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Proceedings Paper

Robust-statistic-based template matching
Author(s): Bingcheng Li; Dongming Zhao; Jesus Rene Villalobos; Sergio D. Cabrera
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Paper Abstract

In this paper, a robust-statistic-based method is proposed to implement template matching. The proposed method has two novel advantages. First, it is computationally efficient because only a very small fraction of the template pixels is used to do template matching. Second, it generates very high mainlobes and very low sidelobes because it only accumulates the gradient magnitudes of edges when the template is moved to the object center (signal focusing (SF) accumulation), and summarizes the gradient magnitudes in homogeneous regions when the template goes to other positions (interference avoiding (IA) accumulation). It is shown experimentally that compared with the normalized correlation method, the SFIA method increases the DSNR for about 11 approximately 30 db and decrease computational cost about 20 approximately 50 times.

Paper Details

Date Published: 15 April 1997
PDF: 11 pages
Proc. SPIE 3029, Machine Vision Applications in Industrial Inspection V, (15 April 1997); doi: 10.1117/12.271242
Show Author Affiliations
Bingcheng Li, Univ. of Texas/El Paso (United States)
Dongming Zhao, Univ. of Michigan/Dearborn (United States)
Jesus Rene Villalobos, Univ. of Texas/El Paso (United States)
Sergio D. Cabrera, Univ. of Texas/El Paso (United States)

Published in SPIE Proceedings Vol. 3029:
Machine Vision Applications in Industrial Inspection V
A. Ravishankar Rao; Ning S. Chang, Editor(s)

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