Visual detection of defects in solder joints

The automatic, real-time visual acquisition and inspection of VLSI boards requires the use of machine vision and artificial intelligence methodologies in a new `frame' for the achievement of better results regarding efficiency, products quality and automated service. In this paper the visual detection and classification of different types of defects on solder joints in PC boards is presented by combining several image processing methods, such as smoothing, segmentation, edge detection, contour extraction and shape analysis. The results of this paper are based on simulated solder defects and a real one.