Saliency-Based Candidate Inspection Region Extraction in Tape Automated Bonding

Abstract

Electronic circuits are composed of components connected by traces which conduct the current. While the interconnections between the components can be created by assembling individual pieces of wire, it is nowadays common to use printed circuit boards. Tape automated bonding (TAB) is a technique to assemble chips and printed circuit boards. Because TAB become smaller, their inspection methods are required to adapt to the decreasing size of the electric circuits’ pattern. An image of a TAB is taken during the manufacturing process and analysed using image processing algorithms to inspect it for flaws in its pattern. This paper proposes an algorithm to find candidate inspection regions in a TAB pattern based on visual saliency. Orientation information contained in the image is processed to detect probable error regions and exclude correct regions from further inspection. The algorithm finds all the flaws in an image and in the case of regular patterns, marks only 5% of the image pixels as belonging to a candidate inspection region. The results show that a saliency-based approach is applicable on the task of finding flaws in the pattern of an electric circuit.