Face recognition using anisotropic dual-tree complex wavelet packets

In this paper, we propose a novel face recognition method based on anisotropic dual-tree complex wavelet packets(ADT-CWP). 2-D dual-tree complex wavelet transform(DT-CWT) provides a geometrically oriented decomposition for image representation as well as shift invariance. By applying anisotropic wavelet packet decomposition on DT-CWT further, ADT-CWP can be used to extract facial features better, which turns out to benefit for face recognition. With adaptively assigning different weights to different wavelet subbands, consistent best performances can be obtained based on different face databases which are under different conditions, such as varying illuminations and expressions, compared to PCA and other face recognition methods, especially Gabor-based method. Furthermore, in addition to the consistent and promising classification performances, our proposed ADT-CWP-based method has a really low computational complexity.