of them moves relative to the other.

Further, when the lighting device 3 is composed of a display panel such as an LED, the lighting pattern and the work 1 are formed by scrolling the light / dark pattern displayed on the display surface on the display surface without physically moving the lighting device 3. May be moved relatively.

The image pickup device 4 is a CCD camera or a CMOS camera, and may be a camera that generates an image in monochrome or a camera that generates an image in color. In this embodiment, the imaging device 4 sequentially images the preset inspection range of the work 1 at predetermined time intervals while moving at least one of the light / dark pattern of the lighting device 3 and the work 1.

The imaging operation of the imaging device 4, the moving operation of the work 1 or the lighting device 3, the control of the lighting pattern of the lighting device 3, and the like are performed by a control device (not shown). Alternatively, it may be controlled by the surface inspection device 5.

FIG. 7 is a block diagram showing a functional configuration of the surface inspection device 5. The surface inspection device 5 is composed of a personal computer, and includes a processor such as a CPU, a memory such as a RAM, a storage device such as a hard disk, a display device 51, and other hardware and software. The surface inspection device 5 includes an image acquisition unit 52, a surface defect detection unit 53, a gloss feature amount calculation unit 54, and the like as one of the functions of the CPU.

The image acquisition unit 52 acquires a plurality of images that are continuously imaged by the image pickup device 2 in the inspection range in time series and are sequentially transmitted from the image pickup device 2. The surface defect detection unit 53 detects surface defects based on the image from the image pickup device 4 acquired by the image acquisition unit 52. The detection of surface defects is repeated until the inspection in the inspection range is completed. As a method for detecting surface defects, for example, the method described in Patent Document 1 (International Publication WO2018 / 221006) or any other known method may be used.

The gloss feature amount calculation unit 54 calculates the feature amount related to the glossiness of the surface of the work 1 by using the image acquired by the image acquisition unit 51. This feature amount calculation step is performed in parallel with the surface defect detection step by the surface defect detection unit 53 until the inspection of the inspection range is completed.

The detection result of the surface defect by the surface defect detection unit 53 and the calculation result of the feature amount related to the glossiness by the gloss feature amount calculation unit 54 are displayed on the display unit 51.

FIG. 8 is a flowchart showing an example of the process of the surface inspection method by the surface inspection system of the work shown in FIG.

In step S01, the inspection range of the work 1 is sequentially photographed by the imaging device 4 at regular time intervals while illuminating the light and dark patterns with the lighting device 3. The captured image is transmitted to the surface inspection device 5, and in step S02, the image acquisition unit 52 acquires the transmitted image, and in step S03, the acquired image is associated with the position information of the image in the work 1. It is stored and stored in a storage unit such as a hard disk device (not shown).

Next, in step S04, it is checked whether or not the entire range has been imaged, and if it has not been imaged (NO in step S04), the process returns to step S01 and imaging is continued. If the entire range has been imaged (YES in step S04), the process proceeds to step S05.

In step S05, the images saved by the surface inspection device 5 are read out in order, and in step S06, the read images are used to relate to the surface defect detection process by the surface defect detection unit 53 and the glossiness by the gloss feature amount calculation unit 54. The calculation process of the feature amount to be performed is performed in parallel.

In step S07, it is checked whether or not the entire inspection range has been inspected, and if it has not been inspected (NO in step S07), the process returns to step S05 to read the next image, and similarly, surface defect detection processing and glossiness are performed. The feature amount related to is calculated.

If the entire inspection range has been inspected in step S07 (YES in step S07), the inspection ends.

As described above, in this embodiment, the surface defect detection unit 53 performs the surface defect detection process, and the gloss feature amount calculation unit 54 performs the gloss feature amount calculation process for calculating the feature amount related to the glossiness. Therefore, the surface of the work 1 is subjected to the calculation process. It is no longer necessary to inspect the gloss in a separate process completely independent of the defect detection process, and the processing efficiency of the entire inspection process is improved and the processing time is shortened accordingly. Further, conventionally, the process of detecting surface defects of the work 1 is performed on the entire number of the works 1, and the gloss inspection may be performed on some of the works, but in parallel with the detection of the surface defects, By calculating the feature amount related to the glossiness using the acquired image, the glossiness can be inspected for the entire number of the work 1, which leads to the improvement of the quality.

It should be noted that performing the surface defect detection process and the feature amount calculation process related to glossiness in parallel is not limited to the case where the surface defect detection process and the feature amount calculation process related to glossiness are performed at the same time. , The surface defect detection process and the feature amount calculation process related to glossiness may be alternately performed. In short, both the surface defect detection process and the feature amount calculation process related to glossiness are performed on the work 1. It may be performed in one surface inspection step.

In addition, it is not necessary to calculate the feature amount related to the glossiness for all the images used for the surface defect detection process, and the frequency of the feature amount calculation process related to the glossiness is calculated on the surface. It may be less frequently than the defect detection process.

FIG. 9 is a flowchart showing another example of the process of the surface inspection method by the surface inspection system of the work shown in FIG. In this example, when the surface defect detection process is performed and then the portion where the surface defect is detected is corrected by repainting or the like, the surface defect is detected and the feature amount related to the glossiness is calculated for the corrected portion. It is something to do.

In step S11, the portion where the surface defect is detected is corrected by repainting or the like, and then in step S12, the corrected portion (inspection range) of the work 1 is sequentially measured by the imaging device 4 while illuminating the light and dark pattern by the lighting device 3. Take a picture. The captured image is transmitted to the surface inspection device 5, and in step S13, the image acquisition unit 52 acquires the transmitted image, and in step S14, the acquired image is associated with the position information of the image in the work 1. It is stored and stored in a storage unit such as a hard disk device (not shown).

Next, in step S15, it is checked whether or not the entire correction range has been imaged, and if it has not been imaged (NO in step S15), the process returns to step S12 and imaging is continued. If the entire correction range has been imaged (YES in step S15), the process proceeds to step S16.

In step S16, the images saved by the surface inspection device 5 are sequentially read out, and in step S17, the surface defect detection unit 53 re-detects the surface defects and the gloss feature amount calculation unit 54 uses the read images to perform another surface defect detection process. The calculation process of the feature amount related to is performed in parallel.

In step S18, it is checked whether or not the entire correction range has been inspected, and if it has not been inspected (NO in step S18), the process returns to step S16 to read the next image, and similarly, surface defect detection processing and glossiness are performed. The feature amount related to is calculated.

If the entire correction range has been inspected in step S18 (YES in step S18), the inspection ends.

In this way, even in the surface inspection after the surface defect detection portion is corrected, the gloss feature amount calculation unit 54 calculates the feature amount related to the glossiness in parallel with the surface defect detection process by the surface defect detection unit 53. In the method shown in the flowchart of FIG. 9, the surface defect detection process and the feature amount related to glossiness calculation process may be performed at the same time, or the surface defect detection process and the feature related to glossiness may be performed at the same time. The amount calculation process may be performed alternately, and both the surface defect detection process and the feature amount calculation process related to the glossiness may be performed in one surface inspection step for the corrected portion of the work 1.

Further, the frequency of the feature amount calculation process related to the glossiness may be lower than the frequency of the surface defect detection process.

Further, in the methods shown in FIGS. 8 and 9, all the images captured and transmitted by the imaging device 4 are temporarily stored and stored in the surface inspection device 5, and after the imaging is completed, the captured image is used for the surface. Although the configuration is such that the defect detection process and the feature amount related to the glossiness are calculated, the image pickup by the image pickup apparatus 4, the acquisition of the captured image, the surface defect detection process, and the feature amount related to the glossiness are performed. The calculation process may be performed simultaneously.

Next, a method of calculating the feature amount related to the glossiness will be described.

[1] First Calculation Process In this example, the feature amount related to the glossiness is calculated from one captured image (single image). Here, the glossiness is a parameter relating to the amount of light that is specularly reflected from the object to be measured of the work 1 with respect to the brightness of the light source of the illumination surface device 3.

In the image acquired from the image pickup device 4 by the image acquisition unit 52, as shown in FIG. 10, patterns of the bright band 6 and the dark band 7 corresponding to the light and dark patterns of the lighting device 3 are generated. The difference between the bright portion of the bright zone 6 and the dark portion of the dark zone 7 is defined as a feature amount related to the glossiness.

In this example, a plurality of pairs of stripe type patterns shown in FIG. 3B are adopted as the light and dark patterns. The same applies to the subsequent calculation processing examples.

10 (A) to 10 (C) show three types of samples having different feature amounts related to glossiness. The left figure of each figure is an image of the measured portion, and the right figure is the left figure. It is a graph in which the position in the width direction of the bright band 6 and the dark band 7 is taken on the horizontal axis and the gray value is taken on the vertical axis for a part of the captured image. The gray value is a comparison value (%) with respect to the brightness of the illumination surface device 3. In FIG. 10 (A), the feature amount (brightness difference of the image) related to the glossiness is 2, 9 in FIG. 10 (B), 11 in FIG. 10 (C), and (A) (B). ) (C), the glossiness increases in this order.

To explain this process in more detail with reference to FIG. 11, first, the measured value regarding the brightness of the lighting device 3 is measured in advance. For example, the brightness value of the illuminating device 3 is measured by using a sample having a known reflectance and measuring the reflected light from the sample when illuminated by the illuminating device 3.

Next, the original image G1 composed of a single image is subjected to moving average processing to create the image G2. Then, a measurement range S1 is set on the image G2, and the difference between the maximum value and the minimum value of the gray value is calculated by comparing with the brightness value of the lighting device 3 in the set measurement range S1 to obtain the glossiness. Let it be a related feature quantity.

[2] Second Calculation Process This processing method calculates the feature amount related to the glossiness by using a plurality of images captured for the part to be measured of the work 1.

When at least one of the light and dark patterns of the work 1 and the lighting device 3 is relatively moved and images are continuously taken at regular time intervals, a plurality of images in which the measured portion of the work 1 is sequentially moved can be obtained. The feature amount related to the glossiness is calculated using these a plurality of images.

12 (A) to 12 (C) show three types of samples having different feature amounts related to glossiness, and the left figure of each figure is one image (single image) among a plurality of images. The figure on the right is a composite image obtained by synthesizing a plurality of images. In the composite image, in this embodiment, the difference between the maximum pixel value and the minimum pixel value (MAX-MIN) of the plurality of images is obtained for each pixel, and the obtained difference is the pixel value of each pixel of the composite image. It is created by.

Then, the average value of each pixel value included in the measurement range S1 surrounded by a square in each composite image is obtained, and this is converted into a comparison (%) with the brightness value of the lighting device 3 to be a feature related to glossiness. The amount. The obtained feature amounts were 2 in (A), 9 in (B), and 11 in (C) in FIG. 12, and the average values increased in the order of (A), (B), and (C), and the glossiness increased. The degree is high.

This process will be described in more detail. While the patterns of the bright portion 31 and the dark portion 32 of the lighting device 3 move relative to the measurement site of the work 1 for one cycle, the image pickup device 4 performs seven imaging times at equal intervals, and FIG. 13 shows. It is assumed that seven images G11 to G17 showing a part are obtained.

First, the measured value regarding the brightness of the lighting device 3 is measured in advance. Next, for each pixel of the images G11 to G17, the difference (MAX-MIN) between the maximum pixel value and the minimum pixel value of the images G11 to G17 is obtained, and the obtained difference is used as the pixel value of each pixel. The composite image G21 shown in the figure is created.

Then, the measurement range S1 is set in the image G21, the average value of each pixel value included in the measurement range S1 is obtained, and this is converted into a comparison (%) with the brightness value of the lighting device 3 and is related to the glossiness. The feature amount to be used. It should be noted that the median value, the mode value, or the like may be used instead of the average value.

[3] Other processing The gloss value of the gloss measuring machine currently on the market or used may be calculated based on the feature amount calculated in the above processes [1] and [2].

For example, in the case of 20-degree gloss, 60-degree gloss, and 80-degree gloss, which are the measured values of a gloss measuring device called GM-268A manufactured by Konica Minolta Co., Ltd., each gloss value, the brightness difference value of a single image, and the graph of FIG. 14 are shown. There is a relationship as shown. By utilizing this relationship, it may be possible to predict and calculate 20-degree gloss, 60-degree gloss, and 80-degree gloss from the difference in brightness.

Further, in the method of calculating the gloss value of the measuring instrument GM-268A, the feature amount related to the glossiness calculated in [1] and [2] and the data related to the gloss value of the measuring instrument GM-268A are prepared and multivariate analysis is performed. A mechanism that can calculate the predicted value may be incorporated by performing the above. Further, although the gloss value of the measuring instrument GM-268A is given as an example here, the gloss value of another measuring instrument may be calculated by the same method.

The present invention can be used, for example, as a surface inspection of a workpiece such as a vehicle body, when detecting surface defects and calculating a feature amount related to glossiness.

1 Work 2 Moving mechanism 3 Lighting device 4 Imaging device 5 Surface inspection device 6 Bright band 7 Dark zone 8 Boundary line 31 Bright part 32 Dark part 51 Display part 52 Image acquisition part 53 Surface defect detection part 54 Glossy feature amount calculation part

Claims (16)

An image acquisition means for acquiring images sequentially captured by an imaging means for an inspection range of the workpiece in a state where the workpiece to be detected for surface defects is illuminated with illumination light having a bright / dark pattern having at least a pair of bright and dark portions. When,
A detection means that detects surface defects based on the image acquired by the image acquisition means and repeats the detection process until the inspection of the inspection range is completed.
By the time the inspection of the inspection range is completed, the feature amount related to the glossiness of the work surface is calculated using the image acquired by the image acquisition means in parallel with the surface defect detection process by the detection means. Feature amount calculation means and
A work surface inspection device characterized by being equipped with. The surface defect detected by the detecting means is a surface defect of the painted appearance of an automobile, and the feature amount related to the glossiness calculated by the feature amount calculating means is a feature related to the glossiness of the painted appearance of the automobile. The work surface inspection apparatus according to claim 1, which is a quantity. The work surface inspection device according to claim 1 or 2, wherein the feature amount calculating means calculates a feature amount related to glossiness by using a single image acquired by the image acquiring means. The feature amount calculating means synthesizes a plurality of images when the positional relationship between the work and the light / dark pattern of the illumination light is relatively changed, which is captured by the imaging means and acquired by the image acquisition means. The work surface inspection apparatus according to claim 1 or 2, wherein a feature amount related to glossiness is calculated using a composite image. The work surface inspection apparatus according to any one of claims 1 to 4, wherein the feature amount calculating means calculates a feature amount of a gloss value from a feature amount related to the calculated glossiness. An imaging means for sequentially imaging the inspection range of the work in a state where the work to be detected for surface defects is illuminated with illumination light having a light-dark pattern having at least a pair of bright parts and dark parts.
The work surface inspection apparatus according to any one of claims 1 to 5.
A surface inspection system characterized by being equipped with. The surface defect detected by the detecting means is a surface defect of the painted appearance of an automobile, and the feature amount related to the glossiness calculated by the feature amount calculating means is a feature amount of the gloss of the painted appearance of the automobile. The work surface inspection system according to claim 6. A moving means for moving the illumination light of the light / dark pattern relative to the work is provided.
The surface inspection system for a work according to claim 6 or 7, wherein the imaging means sequentially images the inspection range of the work while moving the light / dark pattern relative to the work by the moving means. A step of sequentially imaging the inspection range of the work by an imaging means in a state where the work to be detected for surface defects is illuminated with illumination light having a light-dark pattern having at least a pair of bright and dark parts.
An image acquisition step of acquiring an image captured by the imaging means by the image acquisition means, and an image acquisition step.
A detection step in which surface defects are detected based on the image acquired in the image acquisition step and the detection process is repeated until the inspection of the inspection range is completed.
By the time the inspection for the inspection range is completed, the feature amount related to the glossiness of the work surface is calculated using the image acquired by the image acquisition step in parallel with the surface defect detection process by the detection step. Feature calculation steps to be performed and
A method of surface inspection of a workpiece, which is characterized by being equipped with. The surface defects detected in the detection step are surface defects of the painted appearance of the automobile, and the feature amount related to the glossiness calculated in the feature amount calculation step is a feature related to the glossiness of the painted appearance of the automobile. The surface inspection method for a workpiece according to claim 9, which is a quantity. The work surface inspection method according to claim 10, further comprising a correction step for correcting the painted portion in which the surface defect is detected, and the feature amount calculation step is executed for the corrected portion after the correction of the painted portion. An image acquisition step of acquiring images sequentially captured by an imaging means for an inspection range of the workpiece in a state where the workpiece to be detected for surface defects is illuminated with illumination light having a bright / dark pattern having at least a pair of bright and dark portions. When,
A detection step in which surface defects are detected based on the image acquired in the image acquisition step and the detection process is repeated until the inspection of the inspection range is completed.
By the time the inspection for the inspection range is completed, the feature amount related to the glossiness of the work surface is calculated using the image acquired by the image acquisition step in parallel with the surface defect detection process by the detection step. Feature calculation steps to be performed and
A program that lets your computer run. The surface defect detected by the detection step is a surface defect of the painted appearance of the automobile, and the feature amount related to the glossiness calculated by the feature amount calculation step is the feature amount of the gloss of the painted appearance of the automobile. The program according to claim 12. In claim 12 or 13, in the feature amount calculation step, the computer is made to execute a process of calculating a feature amount related to glossiness using a single image imaged by the imaging means and acquired by the image acquisition step. Described program. In the feature amount calculation step, a plurality of images captured by the imaging means and acquired by the image acquisition means when the positional relationship between the work and the light / dark pattern of the illumination light is relatively changed are combined. The program according to any one of claims 12 to 14, which causes the computer to execute a process of calculating a feature amount related to glossiness using a composite image. The program according to any one of claims 12 to 15, in which the feature amount calculation step calculates the feature amount of the gloss value from the feature amount related to the calculated glossiness.

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