An eigenvalue-based similarity measure and its application in defect detection

Abstract

In this paper, we propose an eigenvalue-based similarity measure between two gray-level images and, in particular, aim at the application in defect detection. The pair-wise gray levels at coincident pixel locations in two compared images are used as the coordinates to plot the correspondence map. If two compared images are identical, the plot in the correspondence map is a diagonal straight line. Otherwise, it results in a non-linear shape in the correspondence map. The smaller eigenvalue of the covariance matrix of the data points in the correspondence map is used as the similarity measure. It will be approximately zero for two resembled images, and distinctly large for dissimilar images. Experimental results from a number of assembled PCBs (printed circuit boards) have shown the effectiveness of the proposed similarity measure for detecting local defects in complicated images.