
Proceedings Paper
M-SIFT: a new descriptor based on Legendre moments and SIFTFormat | Member Price | Non-Member Price |
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Paper Abstract
There are many feature descriptors that are insensitive to geometric transformations such as rotation and scale
variation. However, most of them cannot effectively deal with blurred image which is a key problem in many real
applications. In this paper, we propose a new feature descriptor that combines SIFT descriptor with combined blur, scale
and rotation invariant Legendre moment (CBRSL). The proposed method inherits the advantage of SIFT and CBRSL
which leads to invariance for scale, rotation and blur degradation simultaneously. We also show how this new descriptor
is able to better represent the blur and geometric invariant feature descriptor in image registration. The experimental
results validate the effectiveness of our method which is superior to SIFT methods.
Paper Details
Date Published: 12 January 2012
PDF: 7 pages
Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501B (12 January 2012); doi: 10.1117/12.921074
Published in SPIE Proceedings Vol. 8350:
Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies
Safaa S. Mahmoud; Zhu Zeng; Yuting Li, Editor(s)
PDF: 7 pages
Proc. SPIE 8350, Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies, 83501B (12 January 2012); doi: 10.1117/12.921074
Show Author Affiliations
Xin Zuo, Southeast Univ. (China)
Jiangsu Univ. of Science and Technology (China)
Xiubin Dai, Southeast Univ. (China)
Jiangsu Univ. of Science and Technology (China)
Xiubin Dai, Southeast Univ. (China)
Limin Luo, Southeast Univ. (China)
Published in SPIE Proceedings Vol. 8350:
Fourth International Conference on Machine Vision (ICMV 2011): Computer Vision and Image Analysis; Pattern Recognition and Basic Technologies
Safaa S. Mahmoud; Zhu Zeng; Yuting Li, Editor(s)
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