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Proceedings Paper

Shape feature extraction using dual-tree complex wavelet moment invariants method
Author(s): Yu Liu; Xueyan Li; Xiaohua Qian; Fang Gao; Li Cao; Shuxu Guo
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Paper Abstract

In this paper, we proposed a novel method to extract shape feature based on dual-tree complex wavelet. First, with the two level dual-tree complex wavelet transformations, we can get two low frequency components of the first level, which are used as wavelet moment invariants formed from approximation coefficients. Then, we calculate means and variance for each of the six detailed components in the second level since it contains different directions information of the shape. Using the Principal Component Analysis (PCA), twenty features can be reduced to five maximum useful features which contribute to shape matching.

Paper Details

Date Published: 14 December 2015
PDF: 4 pages
Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120N (14 December 2015); doi: 10.1117/12.2205809
Show Author Affiliations
Yu Liu, Jilin Univ. (China)
Xueyan Li, Jilin Univ. (China)
Xiaohua Qian, Wake Forest School of Medicine (United States)
Fang Gao, Jilin Univ. (China)
Li Cao, Huazhong Univ. of Science and Technology (China)
Shuxu Guo, Jilin Univ. (China)

Published in SPIE Proceedings Vol. 9812:
MIPPR 2015: Automatic Target Recognition and Navigation
Nong Sang; Xinjian Chen, Editor(s)

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