Efficient template matching for multi-channel images

被引：32
作者：
Mattoccia, Stefano
Tombari, Federico [1 ]
Di Stefano, Luigi
机构：
[1] Univ Bologna, Dept Elect Comp Sci & Syst DEIS, I-40136 Bologna, Italy
来源：
PATTERN RECOGNITION LETTERS | 2011年 / 32卷 / 05期
关键词：
Template matching; Multi-channel images; ZNCC;
D O I：
10.1016/j.patrec.2010.12.004
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Template matching is a computationally intensive problem aimed at locating a template within a image. When dealing with images having more than one channel, the computational burden becomes even more dramatic. For this reason, in this paper we investigate on a methodology to speed-up template matching on multi-channel images without deteriorating the outcome of the search. In particular, we propose a fast, exhaustive technique based on the Zero-mean Normalized Cross-Correlation (ZNCC) inspired from previous work related to grayscale images. Experimental testing performed over thousands of template matching instances demonstrates the efficiency of our proposal. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：694 / 700
页数：7
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