Adaptive focusing-based LCD panel defect detection method

Abstract

The invention discloses an adaptive focusing-based LCD panel defect detection method. The method includes the following steps that: a picture is displayed on a display panel to be tested, and the validity of the picture is verified; display images under a plurality of imaging modes are obtained, and definition detection is performed on the display images, so that it can be confirmed that the definition of the display images under each imaging mode meets requirements; defect detection is performed on the display images, and the defect recognition of the display panel is completed. According tothe adaptive focusing-based LCD panel defect detection method provided by the technical schemes of the present invention, as for a condition that the same imaging focal length is adopted for differentimaging modes at present, focal length adjustment is respectively performed for each imaging mode, so that display pictures which correspondingly satisfy requirements under different imaging modes can be obtained, and therefore, the accurate identification of the defects of LCD panels can be realized.

Description

technical field [0001] The invention belongs to the field of LCD panel defect detection, in particular to an LCD panel defect detection method based on self-adaptive focusing. Background technique [0002] In the application of AOI technology to defect detection of LCD panels, image quality is a very critical part of defect detection, and its quality directly affects the accuracy of defect detection results. [0003] However, due to the imperfection of the optical system itself, the lens of the camera cannot focus light of different wavelengths to the same focal plane (the focal lengths of light of different wavelengths are different). That is to say, when the lens is at the same focal length, the image focus degree of Red / Green / Blue / L48 images is different, which leads to a large difference in the image quality of different images and it is not easy to balance each image when adjusting. The image quality of the screen, such as figure 1 shown. [0004] In addition, if fi...

AI Technical Summary

Problems solved by technology

[0007] 1. The current pattern image focus state may meet the image quality requirements of the machine adjustment standard, but the image clarity of other patterns cannot meet the requirements, which will affect the detection effect

[0008] 2. The focus state of the image is judged by the subjective judgment of the human eye to judge the image quality, and there are inaccuracies and differences

[0009] 3. There are differences in the image quality of different patterns, and it is inconvenient to configure the algorithm parameters. The parameter values ​​​​set for each screen vary greatly, and the focus degree of different screens is different. It is difficult to unify the parameter setting standards for subsequent classification logic

[0010] In the actual use of the production line, there are deviations in the accuracy of the movement of the line body and the display differences between different panels. These situations may affect the quality of the Pattern image, and then affect the stability of the detection.

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