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Using selective correlation coefficient for robust image registration

delete2003-05-01
delete107
PRE
AI
Y
Yutaka Satoh
DOI:10.1016/S0031-3203(02)00081-Xdelete
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摘要

摘要

En 中文
A new method is proposed for robust image registration named Selective Correlation Coefficient in order to search images under ill-conditioned illumination or partial occlusion. A correlation mask-image is generated for selecting pixels of an image before matching. The mask-image can be derived from a binary-coded increment sign-image defined from any object-image and the template. The mask-rate of occluded regions is theoretically expected to be 0.5, while unoccluded regions have much lower rate than 0.5. Robustness for ill-conditioned environment can be realized since inconsistent brightness of occluded regions can be omitted from the mask operation. Furthermore, the mask enhancement procedure is proposed to get more stable robustness. The effectiveness of masking increases by the procedure, resulting in the rate around 0.7 for masking of occluded regions. This paper includes a theoretical modeling and analysis of the proposed method and some experimental results with real images. (C) 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Keyword:
normalized cross correlation
selective correlation coefficient
image registration
template matching
robust statistics
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Pattern Recognition 封面图
Pattern Recognition
IF:
7.6
论文数:
1.3W
被引数:
4.5W

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