关键词: 冗余, 分辨率, 方向性, 二维快速广义S变换, 识别率

Abstract: For the research of face recognition, the discrete wavelet transform has the disadvantage that the resolution is low. S transform has high resolution and multi-scale direction, but it has high computational complexity and large redundant information. Two dimensional fast generalized S transform is proposed to overcome the shortcomings. Firstly, the amplitude and phase spectra of the two dimensional fast generalized S domain are analysed by programming, and the original signal is reconstructed. It is proven that two dimensional fast generalized S transform has multi resolution and multi orientation. Secondly, the direction based on the fast generalized S domain for two dimensional signals is combined with Support Vector Machine（SVM）.Low frequency direction of S domain is used as the input feature of SVM and face recognition and classification are realized in ORL standard face database. Experimental results show that compared with the discrete wavelet transform, the two dimensional fast generalized S transform, applied to face recognition by combining it with the support vector machine, has higher recognition rate.

Key words: redundant, resolution, orientation, two dimensional fast generalized S transform, recognition rate