Automated inspection of printed circuit boards through machine vision
Computers in Industry
Application of 'vision in the loop' for inspection of lace fabric
Real-Time Imaging - Special issue on real-time visual monitoring and inspection
Rotation-invariant pattern matching using wavelet decomposition
Pattern Recognition Letters
Wavelet-based printed circuit board inspection algorithm
Integrated Computer-Aided Engineering
Defect detection in patterned wafers using anisotropic kernels
Machine Vision and Applications
Material classification for printed circuit boards by kernel fisher discriminant analysis
CCIW'11 Proceedings of the Third international conference on Computational color imaging
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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.