Shape feature extraction using dual-tree complex wavelet moment invariants method
Yü Liu, Xueyan Li, Xiaohua Qian, Fang Gao, Cao Li, Shuxu Guo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
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.