MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes
<p/> <p>Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with larg...
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2010-01-01
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Series: | EURASIP Journal on Advances in Signal Processing |
Online Access: | http://asp.eurasipjournals.com/content/2010/410628 |
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doaj-710ebcca48174dba89711608f4e381302020-11-25T00:52:17ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802010-01-0120101410628MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale ChangesWang HaoGao WenHuang QingmingZhao Feng<p/> <p>Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.</p>http://asp.eurasipjournals.com/content/2010/410628 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wang Hao Gao Wen Huang Qingming Zhao Feng |
spellingShingle |
Wang Hao Gao Wen Huang Qingming Zhao Feng MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes EURASIP Journal on Advances in Signal Processing |
author_facet |
Wang Hao Gao Wen Huang Qingming Zhao Feng |
author_sort |
Wang Hao |
title |
MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes |
title_short |
MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes |
title_full |
MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes |
title_fullStr |
MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes |
title_full_unstemmed |
MOCC: A Fast and Robust Correlation-Based Method for Interest Point Matching under Large Scale Changes |
title_sort |
mocc: a fast and robust correlation-based method for interest point matching under large scale changes |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6172 1687-6180 |
publishDate |
2010-01-01 |
description |
<p/> <p>Similarity measures based on correlation have been used extensively for matching tasks. However, traditional correlation-based image matching methods are sensitive to rotation and scale changes. This paper presents a fast correlation-based method for matching two images with large rotation and significant scale changes. Multiscale oriented corner correlation (MOCC) is used to evaluate the degree of similarity between the feature points. The method is rotation invariant and capable of matching image pairs with scale changes up to a factor of 7. Moreover, MOCC is much faster in comparison with the state-of-the-art matching methods. Experimental results on real images show the robustness and effectiveness of the proposed method.</p> |
url |
http://asp.eurasipjournals.com/content/2010/410628 |
work_keys_str_mv |
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1725243092787789824 |