Color Mura Defect Detection Method Based on Channel Contrast Sensitivity Function Filtering

Abstract

To address the issue of low detection accuracy caused by low contrast in color Mura defects, this paper proposes a color Mura defect detection method based on channel contrast sensitivity function (CSF) filtering. The RGB image of the captured liquid crystal display (LCD) display is converted to the Lab color space, and the Weber contrast feature maps of the Lab channel images are calculated. Frequency domain filtering is performed using the CSF to obtain visually sensitive Lab feature maps. Color Mura defect detection is achieved by employing adaptive segmentation thresholds based on the fused feature maps of the L channel and ab channels. The color Mura evaluation criterion is utilized to quantitatively assess the defect detection results. Experimental results demonstrate that the proposed method achieves an accuracy rate of 87% in color Mura defect detection, outperforming existing mainstream detection methods.