Research on ITO Conductive Glass Chipping Defect Detection Method based on Improved Skeleton Extraction

Aiming at the detection difficulties caused by edge bending, dirt, dust, etc. in the detection of chipping defects of ITO conductive glass based on machine vision, a chipping defect detection method based on improved skeleton extraction is proposed. First, pretreatment is performed prior to skeleton extraction, to remove the pseudo-skeleton caused by the influence of dirt, dust, and other noise. Secondly, according to the characteristics of chipping imaging, remove some algorithm links to improve algorithm execution efficiency; Finally, short straight line segmentation is unfolded after skeleton extraction, Based on the judgment of the number of short straight lines, the detection of chipping defects is realized. Experiments show that the improved algorithm has high efficiency and accuracy for the chipping detection of ITO conductive glass, and has high practical value.