Research Of Machine Vision Based Defect Detection Techniques On PCB

Printed Circuit Board, a kind of information carrier which integrates varieties of electronic devices, has popular applications in electronic fields nowadays. With the rapid development of manufacture techniques, electronic product tends to lighter, thinner and smaller, and PCB turns to have more layers and higher density, which makes quality detection of PCB become more difficult. Traditional detection methods can not satisfy the large production for inaccurate, slow and long time detection, then how to realize automated defect detection of PCB becomes a hot topic in semiconductor industry.Machine vision technology, which combines electronics, photoelectric detection, image processing and computer technology into oneself, is a potential new technology in industrial detection field. Machine vision system, usually obtains digital image signals of detected object by CCD or CMOS camera, then processes the digital image signals to get characteristic values by adopting advanced computer hardware and software techniques, and accomplishes workpiece recognition or defect detection accordingly. Based on the results, the system displays the images, exports the data and sends out instructions to control corresponding equipment to act such as location adjusting and quality filtering according to feedback information.Machine vision technology is applied into automated PCB defect detection in this paper. On the basis of studying machine vision technology, we design the whole scheme of PCB defect detection system towards several simple geometric defects on PCB, discuss the principle of the system, and establish hardware platform for the system, including illuminating unit, image acquisition unit and control unit. Then, we discuss and design the foremost vision detection algorithm towards PCB image, including image pre-processing, segmentation, description, mathematical morphology, and pattern recognition, while the key is to accomplish defect detection using mathematical morphology and pattern recognition based on PCB design rules. Finally, we design system software according to the vision detection algorithm to realize defect detection and recognition on PCB.Experimental results demonstrate that though the PCB defect detection system described in this paper, four types of defects including short circuit, open circuit, protuberance and concavity on PCB can be effectively detected, located and recognized.