Fast correlation registration method using singular value decomposition

✍ Scribed by Mingchuan Zhang; Kai-Bor Yu; Robert M. Haralick

• Book ID: 102867668
• Publisher: John Wiley and Sons
• Year: 1986
• Tongue: English
• Weight: 521 KB
• Volume: 1
• Category: Article
• ISSN: 0884-8173
• DOI: 10.1002/int.4550010303

✦ Synopsis

A new, fast template-matching method using the Singular Value Decomposition (SVD) is presented. This approach involves a two-stage algorithm, which can be used to increase the speed of the matching process. In the first stage, the reference image is orthogonally separated by the SVD and then low-cost pseudo-correlation values are calculated. This reduces the number of computations to 2*N*L instead of N2L2, where L x L is the size of the reference image and N x N is the original image size. At the second stage, a small group of values near the maximum pseudo-correlation is selected. The true correlation for the small number of pixels in this group is then computed precisely in the second stage. Experimental and analytic results are presented to show how the computation complexity is greatly improved.