Liquid crystal display defects in multiple backgrounds with visual real‐time detection. Issue 7 (19th April 2021)

• Record Type: Journal Article
• Authors: Cui, Yu; Wang, Sen; Wu, Haibo; Xiong, Binzhou; Pan, Yunlong
• Is Part Of: Journal of the Society for Information Display. Volume 29:Issue 7(2021)
• Page Start: 547
• Page End: 560
• Publication Date: 2021-04-19
• Subjects: defect detection -- edge detection -- image segmentation -- LCD -- visual real‐time detection; Information display systems -- Periodicals; 621.38154205
• DOI: 10.1002/jsid.997
• Languages: English
• ISSNs: 1071-0922

Abstract

Abstract: There are kinds of defects that may appear in the process of Liquid Crystal Display (LCD) manufacturing, which cannot be effectively detected, owing to the uneven illumination, low contrast, and miscellaneous patterns of defects. To improve the efficiency of defect detection and ensure the quality of LCD, three visual real‐time detection methods are adopted for detecting six different defects in multiple backgrounds, where image preprocessing methods are used to highlight the defects and facilitate the segmentation and detection. Specifically, the interclass variance (OTSU) method is used to segment and mark Liquid Crystal Display (LCD) Mura and scratch defects in six kinds of solid color backgrounds; the method and the connectivity‐4 judgment criteria are adopted to label edge defects in grid display background; the gray mean and standard deviation of the segmented subregions are calculated to recognize the color gradation defect in the 32‐level gradation display background. Experimental results show that LCD Mura defects and scratches can be segmented more completely by the proposed method compared with the benchmark methods, and the edge defects can be identified accurately by the OTSU‐based method and particle‐based morphological processing with grids as the detection background, and the color gradation can also be recognized with the 32‐level gray gradation as the background. Abstract : Various defects may appear in the LCD manufacturing process. We use three visual real‐time inspection methods to detect six different defects in multiple backgrounds. Specifically, we combine the image preprocessing and the OTSU segmentation method, which can effectively detect LCD Mura and scratch defects in the 6 pure color backgrounds; combine the OTSU segmentation method and the connectivity‐4 judgment standard to achieve Detection of edge defects in the grid display background; by dividing the gray scale background, and calculating the gray average and standard deviation of the subregions, the color scale defects can be effectively detected. Through the above three detection methods, LCD defects can be detected effectively, accurately and intuitively.