A calibration method, device and storage medium based on screen foreign body detection

Abstract

The present application discloses a calibration method, device, and storage medium based on screen foreign body detection, which is used to improve the calibration effect of the lighting detection camera and the layered camera in the screen foreign body detection. The method comprises the following steps: obtaining a captured image of the calibration screen; extracting the coordinates of the calibration points to generate the position information of the calibration points; moving the calibration screen to the work station of the layered camera via a displacement stage; focusing the layered camera on the pixel layer of the calibration screen, collecting the center calibration point and the positioning calibration point on the calibration screen, and generating a calibration point image; converting the calibration point image into a grayscale image; determining the grayscale threshold, and performing pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image; performing adjacent pixel gap elimination processing on the binary image, and extracting the positioning pixel point coordinates from the binary image based on the feature information of the positioning pixel point to generate the positioning pixel point position information; calculating the position deviation information; and calculating the position calibration matrix.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of display screen foreign object detection, and in particular to a calibration method, device, and storage medium based on screen foreign object detection. Background Art

[0002] With the development of LCD screens, LCD screens have gradually acquired more functionality. The increase in functionality has led to an increase in the number of layers in LCD screens, or improvements to each layer. This makes the structure of LCD screens complex. Existing LCD screens may include multiple components such as CG cover plates, OCA glue, upper polarizers, TFTs, CFs, lower polarizers, and backlights. Therefore, during the production process of LCD screens, due to the complex structure, foreign matter may be generated in many production links. These foreign matter may be generated between any two adjacent layers. However, the impact of these foreign matter on the quality of the final product is inconsistent. For example, foreign matter in the backlight will not have a greater impact than foreign matter in the polarizer. This makes it very important to determine the location and layer position of foreign matter.

[0003] During the production and preparation process, despite strict control at every stage, it is inevitable that foreign matter will mix between two layers, resulting in screens with foreign matter defects. Therefore, foreign matter defect detection has become an indispensable step in the LCD screen production process. Traditional AOI spot inspection uses a camera aligned with the pixel layer of the LCD screen to capture an image of the entire LCD screen with preset pixels. In the image obtained in this way, foreign matter between two adjacent layers cannot be accurately distinguished, and foreign matter on the upper and lower sides of the pixel layer cannot be accurately detected. Therefore, the inspection performed by the above-mentioned captured images can only be controlled according to the same standard to detect foreign matter. Some foreign matter that has little impact on the quality of the LCD screen will also be screened according to high standards, resulting in huge waste.

[0004] In order to reduce losses and improve product utilization. After the lighting inspection is completed, a defect layering inspection can be added to accurately distinguish the location of foreign objects. The layering inspection uses a 25M camera with a depth of field of 75um to move to the top of the foreign object. By adjusting the height of the layering camera, the clearest position of the defect is obtained and the layer of the defect is calculated. In order for the layering camera to be accurately moved to the top of the foreign object defect, the lighting inspection camera and the layering camera need to be calibrated to calculate the positional relationship between each other. However, with the continuous updating and improvement of LCD screens, the functionality of LCD screens has been continuously developed, and structures such as internal circuits of the display screen have been added. The degree of bending and folding of the display screen has also been upgraded. These have made the LCD screen structure gradually more complex. Traditional camera calibration methods are easily affected by these structures, which affects the point positioning process of the two cameras during calibration, thereby reducing the calibration effect of the lighting inspection camera and the layering camera in the screen foreign object detection. Summary of the Invention

[0005] The present application discloses a calibration method, device and storage medium based on screen foreign body detection, which are used to improve the calibration effect of lighting detection cameras and layered cameras in screen foreign body detection.

[0006] The first aspect of the present application proposes a calibration method based on screen foreign body detection, comprising:

[0007] Input the calibration image to the calibration screen at the center of the stage, use the light detection camera to shoot, and obtain the calibration screen image. There is a center calibration point and several positioning calibration points on the calibration image. The center calibration point is provided with a cross mark area with a different grayscale from the center calibration point. The positioning calibration point is provided with a cross mark area with a different grayscale from the positioning calibration point. A positioning pixel point is set in the center of the cross mark area. The center calibration point is located at the center of the calibration image. There are center calibration points and positioning calibration points at the corresponding positions of the calibration screen image.

[0008] Extract the coordinates of the calibration points from the image captured by the calibration screen according to the preset calibration point feature information, and generate the calibration point position information, which includes the feature information of the center calibration point and the feature information of the positioning calibration point;

[0009] The calibration screen is moved to the workstation of the layered camera by a displacement stage. The layered camera is a color camera.

[0010] Focus the layered camera on the pixel layer of the calibration screen according to the layer information of the calibration screen. According to the position information of the calibration points, the layered camera is used to collect the center calibration point and the positioning calibration point on the calibration screen to generate a calibration point image.

[0011] Convert the calibration point image into a grayscale image;

[0012] Determine the grayscale threshold, and use the grayscale threshold to filter the pixels in the calibration point area of ​​the grayscale image to generate a binary image;

[0013] Performing adjacent pixel gap elimination processing on the binary image, and extracting the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the position information of the positioning pixel points;

[0014] Calculate the position deviation information based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image;

[0015] The position calibration matrix of the lighting detection camera and the layered camera is calculated through the calibration point position information, positioning pixel position information and position deviation information.

[0016] Optionally, extracting the coordinates of the calibration points from the image captured by the calibration screen according to the preset calibration point feature information to generate the calibration point position information includes:

[0017] Binarize the image captured by the calibration screen and remove the cross mark on the image captured by the calibration screen through morphological dilation;

[0018] Filtering all calibration point sets based on the calibration point feature information of each block on the image captured by the calibration screen, where the calibration point feature information includes true roundness information and area information;

[0019] Sort the row and column coordinates of the 9 calibration points in the order of row first and column later to generate the calibration point position information.

[0020] Optionally, the calibration screen is a display screen provided with a circuit area, and the calibration point feature information further includes circuit structure information;

[0021] The calibration point feature information of each block on the calibration screen image is filtered to obtain all calibration point sets, including:

[0022] Marking the circuit area on the image captured by the calibration screen according to the circuit distribution data in the circuit structure information;

[0023] determining an interference area in a circuit area according to circuit reflection data and circuit morphology data in the circuit structure information;

[0024] Determine a set of pre-screened calibration points that meet the calibration points in each block on the image captured by the calibration screen according to the true roundness information and the area information;

[0025] The circuit area interference is filtered out from the initial screening calibration point set through the interference area, and the calibration point set that meets the requirements is selected.

[0026] Optionally, determining a grayscale threshold, and performing pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image includes:

[0027] When a calibration point is located on the circuit area, channel data is selected from the RGB channel information of the grayscale image according to the circuit reflection data in the circuit structure information;

[0028] Generate grayscale threshold according to the selected channel pixel data;

[0029] The grayscale image is filtered by grayscale threshold to generate a binary image.

[0030] Optionally, after converting the calibration point image into a grayscale image, determining a grayscale threshold, and performing pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold before generating a binary image, the calibration method further includes:

[0031] Acquire several light reflection images of the calibration screen collected under spherical integral light sources of different brightness;

[0032] Detecting the brightness information of the display screen in the non-circuit area with the calibration image input by using a luminance meter;

[0033] determining a corresponding target light reflection image from a plurality of light reflection images according to brightness information;

[0034] Determine the calibration point to be adjusted located in the circuit area;

[0035] Determine the reflection area corresponding to the calibration point to be adjusted on the target light reflection image;

[0036] The circuit interference elimination process is performed on the grayscale value of the corresponding area of ​​the grayscale image according to the grayscale mean value of the reflection area.

[0037] Optionally, performing adjacent pixel gap elimination processing on the binary image, and extracting the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the positioning pixel point position information, including:

[0038] Performing morphological dilation processing on the pixels of the calibration point area in the binary image, connecting the pixels of the calibration point area to form a pixel whole, the calibration point area includes the central calibration point area and the positioning calibration point area;

[0039] The coordinate position of the positioning pixel point is extracted from the binary image after morphological expansion according to the feature information of the positioning pixel point, and the position information of the positioning pixel point is generated.

[0040] The second aspect of the present application provides a calibration device based on screen foreign body detection, comprising:

[0041] The first acquisition unit is used to input a calibration image to the calibration screen at the center of the stage, use the light detection camera to shoot, and obtain the calibration screen shot image, wherein a center calibration point and several positioning calibration points are set on the calibration image, a cross mark area with a grayscale different from that of the center calibration point is set on the center calibration point, and a cross mark area with a grayscale different from that of the positioning calibration point is set on the positioning calibration point. A positioning pixel point is set at the exact center of the cross mark area, and the center calibration point is located at the center of the calibration image. There are a center calibration point and a positioning calibration point at the corresponding positions of the calibration screen shot image;

[0042] A first generating unit is configured to extract calibration point coordinates from the image captured by the calibration screen according to preset calibration point feature information, and generate calibration point position information, wherein the calibration point information includes feature information of a central calibration point and feature information of a positioning calibration point;

[0043] A displacement unit is used to move the calibration screen to the working position of the layered camera through a displacement stage, and the layered camera is a color camera;

[0044] The second generating unit is used to focus the layered camera to the pixel layer of the calibration screen according to the layer information of the calibration screen, and collect the central calibration point and the positioning calibration point on the calibration screen through the layered camera according to the calibration point position information to generate a calibration point image;

[0045] A conversion unit, configured to convert the calibration point image into a grayscale image;

[0046] A first determining unit is used to determine a grayscale threshold, and perform pixel point screening processing on the calibration point area of ​​the grayscale image according to the grayscale threshold to generate a binary image;

[0047] The third generating unit is used to perform adjacent pixel gap elimination processing on the binary image, and extract the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the position information of the positioning pixel points;

[0048] A first calculation unit is used to calculate position deviation information based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image;

[0049] The second calculation unit is used to calculate the position calibration matrix of the lighting detection camera and the layered camera through the calibration point position information, the positioning pixel position information and the position deviation information.

[0050] Optionally, the first generating unit includes:

[0051] A processing module is used to perform binarization processing on the calibration screen image and remove the cross mark on the calibration screen image through morphological expansion;

[0052] A screening module is used to screen out all calibration point sets based on the calibration point feature information of each block on the image captured by the calibration screen, where the calibration point feature information includes true roundness information and area information;

[0053] The generation module is used to sort the row and column coordinates of the 9 calibration points in the order of row first and column later to generate the calibration point position information.

[0054] Optionally, the calibration screen is a display screen provided with a circuit area, and the calibration point feature information further includes circuit structure information;

[0055] Screening modules, including:

[0056] Marking the circuit area on the image captured by the calibration screen according to the circuit distribution data in the circuit structure information;

[0057] determining an interference area in a circuit area according to circuit reflection data and circuit morphology data in the circuit structure information;

[0058] Determine a set of pre-screened calibration points that meet the calibration points in each block on the image captured by the calibration screen according to the true roundness information and the area information;

[0059] The circuit area interference is filtered out from the initial screening calibration point set through the interference area, and the calibration point set that meets the requirements is selected.

[0060] Optionally, the first determining unit includes:

[0061] When a calibration point is located on the circuit area, channel data is selected from the RGB channel information of the grayscale image according to the circuit reflection data in the circuit structure information;

[0062] Generate grayscale threshold according to the selected channel pixel data;

[0063] The grayscale image is filtered by grayscale threshold to generate a binary image.

[0064] Optionally, after the conversion unit and before the first determination unit, the calibration device further includes:

[0065] A first acquisition unit is used to acquire a plurality of light reflection images collected by the calibration screen under spherical integral light sources of different brightness;

[0066] A detection unit, configured to detect brightness information of a display screen in a non-circuit area after inputting a calibration image using a luminance meter;

[0067] a second determining unit, configured to determine a corresponding target light reflection image from the plurality of light reflection images according to the brightness information;

[0068] A third determining unit is used to determine a calibration point to be adjusted located in the circuit area;

[0069] A fourth determining unit, configured to determine a reflection area corresponding to the calibration point to be adjusted on the target light reflection image;

[0070] The elimination unit is used to perform circuit interference elimination processing on the grayscale value of the corresponding area of ​​the grayscale image according to the grayscale mean value of the reflection area.

[0071] Optionally, the third generating unit includes:

[0072] Performing morphological dilation processing on the pixels of the calibration point area in the binary image, connecting the pixels of the calibration point area to form a pixel whole, the calibration point area includes the central calibration point area and the positioning calibration point area;

[0073] The coordinate position of the positioning pixel point is extracted from the binary image after morphological expansion according to the feature information of the positioning pixel point, and the position information of the positioning pixel point is generated.

[0074] A third aspect of the present application provides a calibration device based on screen foreign body detection, comprising:

[0075] processor, memory, input and output units, and buses;

[0076] The processor is connected to the memory, input and output units, and the bus;

[0077] The memory stores a program, and the processor calls the program to execute the first aspect and any optional calibration method of the first aspect.

[0078] In a fourth aspect, the present application provides a computer-readable storage medium on which a program is stored. When the program is executed on a computer, the program executes the first aspect and any optional calibration method of the first aspect.

[0079] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0080] In this application, a calibration image is first input to the calibration screen at the center of the stage, and then captured using a lighting detection camera to obtain a captured image of the calibration screen. The pre-set calibration image is configured with one center calibration point and several positioning calibration points. Each center calibration point is provided with a cross mark area with a grayscale different from that of the center calibration point, and each positioning calibration point is provided with a cross mark area with a grayscale different from that of the positioning calibration point. A positioning pixel is located at the exact center of the cross mark area. The center calibration point is located at the center of the calibration image, and the captured captured image of the calibration screen has the center calibration point and positioning calibration points at corresponding positions. In this case, each block on the captured image of the calibration screen has at least one calibration point. Then, based on the preset calibration point feature information, the calibration point coordinates are extracted from the captured image of the calibration screen to generate calibration point position information. The calibration point information includes the feature information of the center calibration point and the feature information of the positioning calibration points. This calibration point position information is determined with reference to the lighting detection camera. Next, the calibration screen is moved to the workstation of the layered camera using the displacement stage. Among them, the layered camera is a color camera. The area captured by the layered camera is limited, but it can capture clearer images. First, the layered camera is focused on the pixel layer of the calibration screen according to the layer information of the calibration screen. After alignment, the center calibration point and the positioning calibration point on the calibration screen are collected through the layered camera according to the calibration point position information to generate a calibration point image. At this time, the shooting is performed with the layered camera as the reference system. The calibration point image is converted into a grayscale image so that the difference between the calibration points in the entire shooting area is highlighted. Next, the grayscale threshold for distinguishing the calibration point area, the cross mark area and the positioning pixel point is determined. The grayscale threshold is used to filter the pixels in the calibration point area of ​​the grayscale image to generate a binary image. At this time, because the layered camera focuses on the pixel layer and highlights the gaps between the pixels, it is necessary to eliminate the gaps between adjacent pixels on the binary image, and extract the positioning pixel coordinates from the binary image according to the feature information of the positioning pixel point to generate the positioning pixel position information. Finally, the position deviation information is calculated based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image. After obtaining the position deviation, the position calibration matrix of the lighting detection camera and the layered camera can be calculated using the calibration point position information, positioning pixel position information, and position deviation information.

[0081] First, the lighting inspection camera captures an image for calibration at the workstation. Then, at the layered camera's workstation, the layered camera focuses on the pixel layer to capture images of each calibration point. Image conversion, pixel filtering within the calibration point, and gap elimination between adjacent pixels are performed to determine the position information of the positioning pixel points. Deviation calculation is then performed based on the center coordinate position of the layered camera to further reduce errors. Finally, a position calibration matrix is ​​generated using the calibration point positions and deviations determined in the two images. This position calibration matrix can be used as the positional relationship data for the current layered camera and lighting inspection camera, improving the calibration effect of the lighting inspection camera and layered camera for screen foreign body detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0083] Figure 1 This is a schematic diagram of an embodiment of a calibration method based on screen foreign body detection in this application;

[0084] Figure 2 A schematic diagram of an embodiment of a method for generating calibration point position information according to the present application;

[0085] Figure 3 A schematic diagram of an embodiment of a method for screening a set of calibration points in this application;

[0086] Figure 4 A schematic diagram of an embodiment of a method for screening pixels in the present application;

[0087] Figure 5 A schematic diagram of an embodiment of a method for eliminating circuit area interference according to the present application;

[0088] Figure 6 A schematic diagram of an embodiment of a method for generating location pixel position information according to the present application;

[0089] Figure 7 This is a schematic diagram of an embodiment of a calibration device based on screen foreign body detection in this application;

[0090] Figure 8 This is a schematic diagram of another embodiment of a calibration device based on screen foreign matter detection in the present application;

[0091] Figure 9 A structural diagram of the machine of this application;

[0092] Figure 10 A schematic diagram of calibrating images for this application;

[0093] Figure 11 A schematic diagram of an image captured for the calibration screen of this application;

[0094] Figure 12 This is a schematic diagram of a binary image after feature quantity screening processing in this application;

[0095] Figure 13 A schematic diagram of the calibration point images of the 9 calibration points in this application. DETAILED DESCRIPTION

[0096] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0097] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0098] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0099] As used in this specification and the appended claims, the term "if" can be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0100] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0101] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0102] In the existing technology, in order to reduce losses and improve product utilization. After the lighting inspection is completed, a defect layering inspection can be added to accurately distinguish the location of the foreign matter. The layering inspection uses a 25M camera with a depth of field of 75um to move to the top of the foreign matter. By adjusting the height of the layering camera, the clearest position of the defect is obtained and the layer of the defect is calculated. In order for the layering camera to be accurately moved to the top of the foreign matter defect, the lighting inspection camera and the layering camera need to calculate the positional relationship between each other through calibration. However, with the continuous updating and improvement of LCD screens, the functionality of LCD screens has been continuously developed, and structures such as the internal circuit of the display screen have been added. The degree of bending and folding of the display screen has also been upgraded. These have made the LCD screen structure gradually more complex. The traditional camera calibration method is easily affected by these structures, which affects the point positioning process of the two cameras during calibration, thereby reducing the calibration effect of the lighting inspection camera and the layering camera in the detection of foreign objects on the screen.

[0103] Based on this, the present application discloses a calibration method, device and storage medium based on screen foreign body detection, which are used to improve the calibration effect of lighting detection cameras and layered cameras in screen foreign body detection.

[0104] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0105] The method of the present application can be applied to a server, device, terminal or other device with logic processing capability, and the present application does not limit this. For the convenience of description, the following description is based on the example of the execution subject being a terminal.

[0106] See also Figure 1 The present application provides an embodiment of a calibration method based on screen foreign body detection, comprising:

[0107] 101. Input a calibration image to the calibration screen at the center of the stage, and use the light detection camera to shoot to obtain the calibration screen image. The calibration image is provided with one center calibration point and several positioning calibration points. The center calibration point is provided with a cross mark area with a different grayscale from the center calibration point. The positioning calibration point is provided with a cross mark area with a different grayscale from the positioning calibration point. A positioning pixel point is provided at the exact center of the cross mark area. The center calibration point is located at the center of the calibration image. The center calibration point and the positioning calibration point are located at the corresponding positions of the calibration screen image.

[0108] In this embodiment, the core is to calculate the position relationship matrix between the lighting detection camera (AOI camera, shooting parameters are 151M) and the layered camera (shooting parameters are 25M). The lighting detection camera is fixed in position, while the layered camera can be moved from the origin to any position within a specified range. The current calculation method uses an algorithm to extract the row and column coordinates of the nine points of the lighting detection camera. The layered camera is then moved to the corresponding calibration points manually or by machine, and the physical distance is recorded. The coordinates of the nine calibration points (center calibration point and positioning calibration point) are matched one by one to calculate the relationship matrix. For a typical LCD screen, this calibration process takes about an hour, which is very unfriendly to on-site production. To improve efficiency, this embodiment provides an automatic calibration method that can complete calibration in a few minutes, greatly improving work efficiency.

[0109] Please refer to Figure 9 , Figure 9 The machine schematic is shown below. The lighting inspection camera (151M) and the delamination camera (25M) are located on either side of the machine. A turntable rotates the LCD screen from the 151M camera station to the 25M camera station. The 151M station only needs to capture all calibration points (center and positioning) in a single image. However, the 25M camera has a narrow field of view and can only capture each point individually. Therefore, we considered the possibility of knowing the physical coordinates of one of the calibration points at the 25M camera station in advance. Based on the positional relationships between these points, we could determine the physical coordinates of the remaining points.

[0110] In the actual production process, the size and resolution of the LCD screens of different models are constantly changing, and in order to ensure that the 25M camera can be moved above each calibration point. Taking the above factors into consideration, this embodiment uses a special displacement stage. This displacement stage is rectangular in shape, with scales on both horizontal and vertical sides of the displacement stage, and high scales are distributed along the center scale 0 to both sides. At the same time, taking into account the different sizes of LCD screens, the displacement stage can be flexibly adjusted up and down and left and right to ensure that the LCD screen can be within the range of activity of the 25M camera. After testing, it was found that when the intersection B of the line connecting the horizontal and vertical directions along the 0 scale is used as the center of the LCD screen, all models can remain within the range of activity of the camera, and the distance from the intersection B to the camera origin remains unchanged. Please refer to Figure 10 , Figure 10 Figure 1 is a schematic diagram of a calibration image. Therefore, this embodiment ensures that point A (the center calibration point) in the middle of the nine calibration points coincides with intersection point B. The physical coordinates of the nine points are ultimately obtained by reversely calculating their distances from the camera origin based on the positional relationship between the eight surrounding points (positioning calibration points) and point A (the center calibration point of the calibration image).

[0111] Among them, a cross mark area with a different grayscale from the center calibration point is set on the center calibration point, and a cross mark area with a different grayscale from the positioning calibration point is set on the positioning calibration point. The cross mark area is used to detect the position of the calibration point on the calibration screen image, so the cross mark area uses a grayscale different from the calibration point. A positioning pixel point is set in the center of the cross mark area. The positioning pixel point is difficult to display in the calibration screen image, but can be clearly displayed under the layered camera. The positioning pixel point is used to locate the center position of the calibration point in the image taken by the layered camera. There are 1 center calibration point and several positioning calibration points on the calibration image. When displayed on the calibration screen, 1 center calibration point and several positioning calibration points are also displayed on the calibration screen. After the lighting detection camera is used to shoot, the generated calibration screen image will also have a center calibration point and a positioning calibration point at the corresponding position.

[0112] It should be noted that the morphological structures of the center calibration point and the positioning calibration point are usually set to the same. The center calibration point needs to calibrate the image center, while the positioning calibration point is set according to the needs of the researcher.

[0113] 102. Extract the coordinates of the calibration points from the image captured by the calibration screen according to the preset calibration point feature information to generate calibration point position information, where the calibration point information includes feature information of the center calibration point and feature information of the positioning calibration point;

[0114] In this embodiment, it is necessary to extract the calibration point coordinates (calibration point position information) from the calibration screen image captured by the light detection camera. Specifically, the terminal first inputs the calibration image to the calibration screen at the center of the stage, uses the light detection camera to capture it, and obtains the calibration screen image. Then, the calibration point coordinates are extracted based on the calibration point feature information in the calibration screen image to generate the calibration point position information. Finally, the row and column coordinates {Rowi, Coli} of the calibration point under the light detection camera are obtained, where i = {0-8}, and then the coordinates are passed to the layered camera.

[0115] The feature information of the calibration points includes information of the calibration points such as area and roundness. Please refer to the subsequent embodiments for detailed calibration methods.

[0116] Specifically, the calibration screen capture image can cover all 9 calibration points, please refer to Figure 11 , Figure 11 This is a schematic diagram of an image captured by the calibration screen. The dot pattern (calibration image) used in this embodiment has clear contrast and little background interference. Calibration points can be extracted through binarization. However, in order to facilitate the layered camera to obtain the center coordinates of the calibration points, a cross mark area is created on each calibration point. Please refer to Figure 12 , Figure 12 It is a binary image after feature filtering.

[0117] There is a difference in grayscale between the cross mark area and the calibration point. Therefore, the cross mark area should be removed from the binary area obtained in the calibration screen image through morphological dilation to make the calibration point a complete circle. Then, all calibration points are filtered out by feature quantity, and the row and column coordinates {Rowi,Coli} of the calibration points under the lighting detection camera are obtained, where i = {0-8}. The coordinates are then passed to the layered camera.

[0118] 103. Move the calibration screen to the station of the layered camera by using the displacement stage. The layered camera is a color camera.

[0119] After obtaining the calibration point position information in the calibration screen detection image, the calibration screen needs to be moved to the position of the layered camera through the displacement stage so that the layered camera can take pictures. The layered camera in this embodiment is a color camera.

[0120] 104. Focusing the layered camera on the pixel layer of the calibration screen according to the layer information of the calibration screen, collecting the center calibration point and the positioning calibration point on the calibration screen through the layered camera according to the calibration point position information, and generating a calibration point image;

[0121] The terminal first focuses the layered camera on the pixel layer of the calibration screen according to the hierarchical information of the calibration screen, and collects each calibration point on the calibration screen through the layered camera and according to the calibration point position information to generate a calibration point image.

[0122] As mentioned above, after the LCD screen rotates to the position of the layered camera, the layered camera first moves to the intersection of the line connecting the zero scale of the stage (i.e., the center of the stage). At this time, the center point of the calibration image is also located here. In this embodiment, the calibration image is burned into each model through PG. Although the resolution of different models is different, when making the calibration map, it is arranged in proportion to the screen size. Therefore, the center position and the eight surrounding points can be multiplied by the length and width according to the ratio to calculate the physical coordinates of the remaining points. The camera is controlled to move to the corresponding position to take pictures, and finally the image of the nine calibration points is obtained. Please refer to Figure 13 , Figure 13 Schematic diagram of the calibration point image of 9 calibration points.

[0123] As can be seen in the figure, the layered camera, due to its limited field of view, cannot capture all calibration points, or even the entire calibration point. To create the calibration points, a cross mark area is designed, and a small positioning pixel, the size of a single display pixel, is placed in the exact center. This allows the center position {Xi, Yi} of each calibration point (calibration point in the calibration image) to be calculated from the center point (the positioning pixel), where i = {0-8}. In this embodiment, due to the limited depth of field, the layered camera needs to be uniformly focused on the pixel layer to clearly capture the calibration points, thereby also clearly displaying the sub-pixels of the LCD screen.

[0124] 105. Convert the calibration point image into a grayscale image;

[0125] 106. Determine a grayscale threshold, and perform pixel screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image;

[0126] 107. Performing adjacent pixel gap elimination processing on the binary image, and extracting the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the position information of the positioning pixel points;

[0127] 108. Calculate position deviation information based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image;

[0128] In this embodiment, the terminal performs image processing according to the following steps to obtain the center coordinates (the position of the positioning pixel point) of each calibration point (the center calibration point and the positioning calibration point).

[0129] First, the calibration point image is converted to a grayscale image (because the 25M layered camera is a color camera). Next, a grayscale threshold is determined based on the calibration point area and the cross mark area. The grayscale threshold is then used to filter the pixels in the calibration point area of ​​the grayscale image to generate a binary image. Because the LCD screen's pixel grid is magnified approximately 150 times when the layered camera focuses on the pixel layer, the gaps between all pixels are also visible. The binary image is composed of many independent pixels. To distinguish the central positioning pixel, the binary image is dilated to connect the pixels around the center point (the pixels in the calibration area) into a whole. The grayscale of the cross mark area differs significantly from the grayscale of the positioning pixel. Typically, the grayscale value of the positioning pixel is set to be close to that of the calibration area.

[0130] The terminal will perform adjacent pixel gap elimination processing on the binary image, and extract the coordinates of the positioning pixel points from the binary image based on the feature information of the positioning pixel points to generate the positioning pixel point position information.

[0131] The calculated center coordinates (positioning pixel coordinates) are subtracted from the center coordinates (half width, half height) of the corresponding calibration point image (25M image) to calculate the position deviation of the calibration point from the center of the camera field of view. However, this coordinate difference is a pixel difference, which needs to be divided by the magnification factor of each pixel and then multiplied by the physical size of a single pixel to obtain the physical coordinate deviation of the calibration point {ΔXi, ΔYi}, where i = {0-8}.

[0132] 109. Calculate the position calibration matrix of the lighting detection camera and the layered camera through the calibration point position information, the positioning pixel position information and the position deviation information.

[0133] Finally, the terminal calculates the position calibration matrix of the lighting detection camera and the layered camera through the calibration point position information, positioning pixel position information and position deviation information.

[0134] Add {Xi, Yi} (i={0-8}) and {ΔXi, ΔYi} (i={0-8}) to obtain the physical coordinates of the nine calibration points at the layered camera station {Xi+ΔX, Yi+ΔYi} (i={0-8}). Because the theoretical coordinates of the calibration points are calculated, their order is known and can be adjusted at will. In this embodiment, the coordinate order is ensured to be consistent with that of 151M. In this way, the row and column coordinates {Rowi, Coli} (i={0-8}) of the calibration points obtained by the 151M camera and their physical coordinates {Xi+ΔX, Yi+ΔYi} (i={0-8}) correspond one to one. Then, the position relationship matrix R between the two cameras is calculated according to the following formula to complete all the work of automatic point calibration.

[0135]

[0136] Among them, the formula are the parameters in {Xi,Yi} (i={0-8}), are the parameters in {ΔXi,ΔYi} (i={0-8}), are the parameters in {Rowi,Coli} (i={0-8}) respectively.

[0137] In this embodiment, a calibration image is first input to the calibration screen at the center of the stage. The calibration screen is then captured using a lighting detection camera to obtain a captured image of the calibration screen. The pre-set calibration image is configured with one center calibration point and several positioning calibration points. Each center calibration point is assigned a cross mark region with a grayscale different from that of the center calibration point. Each positioning calibration point is assigned a cross mark region with a grayscale different from that of the positioning calibration point. A positioning pixel is positioned directly in the center of the cross mark region. The center calibration point is located at the center of the calibration image. The captured captured image of the calibration screen contains both the center calibration point and the positioning calibration point at corresponding locations. At this point, each area of ​​the captured image of the calibration screen has at least one calibration point. Calibration point coordinates are then extracted from the captured image of the calibration screen based on pre-set calibration point feature information to generate calibration point location information. This calibration point information includes feature information for the center calibration point and feature information for the positioning calibration points. This calibration point location information is determined using the lighting detection camera as a reference. Next, the calibration screen is moved to the workstation of the layered camera using the displacement stage. Among them, the layered camera is a color camera. The area captured by the layered camera is limited, but it can capture clearer images. First, the layered camera is focused on the pixel layer of the calibration screen according to the layer information of the calibration screen. After alignment, the center calibration point and the positioning calibration point on the calibration screen are collected through the layered camera according to the calibration point position information to generate a calibration point image. At this time, the shooting is performed with the layered camera as the reference system. The calibration point image is converted into a grayscale image so that the difference between the calibration points in the entire shooting area is highlighted. Next, the grayscale threshold for distinguishing the calibration point area, the cross mark area and the positioning pixel point is determined. The grayscale threshold is used to filter the pixels in the calibration point area of ​​the grayscale image to generate a binary image. At this time, because the layered camera focuses on the pixel layer and highlights the gaps between the pixels, it is necessary to eliminate the gaps between adjacent pixels on the binary image, and extract the positioning pixel coordinates from the binary image according to the feature information of the positioning pixel point to generate the positioning pixel position information. Finally, the position deviation information is calculated based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image. After obtaining the position deviation, the position calibration matrix of the lighting detection camera and the layered camera can be calculated using the calibration point position information, positioning pixel position information, and position deviation information.

[0138] First, the lighting inspection camera captures an image for calibration at the workstation. Then, at the layered camera's workstation, the layered camera focuses on the pixel layer to capture images of each calibration point. Image conversion, pixel filtering within the calibration point, and gap elimination between adjacent pixels are performed to determine the position information of the positioning pixel points. Deviation calculation is then performed based on the center coordinate position of the layered camera to further reduce errors. Finally, a position calibration matrix is ​​generated using the calibration point positions and deviations determined in the two images. This position calibration matrix can be used as the positional relationship data for the current layered camera and lighting inspection camera, improving the calibration effect of the lighting inspection camera and layered camera for screen foreign body detection.

[0139] See also Figure 2 The present application provides an embodiment of a method for generating calibration point position information, comprising:

[0140] 201. Binarize the image captured by the calibration screen and remove the cross mark on the image captured by the calibration screen by morphological dilation.

[0141] 202. Filter out all calibration point sets based on calibration point feature information of each block on the image captured by the calibration screen, where the calibration point feature information includes roundness information and area information;

[0142] 203. Sort the row and column coordinates of the 9 calibration points in the order of row first and column later to generate calibration point position information.

[0143] In this embodiment, the image is first binarized to remove a large amount of background. Because the grayscale of the cross mark area and the calibration points differ, the binarized area obtained from the calibration screen image is morphologically dilated to remove the cross mark area, transforming the calibration points into a complete circle. All calibration points are then filtered using feature values ​​(such as area and true circularity).

[0144] If the LCD screen does not have a circuit area, you can directly analyze which part matches the calibration point by analyzing the area size and roundness of the binarized block. Only after the corresponding area is analyzed can the point calculation be performed.

[0145] Finally, the row and column coordinates of the 9 calibration points are sorted in the order of row first and column later, and the row and column coordinates {Rowi, Coli} of the calibration points under the light detection camera are finally obtained, where i = {0-8}, and then the coordinates are passed to the layered camera.

[0146] See also Figure 3 The present application provides an embodiment of a method for screening a set of calibration points, comprising:

[0147] 301. Marking a circuit area on the calibration screen captured image according to the circuit distribution data in the circuit structure information;

[0148] 302. Determine an interference area in the circuit area based on circuit reflection data and circuit morphology data in the circuit structure information;

[0149] 303. Determine a set of pre-screened calibration points that meet the calibration points in each block on the image captured by the calibration screen according to the true roundness information and the area information;

[0150] 304. Filter out circuit area interference from the initial screening calibration point set through the interference area, and select a calibration point set that meets the requirements.

[0151] When using a lighting detection camera to capture images, if the LCD screen contains internal display circuitry (internal circuitry is typically very thin, but the presence of composite circuitry increases thickness, making it more reflective), and the calibration point is located within the internal circuit area, reflection deviation may occur when the calibration image is displayed on the calibration screen. This is because when the internal circuit structure is complex, some internal circuitry reflects the light generated when the pixel layer is illuminated. The calibration screen image captured by the lighting detection camera may have grayscale deviations, especially around the calibration point. In this case, there may be false calibration point areas caused by internal circuit reflections, requiring specific circuit interference processing for this circuit area.

[0152] First, the terminal marks the circuit area on the image captured by the calibration screen according to the circuit distribution data in the circuit structure information, then calculates the grayscale value of the calibration point in the calibration image, and then determines the interference area in the circuit area according to the circuit reflection data and circuit morphology data in the circuit structure information. The circuit reflection data refers to the degree to which the material and thickness used in a certain part of the circuit area can reflect the light source. The reflected part can interfere with the display effect of a specific area on the LCD screen. In this embodiment, it is necessary to screen the circuit area that can cause interference, and then analyze it according to the circuit morphology data. If the circuit area in the interfering circuit area is small or very narrow, the reflection effect it brings can be ignored. However, if there is an area with a circular or circular shape, that is, an area similar to the shape of the calibration point, it is determined to be an interference area.

[0153] The terminal determines a preliminary set of calibration points that meet the calibration requirements for each block in the image captured by the calibration screen based on the true roundness and area information. It then filters out circuit area interference from the initial set of calibration points using the interference area, ultimately selecting a set of calibration points that meet the requirements.

[0154] It should be noted that, in addition to screening, if the interference area and the initial screening calibration point set coincide with each other, after the true roundness and area detection, the true calibration point area is missing due to the filtering of the interference area and cannot be detected. In this case, it is necessary to adjust the calibration point position of this block and re-test.

[0155] See also Figure 4 , the present application provides an embodiment of a method for screening pixels, comprising:

[0156] 401. When a calibration point is located on the circuit area, select channel data from the RGB channel information of the grayscale image according to the circuit reflection data in the circuit structure information;

[0157] 402. Generate a grayscale threshold according to the pixel data of the selected channel;

[0158] 403. Perform pixel screening processing on the grayscale image using a grayscale threshold to generate a binary image.

[0159] In this embodiment, the layered camera's narrow depth of field allows for fairly clear pixel representation within the pixel layer. This makes the grayscale between the calibration point area and the cross mark area more susceptible to internal circuitry influences. In the calibration screen image captured by the lighting inspection camera, the grayscale is affected by the Class A circuit area (highly reflective). However, when the calibration point overlaps with the Class B circuit area (with moderate reflectivity), the grayscale between the calibration point area and the cross mark area in the calibration point image captured by the layered camera with its narrow depth of field is more susceptible to the Class B circuit area.

[0160] When the terminal converts the calibration point image into a grayscale image, the grayscale values ​​of the RGB channels in the grayscale image vary significantly. This requires analyzing which calibration points overlap with the Class B circuit area. Channel data is selected from the RGB channel information of the grayscale image based on the circuit reflection data in the circuit structure information. Specifically, the grayscale values ​​of the R and B sub-pixels are used as the grayscale threshold, typically serving as the lower grayscale limit for binarization. Finally, the grayscale image is pixel-filtered using the grayscale threshold to generate a binarized image. This method effectively reduces the impact of the Class B circuit area on the calibration point area and cross mark area in the grayscale image, accurately separating the pixels in the two areas.

[0161] See also Figure 5 , the present application provides an embodiment of a method for eliminating circuit area interference, comprising:

[0162] 501. Acquire a plurality of light reflection images collected from a calibration screen under spherical integral light sources of different brightness;

[0163] 502. Detecting brightness information of a display screen in a non-circuit area having a calibration image input thereto by using a brightness meter;

[0164] 503. Determine a corresponding target light reflection image from the plurality of light reflection images according to the brightness information;

[0165] 504. Determine a calibration point to be adjusted located in the circuit area;

[0166] 505. Determine a reflection area corresponding to the calibration point to be adjusted on the target light reflection image;

[0167] 506. Perform circuit interference elimination processing on the grayscale values ​​of the corresponding area of ​​the grayscale image according to the grayscale mean value of the reflection area.

[0168] In this embodiment, the grayscale of the calibration point area and the cross mark area needs to be adjusted to account for the impact of the circuit area's reflection on the calibration area. This allows for more accurate subsequent binarization. Specifically, several light reflection images of the calibration screen need to be acquired under spherical integral light sources of varying brightness.

[0169] Then, a luminance meter is used to detect the brightness information of the display screen in the non-circuit area with the calibration image input, and the target light reflection image with consistent brightness is found based on the brightness information.

[0170] Next, the calibration points to be adjusted located in the circuit area are determined, namely, the calibration point area and the cross mark point area located on the grayscale image and on the circuit area. Next, the reflection area corresponding to the calibration point to be adjusted on the target light reflection image is determined. Finally, the grayscale values ​​of the corresponding areas of the grayscale image are subjected to circuit interference elimination processing based on the grayscale mean of the reflection area. That is, the grayscale of the pixels in the calibration point area is subtracted from the grayscale mean of the corresponding reflection area. At the same time, the grayscale of the pixels in the cross mark point area is subtracted from the grayscale mean of the corresponding reflection area. This further eliminates the influence of the reflection of the circuit area on the grayscale image, and improves the accuracy of the subsequent binarization processing.

[0171] See also Figure 6 The present application provides an embodiment of a method for generating location information of a positioning pixel point, comprising:

[0172] 601. Perform morphological dilation processing on the pixels of the calibration point area in the binary image, and connect the pixels of the calibration point area to form a pixel whole, wherein the calibration point area includes a central calibration point area and a positioning calibration point area;

[0173] 602. Extract the coordinate position of the positioning pixel point from the binary image after morphological expansion according to the feature information of the positioning pixel point, and generate the positioning pixel point position information.

[0174] In this embodiment, the terminal first performs morphological dilation processing on the pixels in the calibration point area in the binary image, connects the pixels around the positioning pixel point (mainly the pixels in the calibration area, the pixels in the cross mark area will not be affected due to the difference in grayscale, and the positioning pixel point does not exist because there are no adjacent pixels of the same grayscale around it, so the dilation will not affect the positioning pixel point) to form a pixel as a whole, and eliminates the pixel gaps generated after binarization. This has no effect on the positioning pixel point, because there are no other lit pixels around the positioning pixel point, so the surrounding area cannot eliminate gaps with other pixels after binarization.

[0175] Finally, the positioning points are extracted from the binary image after morphological expansion according to the feature information of the positioning pixels, that is, the coordinates of the positioning pixels are determined according to , and the position information of the positioning pixels is generated.

[0176] See also Figure 7 The present application provides an embodiment of a calibration device based on screen foreign body detection, comprising:

[0177] The first acquisition unit 701 is used to input a calibration image to the calibration screen at the center of the stage, use the light detection camera to shoot, and obtain the calibration screen captured image. The calibration image is provided with one center calibration point and several positioning calibration points. The center calibration point is provided with a cross mark area with a grayscale different from that of the center calibration point. The positioning calibration point is provided with a cross mark area with a grayscale different from that of the positioning calibration point. A positioning pixel point is provided at the exact center of the cross mark area. The center calibration point is located at the center of the calibration image. The center calibration point and the positioning calibration point are located at the corresponding positions of the calibration screen captured image.

[0178] The first generating unit 702 is configured to extract the coordinates of the calibration points from the image captured by the calibration screen according to the preset calibration point feature information, and generate calibration point position information, where the calibration point information includes feature information of the center calibration point and feature information of the positioning calibration point;

[0179] Optionally, the first generating unit 702 includes:

[0180] The processing module 7021 is used to perform binarization processing on the calibration screen image and remove the cross mark on the calibration screen image by morphological dilation;

[0181] A screening module 7022 is configured to screen out all calibration point sets from the calibration point feature information of each block on the image captured by the calibration screen, where the calibration point feature information includes roundness information and area information;

[0182] Optionally, the calibration screen is a display screen provided with a circuit area, and the calibration point feature information further includes circuit structure information;

[0183] Screening module 7022 includes:

[0184] Marking the circuit area on the image captured by the calibration screen according to the circuit distribution data in the circuit structure information;

[0185] determining an interference area in a circuit area according to circuit reflection data and circuit morphology data in the circuit structure information;

[0186] Determine a set of pre-screened calibration points that meet the calibration points in each block on the image captured by the calibration screen according to the true roundness information and the area information;

[0187] The circuit area interference is filtered out from the initial screening calibration point set through the interference area, and the calibration point set that meets the requirements is selected.

[0188] The generating module 7023 is used to sort the row and column coordinates of the 9 calibration points in the order of row first and column later to generate the calibration point position information.

[0189] The displacement unit 703 is used to move the calibration screen to the position of the layered camera through the displacement stage. The layered camera is a color camera.

[0190] The second generating unit 704 is configured to focus the layered camera on the pixel layer of the calibration screen according to the layer information of the calibration screen, and to capture the center calibration point and the positioning calibration point on the calibration screen through the layered camera according to the calibration point position information to generate a calibration point image;

[0191] A conversion unit 705 is used to convert the calibration point image into a grayscale image;

[0192] A first acquisition unit 706 is configured to acquire a plurality of light reflection images of the calibration screen captured under spherical integral light sources of different brightness;

[0193] A detection unit 707 is configured to detect brightness information of a display screen in a non-circuit area after inputting a calibration image using a brightness meter;

[0194] A second determining unit 708 is configured to determine a corresponding target light reflection image from among the plurality of light reflection images according to the brightness information;

[0195] A third determining unit 709 is configured to determine a calibration point to be adjusted located in the circuit area;

[0196] The fourth determining unit 710 is configured to determine a reflection area corresponding to the calibration point to be adjusted on the target light reflection image;

[0197] Elimination unit 711, configured to perform circuit interference elimination processing on the grayscale value of the corresponding area of ​​the grayscale image according to the grayscale mean value of the reflective area;

[0198] A first determining unit 712 is configured to determine a grayscale threshold, and perform pixel screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image;

[0199] Optionally, the first determining unit 712 includes:

[0200] When a calibration point is located on the circuit area, channel data is selected from the RGB channel information of the grayscale image according to the circuit reflection data in the circuit structure information;

[0201] Generate grayscale threshold according to the selected channel pixel data;

[0202] The grayscale image is filtered by grayscale threshold to generate a binary image.

[0203] The third generating unit 713 is configured to perform adjacent pixel gap elimination processing on the binary image, and extract the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the position information of the positioning pixel points;

[0204] Optionally, the third generating unit 713 includes:

[0205] Performing morphological dilation processing on the pixels of the calibration point area in the binary image, connecting the pixels of the calibration point area to form a pixel whole, the calibration point area includes the central calibration point area and the positioning calibration point area;

[0206] The coordinate position of the positioning pixel point is extracted from the binary image after morphological expansion according to the feature information of the positioning pixel point, and the position information of the positioning pixel point is generated.

[0207] A first calculation unit 714 is configured to calculate position deviation information based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image;

[0208] The second calculation unit 715 is used to calculate the position calibration matrix of the lighting detection camera and the layered camera according to the calibration point position information, the positioning pixel position information and the position deviation information.

[0209] See also Figure 8 , the present application provides a calibration device based on screen foreign body detection, comprising:

[0210] Processor 801 , memory 802 , input / output unit 803 , and bus 804 .

[0211] The processor 801 is connected to the memory 802 , the input and output unit 803 , and the bus 804 .

[0212] The memory 802 stores a program, and the processor 801 calls the program to execute the following Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 、 Figure 5 and Figure 6 The calibration method in .

[0213] The present application provides a computer-readable storage medium, wherein a program is stored on the computer-readable storage medium, and when the program is executed on a computer, the program performs the following operations: Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 、 Figure 5 and Figure 6 The calibration method in .

[0214] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0215] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0216] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0217] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0218] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk, and other media that can store program code.

Claims

1. A calibration method based on screen foreign body detection, characterized in that: include: Input a calibration image to the calibration screen at the center of the stage, use the light detection camera to shoot, and obtain a calibration screen captured image. The calibration image is provided with a center calibration point and several positioning calibration points. The center calibration point is provided with a cross mark area with a different grayscale from the center calibration point. The positioning calibration point is provided with a cross mark area with a different grayscale from the positioning calibration point. A positioning pixel point is provided at the exact center of the cross mark area. The center calibration point is located at the center of the calibration image. There are a center calibration point and a positioning calibration point at the corresponding positions of the calibration screen captured image. Extracting the coordinates of the calibration points from the image captured by the calibration screen according to the preset calibration point feature information to generate calibration point position information, wherein the calibration point feature information includes feature information of the center calibration point and feature information of the positioning calibration point; The calibration screen is moved to the working position of a layered camera by a displacement stage, and the layered camera is a color camera; Focusing the layered camera on the pixel layer of the calibration screen according to the layer information of the calibration screen, and collecting the center calibration point and the positioning calibration point on the calibration screen by the layered camera according to the calibration point position information to generate a calibration point image; Converting the calibration point image into a grayscale image; Determining a grayscale threshold, and performing pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image; Performing adjacent pixel gap elimination processing on the binary image, and extracting the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the position information of the positioning pixel points; Calculating position deviation information based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image; The position calibration matrix of the lighting detection camera and the layered camera is calculated using the calibration point position information, the positioning pixel point position information and the position deviation information.

2. The calibration method according to claim 1, characterized in that: Extracting the coordinates of the calibration points from the image captured by the calibration screen according to the preset calibration point feature information to generate the calibration point position information includes: Binarizing the image captured by the calibration screen, and removing the cross mark on the image captured by the calibration screen by morphological dilation; Screening out all calibration point sets based on calibration point feature information of each block on the image captured by the calibration screen, wherein the calibration point feature information includes roundness information and area information; Sort the row and column coordinates of the 9 calibration points in the order of row first and column later to generate the calibration point position information.

3. The calibration method according to claim 2, characterized in that: The calibration screen is a display screen provided with a circuit area, and the calibration point feature information also includes circuit structure information; The calibration point feature information of each block on the calibration screen captured image is filtered to obtain all calibration point sets, including: Marking a circuit area on the calibration screen captured image according to the circuit distribution data in the circuit structure information; determining an interference area in a circuit area according to circuit reflection data and circuit morphology data in the circuit structure information; Determine a set of pre-screened calibration points that meet the calibration points in each block on the image captured by the calibration screen according to the true roundness information and the area information; The circuit area interference is filtered out from the initial screening calibration point set through the interference area, and a calibration point set that meets the requirements is selected.

4. The calibration method according to claim 3, characterized in that: Determining a grayscale threshold, performing pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image, including: When a calibration point is located on the circuit area, channel data is selected from the RGB channel information of the grayscale image according to the circuit reflection data in the circuit structure information; Generate grayscale threshold according to the selected channel pixel data; The grayscale image is subjected to pixel screening processing by using a grayscale threshold to generate a binary image.

5. The calibration method according to claim 4, characterized in that: After converting the calibration point image into a grayscale image, determining a grayscale threshold, and performing pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold before generating a binary image, the calibration method further includes: Acquire a plurality of light reflection images of the calibration screen collected under spherical integrating light sources of different brightness; Detecting the brightness information of the display screen in the non-circuit area with the calibration image input by using a luminance meter; determining a corresponding target light reflection image from a plurality of light reflection images according to brightness information; Determine the calibration point to be adjusted located in the circuit area; Determining a reflection area corresponding to the calibration point to be adjusted on the target light reflection image; A circuit interference elimination process is performed on the grayscale values ​​of the corresponding area of ​​the grayscale image according to the grayscale mean value of the reflective area.

6. The calibration method according to any one of claims 1 to 5, characterized in that: The binary image is processed to eliminate gaps between adjacent pixels, and the coordinates of the positioning pixel points are extracted from the binary image according to the feature information of the positioning pixel points to generate the positioning pixel point position information, including: Performing morphological dilation processing on the pixels of the calibration point area in the binary image to connect the pixels of the calibration point area to form a pixel whole, wherein the calibration point area includes a central calibration point area and a positioning calibration point area; The coordinate position of the positioning pixel point is extracted from the binary image after morphological expansion according to the feature information of the positioning pixel point, and the position information of the positioning pixel point is generated.

7. A calibration device based on screen foreign body detection, characterized in that: include: A first acquisition unit is used to input a calibration image to the calibration screen at the center of the stage, shoot it using a light detection camera, and acquire a calibration screen shot image, wherein the calibration image is provided with a center calibration point and several positioning calibration points, the center calibration point is provided with a cross mark area with a grayscale different from that of the center calibration point, the positioning calibration point is provided with a cross mark area with a grayscale different from that of the positioning calibration point, and a positioning pixel point is provided at the exact center of the cross mark area, the center calibration point is located at the center of the calibration image, and there are a center calibration point and a positioning calibration point at corresponding positions in the calibration screen shot image; A first generating unit is configured to extract calibration point coordinates from the calibration screen captured image according to preset calibration point feature information, and generate calibration point position information, wherein the calibration point feature information includes feature information of a central calibration point and feature information of a positioning calibration point; A displacement unit, used for moving the calibration screen to a workstation of a layered camera via a displacement stage, wherein the layered camera is a color camera; A second generating unit is configured to focus the layered camera on the pixel layer of the calibration screen according to the layer information of the calibration screen, and collect the central calibration point and the positioning calibration point on the calibration screen by the layered camera according to the calibration point position information to generate a calibration point image; a conversion unit, configured to convert the calibration point image into a grayscale image; a first determining unit, configured to determine a grayscale threshold, and perform pixel point screening processing on the calibration point area of ​​the grayscale image using the grayscale threshold to generate a binary image; The third generating unit is used to perform adjacent pixel gap elimination processing on the binary image, and extract the coordinates of the positioning pixel points from the binary image according to the feature information of the positioning pixel points to generate the position information of the positioning pixel points; A first calculation unit is used to calculate position deviation information based on the positioning pixel position information and the center coordinate position of the layered camera on the calibration point image; The second calculation unit is used to calculate the position calibration matrix of the lighting detection camera and the layered camera according to the calibration point position information, the positioning pixel point position information and the position deviation information.

8. The calibration device according to claim 7, characterized in that: The first generation unit includes: A processing module, configured to perform binarization processing on the image captured by the calibration screen, and remove the cross mark on the image captured by the calibration screen by morphological dilation; a screening module, configured to screen out all calibration point sets from calibration point feature information of each block on the image captured by the calibration screen, wherein the calibration point feature information includes true roundness information and area information; The generation module is used to sort the row and column coordinates of the 9 calibration points in the order of row first and column later to generate the calibration point position information.

9. A calibration device based on screen foreign body detection, characterized in that: Includes processor, memory, input and output units and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the calibration method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a program, and when the program is executed on a computer, the calibration method according to any one of claims 1 to 6 is executed.

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