PCB defect detection system based on image processing

Under the background of intelligent manufacturing, the quality inspection of printed circuit board (PCB), as the carrier of electronic products, plays an important role. In view of the shortcomings of existing traditional detections, this paper has put forward a PCB detection method based on machine vision, focusing on image preprocessing algorithm and detection analysis. The median filter algorithm was used to remove the noise in the image. Logarithmic transformation was used to enhance image contrast. Sobel operator was used for edge detection to obtain the geometric center of the defect area. On this basis, the PCB image was registered by template matching method, and the difference between the preprocessed PCB image to be tested and the standard PCB image was calculated to get the difference map. Subsequently, morphological algorithm was used to remove the slight differences and obtain the defect map. In the end, the simulation results have shown that the proposed algorithm has good detection effect and high precision in PCB defect detection.