Defects Detection in Printed Circuit Boards by Separation and Comparison of Chains

Abstract

The known K-means clustering, flood-filling, and thinning algorithms are used to find coordinates of contacts in PCB images. Images of different types and colors are considered. The clustering algorithm is used to reduce the number of colors, to get uniform colors in the PCB image. The thinning algorithm is used to build skeletons and find pixels of contacts. The flood-fill algorithm is used to mark and separate chains, defect connectivity, and metal defects. Different subtraction operations are applied to original, transformed, and distributed cumulative histogram images.