基于环形对称Gabor变换和2DPCA的人脸识别算法

与传统Gabor小波变换相比，环形对称Gabor变换（CSGT）具有信息冗余度低和严格的旋转不变性的优点。提出了一种基于环形对称Gabor变换与2DPCA的人脸识别新算法，首先将所有人脸图像都变换到环形对称Gabor变换域，然后按照两种融合方案将不同尺度的特征融合到一起，最后采用2DPCA方法进行特征提取和分类。在ORL人脸数据库上进行仿真实验并与传统的2DPCA、GT+2DPCA等方法做了对比，实验结果表明提出的算法不但取得了更好的识别效果，而且提高了识别速度。

Face recognition based on circularly symmetrical Gabor transform and 2DPCA

Compared with the traditional Gabor wavelet transform, the Circularly Symmetric Gabor Transform（CSGT） has the advantages of low redundancy and strict rotation invariance. An effective face recognition method is proposed in this paper, which is based on CSGT and two-Dimensional Principal Component Analysis（2DPCA）. The face images are mapped onto the CSGT domain, the multi-scale features are fused by using two fusion rules in the same domain. The features are extracted and classified employing the 2DPCA algorithm. Experimental results on ORL database show that the proposed method can obtain higher recognition rate and faster recognition speed.