A novel method of detecting a panel

Abstract

The application discloses a novel detection panel method, comprising a line scanning camera and a surface camera, and the line scanning camera and the surface camera cooperate with each other to scan a product. The application has the beneficial effect that the line scanning camera and the surface camera cooperate with each other to scan the product, the line scanning camera can quickly process the photographed image, and defects such as scratches, uneven film and misplacement can be detected, and then the surface camera extracts the color information of RGB, so that defects such as RGB pixel overflow, deviation and omission can be detected, and manual re-inspection in the later period is avoided.

Description

Technical Field

[0001] This invention relates to the field of panel inspection technology, and in particular to a novel method for inspecting panels. Background Technology

[0002] After the RGB pixels of the display panel are coated with a mask, defects need to be detected. Because the entire panel is very large and microscopic inspection is required, and the speed of a surface camera is not as fast as that of a line scan camera, a black and white line scan camera is used for defect detection.

[0003] However, using masks for printing or vapor deposition of RGB colors can result in color loss or color shift, which cannot be detected by the current architecture. This is because monochrome cameras are not sensitive to RGB colors, resulting in poor contrast. Therefore, this defect can only be detected through random checks by personnel later on, and real-time alarm processing is not possible. Since this defect caused by the mask is due to positioning errors, it can lead to overall color loss or shift. After long-term research, the inventors have developed a new method for detecting panels by adding a color surface camera to the existing method. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a novel method for detecting panels.

[0005] The objective of this invention is achieved through the following technical solution: a novel method for detecting panels, comprising a line scan camera and a surface camera, wherein the line scan camera and the surface camera cooperate to scan the product.

[0006] Preferably, it includes the following steps:

[0007] S1: The product moves into the scanning area, so that the line camera and area camera in the scanning area can scan the product simultaneously;

[0008] S2: The line scan camera transmits the image to the slave unit for processing;

[0009] S3: The slave device transmits the processed defect data to the host device via the HUB;

[0010] S4: The area camera transmits the image to the host for processing. The host aggregates the defects scanned by the line scan camera and integrates the data scanned by the area camera and the line scan camera to generate MAP data.

[0011] Preferably, before image processing in S2 and S4, brightness and contrast need to be adjusted and noise reduction is required.

[0012] Preferably, the formula for adjusting image brightness and contrast is as follows:

[0013] G(i,j)=a*F(i,j)+b;

[0014] Where a > 0, b is the gain coefficient, that is, parameter a adjusts the overall contrast of the image, and parameter b adjusts the overall brightness of the image.

[0015] Preferably, the noise reduction process includes the following steps:

[0016] A1: Choose a 3x3 convolution kernel;

[0017] A2: Determine the coordinates of the convolution center;

[0018] A3: Distribute convolution kernel weights using a two-dimensional Gaussian function;

[0019] A4: Convolution with the image achieves noise reduction.

[0020] Preferably, the exposure time of the surface camera is ≤ the accuracy / the speed of the motion platform.

[0021] Preferably, the area camera includes the following processing steps:

[0022] B1: The area camera acquires a 3D color image of the panel display area;

[0023] B2: Determine the size of the m*m rectangle;

[0024] B3: The two diagonals of the rectangle are the defect inspection areas;

[0025] B4: Returns the defect coordinates and integrates them with the line scan camera data to generate MAP data;

[0026] B5: Identify defects, obtain defect widths, and classify them.

[0027] Preferably, in B5

[0028] The present invention has the following advantages: The present invention scans the product by using a line scan camera and a surface camera in cooperation. The line scan camera can quickly process the captured image and detect defects such as scratches, uneven film and misalignment. Then, the surface camera extracts the RGB color information, thereby detecting defects such as RGB pixel overflow, offset and omission, avoiding manual re-inspection in the later stage. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the basic process of the panel detection method;

[0030] Figure 2 This is a schematic diagram of the hardware architecture for the detection panel method.

[0031] In the diagram, 1-line scan camera, 2-sub-camera, 3-HUB, 4-main unit, 5-plane camera. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0033] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0034] It should be noted that, unless otherwise specified, the embodiments and features described in this invention can be combined with each other.

[0035] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0036] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use, or the orientation or positional relationship commonly understood by those skilled in the art. They are only used for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0037] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0038] In this embodiment, as Figure 1As shown, a novel method for inspecting panels includes a line scan camera 1 and a surface camera 5, which work together to scan the product. By scanning the product together, the line scan camera 1 can quickly process the captured image to detect defects such as scratches, uneven film, and misalignment. Then, the surface camera 5 extracts RGB color information, thereby detecting defects such as RGB pixel overflow, offset, and omission, avoiding subsequent manual re-inspection.

[0039] Furthermore, such as Figure 2 As shown, it includes the following steps:

[0040] S1: The product moves to the scanning area, so that the line camera 1 and the area camera 5 in the scanning area can scan the product simultaneously.

[0041] S2: Line scan camera 1 transmits the image to slave unit 2 for processing;

[0042] S3: Sub-machine 2 transmits the processed defect data to host machine 4 via HUB3;

[0043] S4: The surface camera 5 transmits the image to the host 4 for processing. The host 4 aggregates the defects scanned by the line scan camera 1 and integrates the data scanned by the surface camera 5 and the line scan camera 1 to generate MAP data. Specifically, the main function of the line scan camera 1 is to capture the entire image of the panel and present it in black and white. The image captured by the line scan camera 1 is then transmitted to the slave camera 2. The slave camera 2 detects defects such as scratches, uneven film, and misalignment. The defect data processed by the slave camera 2 is then transmitted to the host 4 via the HUB 3. The surface camera 5 is mainly used to capture color images of the panel display area and transmits the color images to the host 4 for processing and aggregation of the defect information from the line scan camera 1. The data detected by the two cameras are then integrated to generate MAP data.

[0044] In this embodiment, brightness and contrast adjustments, as well as noise reduction, are required before image processing in steps S2 and S4. Furthermore, the formulas for adjusting image brightness and contrast are as follows:

[0045] G(i,j)=a*F(i,j)+b;

[0046] Where a > 0, b is the gain coefficient, meaning parameter a adjusts the overall image contrast, and parameter b adjusts the overall image brightness. Further, the noise reduction process includes the following steps:

[0047] A1: Choose a 3x3 convolution kernel;

[0048] A2: Determine the coordinates of the convolution center;

[0049] A3: Distribute convolution kernel weights using a two-dimensional Gaussian function;

[0050] A4: Convolution with the image achieves a noise reduction effect. Specifically, the main purpose of noise reduction processing is to suppress the adverse effects of various noises on subsequent image processing and image visual effects during image transmission. In this embodiment, Gaussian filtering is used.

[0051] In this embodiment, the exposure time of the area camera 5 is ≤ accuracy / speed of the motion platform. Specifically, the area camera 5 is selected as a global exposure camera, and the main purpose of ensuring that the exposure time is ≤ accuracy / speed of the motion platform is to solve the image retention problem.

[0052] Furthermore, the face camera 5 includes the following processing steps:

[0053] B1: Camera 5 acquires a three-dimensional color image of the panel display area;

[0054] B2: Determine the size of the m*m rectangle;

[0055] B3: The two diagonals of the rectangle are the defect inspection areas;

[0056] B4: Return the defect coordinates and integrate them with the line scan camera data to generate MAP data;

[0057] B5: Identify defects, obtain defect widths, and classify them.

[0058] In this embodiment, since arranging the image in RGB channels is not conducive to color differentiation in terms of hue, saturation, and brightness, the image is divided into defect color thresholds using HSV channels. Since defects appear predominantly white under an area camera, the formula for converting RGB channels to HSV channels is as follows:

[0059] V←max(R, G, B);

[0060]

[0061]

[0062] Through adjustment and testing, the color thresholds of white under the HSV channel were divided into hue (H): min(0)~max(180); saturation (S): min(0)~max(30); and brightness (V): min(221)~max(255).

[0063] Furthermore, in B5 Specifically, a defect width less than the R, G, B color bandwidth is considered a color offset, and a defect width equal to the R, G, B color bandwidth is considered a color loss.

[0064] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A novel method for detecting a panel, characterized in that: It includes a line scan camera (1) and a surface camera (5), wherein the line scan camera (1) and the surface camera (5) cooperate to scan the product; It also includes the following steps: S1: The product moves into the scanning area, so that the line camera (1) and the area camera (5) in the scanning area scan the product simultaneously; S2: The line scan camera (1) transmits the image to the sub-machine (2) for processing; S3: The submachine (2) transmits the processed defect data to the host (4) through the HUB (3); S4: The area camera (5) transmits the image to the host (4) for processing. The host (4) collects the defects scanned by the line scan camera (1) and integrates the data scanned by the area camera (5) and the line scan camera (1) to generate MAP data. The area camera (5) includes the following processing steps: B1: The surface camera (5) acquires a three-dimensional color image of the panel display area; B2: Determine the size of the m*m rectangle; B3: The two diagonals of the rectangle are the defect inspection area; B4: Returns the defect coordinates and integrates them with the line scan camera data to generate MAP data; B5: Identify defects, obtain defect widths, and classify them; In B5, the defect width = the number of missing pixels * the pixel width of the surface image. .

2. The method for detecting a novel panel according to claim 1, characterized in that: Before image processing in both S2 and S4, brightness and contrast need to be adjusted and noise reduction is required.

3. The method for detecting a novel panel according to claim 2, characterized in that: The formula for adjusting image brightness and contrast is: ； Where a > 0, b is the gain coefficient, that is, parameter a adjusts the overall contrast of the image, and parameter b adjusts the overall brightness of the image.

4. The method for detecting a novel panel according to claim 3, characterized in that: The noise reduction process includes the following steps: A1: Choose a 3x3 convolution kernel; A2: Determine the coordinates of the convolution center; A3: Distribute convolution kernel weights using a two-dimensional Gaussian function; A4: Convolution with the image achieves noise reduction.

5. The method for detecting a novel panel according to claim 4, characterized in that: The exposure time of the surface camera (5) is less than or equal to the accuracy / speed of the motion platform.

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