Machine vision system for visual defect inspection of TFT-LCD

To improve the identification for visual defect of TFT-LCD,a new machine vision system is proposed,which is superior to human eye inspection. The system respectively employs a CCD camera to capture the image of TFT-LCD panel and an image processing system to identify potential visual defects. Image pre-processing,such as average filtering and geometric correction,was performed on the captured image,and then a candidate area of defect was segmented from the background. Feature information extracted from the area of interest entered a fuzzy rule-based classifier that simulated the defect inspection of TFT-LCD undertaken by experienced technicians. Experiment results show that the machine vision system can obtain fast,objective and accurate inspection compared with subjective and inaccurate human eye inspection.