Fast normalized cross correlation for defect detection

Authors:
Du-Ming Tsai;Chien-Ta Lin
Affiliations:
Department of Industrial Engineering and Management, Yuan-Ze University, 135 Yuan-Tung Road, Nei-Li, Tao-Yuan 32026, Taiwan, ROC;Department of Industrial Engineering and Management, Yuan-Ze University, 135 Yuan-Tung Road, Nei-Li, Tao-Yuan 32026, Taiwan, ROC
Venue:
Pattern Recognition Letters
Year:
2003

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Abstract

Normalized cross correlation (NCC) has been used extensively for many machine vision applications, but the traditional normalized correlation operation does not meet speed requirements for time-critical applications. In this paper, we propose a fast NCC computation for defect detection. A sum-table scheme is utilized, which allows the calculations of image mean, image variance and cross-correlation between images to be invariant to the size of template window. For an image of size M × N and a template window of size m × n, the computational complexity of the traditional NCC involves 3 ċ m ċ n ċ M ċ N additions/subtractions and 2 ċ m ċ n ċ M ċ N multiplications. The required numbers of computations of the proposed sum-table scheme can be significantly reduced to only 18 ċ M ċ N additions/subtractions and 2 ċ M ċ N multiplications.