Improved rotational matching of sift and surf
Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientati...
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Society of Photo-Optical Instrumentation Engineers (SPIE)
2012
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Online Access: | http://eprints.utm.my/id/eprint/47087/ http://dx.doi.org/10.1117/12.953950 |
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my.utm.470872019-03-31T08:31:40Z http://eprints.utm.my/id/eprint/47087/ Improved rotational matching of sift and surf Goh, K. M. Mokji, M. M. Abu Bakar, S. A. R. TA Engineering (General). Civil engineering (General) Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientation assignment and feature descriptor extraction for matching. SURF is computation efficient compared to SIFT because the integral image is used for the convolutions to reduce computation time. However, both methods also do not focus much on the technique of matching. This paper introduces a method which can help to improve the rotational matching performance in term of accuracy by establishing a decision matrix and an approximated rotational angle within two corresponding images. The proposed method generally improved the matching rate around 10% to 20% in terms of accuracy. Society of Photo-Optical Instrumentation Engineers (SPIE) 2012 Article PeerReviewed Goh, K. M. and Mokji, M. M. and Abu Bakar, S. A. R. (2012) Improved rotational matching of sift and surf. Fourth International Conference On Digital Image Processing (Icdip 2012), 8334 . http://dx.doi.org/10.1117/12.953950 DOI:10.1117/12.953950 |
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TA Engineering (General). Civil engineering (General) Goh, K. M. Mokji, M. M. Abu Bakar, S. A. R. Improved rotational matching of sift and surf |
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Scale-Invariant Feature Transform(SIFT) and Speeded-Up Robust Feature(SURF) are common techniques used for extracting robust features that can be used to perform matching between different viewpoints of scenes. Both methods basically involve three main stages, which are feature extraction, orientation assignment and feature descriptor extraction for matching. SURF is computation efficient compared to SIFT because the integral image is used for the convolutions to reduce computation time. However, both methods also do not focus much on the technique of matching. This paper introduces a method which can help to improve the rotational matching performance in term of accuracy by establishing a decision matrix and an approximated rotational angle within two corresponding images. The proposed method generally improved the matching rate around 10% to 20% in terms of accuracy. |
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Article |
author |
Goh, K. M. Mokji, M. M. Abu Bakar, S. A. R. |
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Goh, K. M. Mokji, M. M. Abu Bakar, S. A. R. |
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Goh, K. M. |
title |
Improved rotational matching of sift and surf |
title_short |
Improved rotational matching of sift and surf |
title_full |
Improved rotational matching of sift and surf |
title_fullStr |
Improved rotational matching of sift and surf |
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Improved rotational matching of sift and surf |
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improved rotational matching of sift and surf |
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Society of Photo-Optical Instrumentation Engineers (SPIE) |
publishDate |
2012 |
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http://eprints.utm.my/id/eprint/47087/ http://dx.doi.org/10.1117/12.953950 |
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13.159267 |