Automatic detection of region-mura defect in TFT-LCD
Visual defects, called mura in the field, sometimes occur during the manufacturing of the flat panel liquid crystal displays. In this paper we propose an automatic inspection method that reliably detects and quantifies TFT-LCD region-mura defects. The method consists of two phases. In the first phase we segment candidate region-muras from TFT-LCD panel images using the modified regression diagnostics and Niblack's thresholding. In the second phase, based on the human eye's sensitivity to mura, we quantify mura level for each candidate, which is used to identify real muras by grading them as pass or fail. Performance of the proposed method is evaluated on real TFT-LCD panel samples.
regression diagnostics machine vision image segmentation industrial inspection visual perception