Image Registration Using SIFT and Canonical Correlation Analysis

DOI

10.2991/meita-15.2015.25How to use a DOI?

Keywords

Image registration, Feature matching, SIFT, Mismatches removal, RANSAC

Abstract

To improve the quality of SIFT feature matching, a mismatches removal method is proposed based on the collinearity property of the canonical correlation features. The influence of each match on the collineartiy degree is analyzed to find false matches. Firstly, a putative set of matches is obtained based on distances between SIFT feature descriptors. Secondly, the spatial relationship of matched points is encoded by canonical correlation analysis. The match with the largest effect on the collinearity degree is iteratively eliminated. Experimental results show the proposed method can reserve a high rate of correct matches determined by a threshold. Compared with several other mismatches removal methods, it provides comparable or better results.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wei Zhao
AU  - Zheng Tian
AU  - Lijuan Yang
AU  - Weidong Yan
AU  - Jinhuan Wen
PY  - 2015/08
DA  - 2015/08
TI  - Image Registration Using SIFT and Canonical Correlation Analysis
BT  - Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications
PB  - Atlantis Press
SP  - 118
EP  - 122
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-15.2015.25
DO  - 10.2991/meita-15.2015.25
ID  - Zhao2015/08
ER  -