Shape feature extraction using dual-tree complex wavelet moment invariants method

Yu Liu; Xueyan Li; Xiaohua Qian; Fang Gao; Li Cao; Shuxu Guo

doi:10.1117/12.2205809

14 December 2015 Shape feature extraction using dual-tree complex wavelet moment invariants method

Yu Liu, Xueyan Li, Xiaohua Qian, Fang Gao, Li Cao, Shuxu Guo

Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 98120N (2015) https://doi.org/10.1117/12.2205809
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

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.

Citation Download Citation

Yu Liu, Xueyan Li, Xiaohua Qian, Fang Gao, Li Cao, and Shuxu Guo "Shape feature extraction using dual-tree complex wavelet moment invariants method", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120N (14 December 2015); https://doi.org/10.1117/12.2205809

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