A detection method and device based on a TDI linear array camera

Abstract

This invention provides a detection method based on a TDI line scan camera, comprising: controlling the TDI line scan camera to capture a first image using a first integration stage; controlling the TDI line scan camera to capture a second image using a second integration stage, wherein the second integration stage is greater than the first integration stage; acquiring high reflectivity regions in the first image and performing feature detection on the high reflectivity regions in the first image; acquiring low reflectivity regions in the second image and performing feature detection on the low reflectivity regions in the second image. This invention also provides a defect detection device based on a TDI line scan camera. This defect detection method and device have low false detection and false negative rates.

Description

Technical Field

[0001] This invention relates to the field of industrial inspection, and in particular to an inspection method and apparatus based on a TDI line scan camera. Background Technology

[0002] In the field of panel AOI (Automated Optical Inspection), the main purpose of AOI inspection equipment is to discover various defects in the panel during the production process (such as particles, dirt, scratches, bumps, dents, short circuits, open circuits, etc.). The main method used is to use multiple scanning CCD probes arranged side by side to scan the entire panel in a stitched manner. Based on the captured images, image processing algorithms are used to analyze the various defects on the panel.

[0003] However, different areas of a panel product at the same stage of the manufacturing process have different reflectivities, which can easily lead to overexposure in high-reflectivity areas or insufficient brightness in low-reflectivity areas. This results in defects in high-reflectivity areas also having high brightness, or non-defective parts in low-reflectivity areas having low brightness, making it impossible to distinguish between defects and non-defective parts by comparing brightness levels, thus increasing the false positive and false negative rates. Summary of the Invention

[0004] To address the above problems, this invention provides a detection method based on a TDI line scan camera, comprising:

[0005] The first image is captured using the TDI linear array camera controlled by the first integral series.

[0006] The second integration stage is used to control the TDI line scan camera to capture a second image, where the second integration stage is greater than the first integration stage;

[0007] Obtain the high reflectivity region in the first image, and perform feature detection on the high reflectivity region in the first image;

[0008] The low reflectivity region in the second image is obtained, and feature detection is performed on the low reflectivity region in the second image.

[0009] In one embodiment, the method further includes:

[0010] A first pixel row group is selected from the pixel rows of the TDI line scan camera, and the number of pixel rows in the first pixel row group is the first integration level;

[0011] The step of using the first integral series to control the TDI line scan camera to capture the first image includes:

[0012] During the scanning of the object being detected, a first image is output based on the signal integration acquired from the first pixel row group.

[0013] In one embodiment, the method further includes:

[0014] A second pixel row group is selected from the pixel rows of the TDI line scan camera, and the number of pixel rows in the second pixel row group is the second integration level;

[0015] The step of using a second integral series to control the TDI line scan camera to capture the second image includes:

[0016] During the scanning of the object being detected, a second image is output based on the signal integration acquired from the second pixel row group.

[0017] In one embodiment, the method further includes:

[0018] The first pixel row group and the second pixel row group are in a non-overlapping relationship, a partially overlapping relationship, or an inclusive relationship.

[0019] In one embodiment, obtaining the high reflectivity region in the first image and / or obtaining the low reflectivity region in the second image comprises:

[0020] High reflectivity regions and / or low reflectivity regions are obtained by identifying markings on the surface of the detected object in the first and / or second images.

[0021] In one embodiment, the method further includes:

[0022] Obtain the grayscale values ​​of the high reflectivity region and the low reflectivity region, and set the first integration level and / or the second integration level based on the grayscale values.

[0023] To address the above problems, the present invention also provides a detection device based on a TDI line scan camera, comprising:

[0024] The image acquisition module is used to control the TDI line scan camera to capture a first image using a first integration stage; and to control the TDI line scan camera to capture a second image using a second integration stage, wherein the second integration stage is greater than the first integration stage.

[0025] The image recognition module is used to acquire high reflectivity regions in the first image and perform feature detection on the high reflectivity regions in the first image; and to acquire low reflectivity regions in the second image and perform feature detection on the low reflectivity regions in the second image.

[0026] In one embodiment, the image acquisition module is further configured to:

[0027] In the pixel rows of the TDI line scan camera, a first pixel row group and a second pixel row group are selected, where the number of pixel rows in the first pixel row group is the first integration level, and the number of pixel rows in the second pixel row group is the second integration level.

[0028] The image acquisition module is also used to output a first image based on the signal integration of the first pixel row group and to output a second image based on the signal integration of the second pixel row group.

[0029] In one embodiment, the image recognition module is used to obtain high reflectivity regions and / or low reflectivity regions by recognizing markings on the surface of the detected object in a first image and / or a second image.

[0030] In one embodiment, the device further includes a level setting module, which is also used to obtain the gray values ​​of the high reflectivity region and the low reflectivity region, and set the first integration level and / or the second integration level according to the gray values.

[0031] Compared with the prior art, the detection method and apparatus based on TDI line scan camera of this application have the following beneficial effects.

[0032] This application's defect detection method based on a TDI line scan camera generates two images of the object being inspected during the inspection process: a first image and a second image. The first image uses a lower TDI integration level, resulting in a shorter exposure time, thus reducing the likelihood of overexposure in high-reflectivity areas. The second image uses a higher TDI integration level, resulting in a longer exposure time, ensuring sufficient exposure and preventing excessive darkness in low-reflectivity areas. Feature detection is then performed on the high-reflectivity areas of the first image, and on the low-reflectivity areas of the second image. This ensures that features such as defects in high-reflectivity areas are not falsely detected or missed due to overexposure, and vice versa, thereby reducing the overall false detection and missed detection rates. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the working principle of a TDI linear array camera.

[0034] Figure 2 This is a schematic diagram of the working principle of a TDI linear array camera.

[0035] Figure 3 This is a schematic diagram of the working principle of a TDI linear array camera.

[0036] Figure 4 This is a flowchart of a detection method based on a TDI line scan camera in one embodiment of this application;

[0037] Figure 5 This is a schematic diagram illustrating the pixel row selection settings for different integration levels of a TDI linear array camera in one embodiment of this application.

[0038] Figure 6 This is a structural diagram of a detection device based on a TDI line scan camera in one embodiment of this application. Detailed Implementation

[0039] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0040] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0041] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0042] To address the aforementioned problems, this invention provides a detection method that can expose high-reflectivity and low-reflectivity regions at different exposure levels and detect features in high-reflectivity and low-reflectivity regions separately, thereby ensuring a low false detection rate and a low false detection rate. This method is based on a TDI line scan camera.

[0043] Compared to conventional line scan cameras, TDI (Time Delayed and Integration) line scan cameras feature high response speed and wide dynamic range. They are particularly suitable for situations involving high-speed object movement and low-light conditions, and can also output signals with a certain signal-to-noise ratio, greatly mitigating the disadvantage of low signal-to-noise ratio caused by harsh environmental conditions.

[0044] The working principle of the TDI line scan camera can be found in [reference]. Figure 1 As shown, the photosensitive device (CCD, charge-coupled element) of the TDI linear array camera used for testing includes multiple rows of pixels. Figure 1 Taking a CCD structure with N pixel rows as an example, in practical applications, TDI line scan cameras typically have more than 256 pixel rows. During the image acquisition process of the object being inspected, the object needs to move along the arrangement direction of the pixel rows of the TDI line scan camera, and there are requirements for the moving speed. The moving speed of the object must be consistent with the line scanning speed of the TDI line scan camera.

[0045] In other words, reference Figure 1 As shown, in the first time interval, the object being detected moves to the right relative to the TDI line scan camera, so that region A of the object being detected enters the scanning area of ​​the first pixel row of the TDI line scan camera. The TDI line scan camera needs to complete the scanning of region A within the first time interval, that is, to acquire the photosensitive data of region A on the first pixel row.

[0046] During the second time interval, the object being detected needs to continue moving to the right, so that region B enters the scanning area of ​​the first pixel row of the TDI line scan camera, and region A enters the scanning area of ​​the second pixel row of the TDI line scan camera. The TDI line scan camera needs to complete the scanning of regions A and B within the second time interval, that is, to acquire the photosensitive data of region B on the first pixel row and acquire the photosensitive data of region A on the second pixel row.

[0047] Similarly, as the object being detected continues to move at this speed, the TDI line scan camera can acquire photosensitive data of region A and data of regions B...H across N pixel rows. Then, by integrating the photosensitive data of region A across the N pixel rows, the image of region A can be obtained.

[0048] I(A) = S1(A) + S2(A) + ... + S N (A)

[0049] Similarly, by integrating the photosensitive data of regions B, C, ..., H, we can obtain the photosensitive data of region AH of the object being tested, and thus obtain an image of the object being tested.

[0050] This ensures that even if the object being detected moves quickly, the time interval of each scan line is short, and the exposure time of the corresponding area of ​​the object being detected is insufficient, it will not affect the exposure level of the final image of the object being detected.

[0051] See again Figure 3 It can be seen that the number of pixel rows in the TDI line scan camera used is the number of light-sensitive data that needs to be integrated. Figure 3For all N pixel rows of a TDI line scan camera, for region A, the N photosensitive data points need to be integrated and summed; however, if only using... Figure 3 For the first 14 pixel rows of a TDI line scan camera, the light-sensitive data of the first 14 pixel rows needs to be integrated and summed for region A. In other words, the number of pixel rows of the TDI line scan camera corresponds to the amount of data to be integrated, and this amount of data is the integration level.

[0052] In this embodiment, a detection method is proposed by utilizing the characteristics of the TDI line scan camera. This detection method can use a smaller integration series to control the TDI line scan camera to scan high reflectivity areas, that is, to use a smaller exposure time when shooting high reflectivity areas, so as not to cause overexposure when shooting high reflectivity areas. The detection method can also use a larger integration series to control the TDI line scan camera to scan low reflectivity areas, that is, to use a larger exposure time when shooting low reflectivity areas, so as not to cause the low reflectivity areas to be too dark when shooting low reflectivity areas.

[0053] For details, please refer to Figure 4 As shown, the method includes:

[0054] Step S102: Use a first integration stage to control the TDI line scan camera to capture a first image; use a second integration stage to control the TDI line scan camera to capture a second image, wherein the second integration stage is greater than the first integration stage.

[0055] Step S104: Obtain high reflectivity regions in the first image and perform feature detection on these regions; obtain low reflectivity regions in the second image and perform feature detection on these regions as well. Feature detection includes detecting features of the object's surface obtained from the image, such as defect detection and linewidth detection.

[0056] In this embodiment, the first image for detecting defects in high reflectivity regions and the second image for detecting defects in low reflectivity regions are captured during the same scan of the object being inspected by the TDI line scan camera.

[0057] Specifically, a first pixel row group and a second pixel row group can be selected from the pixel rows of the TDI line scan camera used in this scan. The number of pixel rows in the first pixel row group is the first integration level, and the number of pixel rows in the second pixel row group is the second integration level.

[0058] During the scanning of the object being detected, a first image is output based on the signal integration of the first pixel row group, and a second image is output based on the signal integration of the second pixel row group.

[0059] refer to Figure 5As shown, in one embodiment, M pixel rows from row 1 to row M can be selected as the first pixel row group, and the first integration level is M; N - M pixel rows from row M + 1 to row N are selected as the second pixel row group, and the second integration level is N - M, and M < N - M. Then, the data of the area A of the detected object in the first image is:

[0060] I1(A) = S1(A) + S2(A) + …… + S M (A)

[0061] The data of the area A of the detected object in the second image is:

[0062] I2(A) = S M+1 (A) + S M+2 (A) + …… + S N (A)

[0063] Since M < N - M, it can be seen that the exposure time of I1(A) is less than that of I2(A), and the number of integration times of I1(A) is also less than that of I2(A). Then, the high - reflectivity region in I1(A) is not likely to be overexposed, and the gray - level difference between the defective and non - defective regions in the high - reflectivity region of the first image will not be too small; and the low - reflectivity region in I2(A) is not likely to be underexposed, and the gray - level difference between the defective and non - defective regions in the low - reflectivity region of the second image will not be too small.

[0064] In this embodiment, the selection of the first pixel row group and the second pixel row group can be a non - overlapping relationship, a partially overlapping relationship, or an inclusion relationship.

[0065] As in the above example, M pixel rows from row 1 to row M can be selected as the first pixel row group, and N - M pixel rows from row M + 1 to row N are selected as the second pixel row group, and the first pixel row group and the second pixel row group are adjacent and non - overlapping; in another embodiment, M pixel rows from row 1 to row M can be selected as the first pixel row group, and N pixel rows from row 1 to row N are selected as the second pixel row group, and the first pixel row group and the second pixel row group are in an inclusion relationship; in another embodiment, M pixel rows from row 1 to row M can be selected as the first pixel row group, and N - 1 pixel rows from row 2 to row N are selected as the second pixel row group, and the first pixel row group and the second pixel row group are in a partially overlapping relationship; in another embodiment, odd - numbered rows from 1 to N (rows 1, 3, 5 …) can be extracted as the first pixel row group, and N pixel rows from row 1 to row N are selected as the second pixel row group, and the first pixel row group and the second pixel row group are in an inclusion relationship. That is to say, as long as the TDI linear array camera supports, the first pixel row group and the second pixel row group can be selected arbitrarily, as long as the number of the second pixel row group is greater than that of the first pixel row group.

[0066] In practical applications, the most common high-end TDI line scan camera currently has a maximum integration level of 256 levels, meaning it has 256 pixel rows. Due to the internal design limitations of the TDI chip, the 256 pixel rows are typically grouped, and the integration level is usually set and adjusted to 64, 128, 192, or 256 levels, with 64 levels as the smallest unit for adjustment.

[0067] In the first practical application, the 256 levels can be split into two parts, such as 64+128 (i.e., the number of the first pixel row group or the first integral level is 64, and the number of the second pixel row group or the second integral level is 128), or 64+192 (i.e., the number of the first pixel row group or the first integral level is 64, and the number of the second pixel row group or the second integral level is 192). Taking the 64+192 level split as an example, the first 64 levels are used for imaging the darker first image, which can highlight the defect features in the high reflectivity areas. The last 192 levels are used for imaging the brighter second image, which can highlight the defect features in the low reflectivity areas.

[0068] The advantage of this approach is that the signal processing for the 64-level and 192-level sections is relatively independent and does not affect each other, simplifying the design of the internal signal processing circuitry of the TDI chip. The disadvantage is that the highest integration level for the second image is only 192 levels, resulting in the loss of 64 integration levels, which may lead to insufficient brightness in the acquired bright image.

[0069] In the second practical application, a 64+256 format can be used (i.e., the number of the first pixel row group or the first integration level is 64, the second pixel row group uses all pixel row groups of TDI, and the maximum integration level of TDI is used). After the first 64 levels output a darker first image, integration continues to 256 levels to output a brighter second image. This method offers more diverse combinations (such as 64+256, 128+256, 64+192, etc.), which can meet more needs for distinguishing between bright and dark images.

[0070] For example, if the image grayscale difference between high-reflectivity and low-reflectivity regions is small, a combination of 128+256 or 192+256 can be used; conversely, a combination of 64+256 or 64+192 can be used. The advantage of this approach, besides the aforementioned flexibility, is that it can essentially utilize the full 256 levels of integration for imaging bright images. However, the disadvantages are twofold: firstly, the correlation between the first and second images complicates the internal signal processing circuitry of the TDI chip; secondly, if the 64-level dark image is output first, the signal in the 64-level pixel row will be temporarily locked and output, and the signal output and conversion require a certain amount of time, during which subsequent integration cannot be performed on the 64-level pixel row.

[0071] In this embodiment, to solve this problem, grayscale values ​​of high reflectivity regions and low reflectivity regions can also be obtained, and a first integration level and / or a second integration level can be set according to the grayscale values.

[0072] For example, the object to be tested can be photographed in advance, and images of high reflectivity areas and low reflectivity areas, as well as the gray values ​​of pixels in the high reflectivity areas and low reflectivity areas in the images, can be obtained. If the gray value of the low reflectivity area is low, it means that the brightness of the low reflectivity area of ​​the object to be tested is dark. For the second image, it may be necessary to use the maximum 256 integration levels. In this case, the 64+256 scheme of the above method two can be selected. If the gray value of the high reflectivity area is also low at this time, the 128+256 scheme can be used on the basis of method two to increase the brightness of the high reflectivity area.

[0073] Correspondingly, if the gray value of the low reflectivity area is high, it means that the low reflectivity area is brighter. For the second image, it may not be necessary to use the maximum 256 integration levels. In this case, the 64+192 scheme of the above method one can be selected. If the gray value of the high reflectivity area is also high at this time, the 64+128 scheme can be used on the basis of method one to prevent overexposure of the high reflectivity area.

[0074] In this embodiment, obtaining high reflectivity regions in the first image and / or low reflectivity regions in the second image is achieved by image recognition of markings on the surface of the detected object in the first and / or second images.

[0075] In industrial inspection processes, high-reflectivity and low-reflectivity areas can be defined empirically for a specific object being inspected. For example, in the field of panel AOI (Automated Optical Inspection), the high-reflectivity and low-reflectivity areas of panels of the same specification are consistent. These areas can be pre-defined and marked on the panel. Marking methods can include printing or coating marker points, or directly using the area outlines on the panel as marker lines. In the first and / or second images, only image recognition algorithms such as edge detection are needed to identify the high-reflectivity areas in the first image and the low-reflectivity areas in the second image.

[0076] In other embodiments, a TDI line scan camera can be used to scan the object in two stages. During the first scan, the TDI line scan camera is configured to use a smaller first integration stage (or a TDI line scan camera with fewer integration stages) to scan the object, capturing a first image of the high-reflectivity region. During the second scan, the TDI line scan camera is configured to use a larger second integration stage (or a TDI line scan camera with more integration stages) to scan the object, capturing a second image of the low-reflectivity region. This method also yields two images of different reflectivity regions, but requires two scans, which is less efficient than the approach in this embodiment.

[0077] To address the aforementioned problems, the present invention also provides a defect detection device based on a TDI line scan camera, such as... Figure 6 As shown, it includes:

[0078] Image acquisition module 102 is used to control a TDI line scan camera to capture a first image using a first integration series; and to control a TDI line scan camera to capture a second image using a second integration series, wherein the second integration series is greater than the first integration series.

[0079] The image recognition module 104 is used to acquire high reflectivity regions in the first image and perform feature detection on the high reflectivity regions in the first image; and to acquire low reflectivity regions in the second image and perform feature detection on the low reflectivity regions in the second image.

[0080] In one embodiment, the image acquisition module 102 is further configured to:

[0081] In the pixel rows of the TDI line scan camera, a first pixel row group and a second pixel row group are selected, where the number of pixel rows in the first pixel row group is the first integration level, and the number of pixel rows in the second pixel row group is the second integration level.

[0082] The image acquisition module 102 is also used to output a first image based on the signal integration of the first pixel row group and to output a second image based on the signal integration of the second pixel row group.

[0083] In one embodiment, the image recognition module 104 is used to obtain high reflectivity regions and / or low reflectivity regions by recognizing markings on the surface of the object being detected in a first image and / or a second image.

[0084] In one embodiment, the device further includes a level setting module 106, which is further configured to acquire the gray values ​​of the high reflectivity region and the low reflectivity region, and set the first integration level and / or the second integration level according to the gray values.

[0085] Compared with the prior art, the detection method and apparatus based on TDI line scan camera of this application have the following beneficial effects.

[0086] This application's detection method based on a TDI line scan camera generates two images of the detected object during the detection process: a first image and a second image. The first image uses a lower TDI integration level, resulting in a shorter exposure time, thus reducing the likelihood of overexposure in high-reflectivity areas. The second image uses a higher TDI integration level, resulting in a longer exposure time, ensuring sufficient exposure and preventing excessive darkness in low-reflectivity areas. Feature detection is then performed on both the high-reflectivity and low-reflectivity areas of the first and second images. This ensures that features in high-reflectivity areas are not falsely detected or missed due to overexposure, and vice versa, thereby reducing the overall false detection and missed detection rates.

[0087] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0088] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A detection method based on a TDI linear scan camera, comprising: The first image is captured using the TDI linear array camera controlled by the first integral series. The second integration stage is used to control the TDI line scan camera to capture a second image, where the second integration stage is greater than the first integration stage; Obtain the high reflectivity region in the first image, and perform feature detection on the high reflectivity region in the first image; The low reflectivity region in the second image is obtained, and feature detection is performed on the low reflectivity region in the second image.

2. The detection method based on a TDI line scan camera according to claim 1, characterized in that, The method further includes: A first pixel row group is selected from the pixel rows of the TDI line scan camera, and the number of pixel rows in the first pixel row group is the first integration level; The step of using the first integral series to control the TDI line scan camera to capture the first image includes: During the scanning of the object being detected, a first image is output based on the signal integration acquired from the first pixel row group.

3. The detection method based on a TDI line scan camera according to claim 2, characterized in that, The method further includes: A second pixel row group is selected from the pixel rows of the TDI line scan camera, and the number of pixel rows in the second pixel row group is the second integration level; The step of using a second integral series to control the TDI line scan camera to capture the second image includes: During the scanning of the object being detected, a second image is output based on the signal integration acquired from the second pixel row group.

4. The detection method based on a TDI linear array camera according to claim 3, characterized in that, The method further includes: The first pixel row group and the second pixel row group are in a non-overlapping relationship, a partially overlapping relationship, or an inclusive relationship.

5. The detection method based on a TDI linear array camera according to claim 1, characterized in that, The high reflectivity region in the first image is obtained as follows: High reflectivity areas are obtained by identifying markings on the surface of the object being detected in the first image; The low reflectance region in the second image is obtained as follows: Low reflectivity areas are obtained by identifying markings on the surface of the object being detected in the second image using image recognition.

6. The detection method based on a TDI linear array camera according to any one of claims 1 to 5, characterized in that, The method further includes: The object to be detected is photographed in advance, and the gray values ​​of the pixels in the high reflectivity area and low reflectivity area of ​​the pre-photographed image are obtained. The first integration level and / or the second integration level are set according to the gray values.

7. A detection device based on a TDI linear scan camera, comprising: The image acquisition module is used to control the TDI line scan camera to capture the first image using the first integration series; The second integration stage is used to control the TDI line scan camera to capture a second image, where the second integration stage is greater than the first integration stage; The image recognition module is used to acquire high reflectivity regions in the first image and perform feature detection on the high reflectivity regions in the first image; and to acquire low reflectivity regions in the second image and perform feature detection on the low reflectivity regions in the second image.

8. The detection device based on a TDI line array camera according to claim 7, characterized in that, The image acquisition module is also used for: A first pixel row group and a second pixel row group are selected from the pixel rows of the TDI line scan camera. The number of pixel rows in the first pixel row group is the first integration level, and the number of pixel rows in the second pixel row group is the second integration level. The image acquisition module is also used to output a first image based on the integration of the signal acquired by the first pixel row group and to output a second image based on the integration of the signal acquired by the second pixel row group.

9. The detection device based on a TDI line array camera according to claim 7, characterized in that, The image recognition module is used to obtain high reflectivity regions by recognizing marks on the surface of the object being detected in the first image, and to obtain low reflectivity regions by recognizing marks on the surface of the object being detected in the second image.

10. The detection device based on a TDI line scan camera according to any one of claims 7 to 9, characterized in that, The detection device further includes a level setting module, which is also used to take a picture of the object to be detected in advance, and obtain the gray values ​​of the pixels in the high reflectivity area and low reflectivity area of ​​the pre-taken image, and set the first integration level and / or the second integration level according to the gray values.

Images