基于单演同相幅值模式的人脸识别方法

Face recognition algorithm based on pattern of monogenic magnitudes with same phase

针对单演信号表述仅利用幅值和方向而忽略相位信息的问题,提出了一种单演同相幅值模式方法。用多尺度的单演滤波器提取人脸的单演幅值和相位信息,将相位量化并根据相位量化的结果对幅值累加和二值编码,从而获得若干张单演同相幅值模式图。将每一张PMMSP图分块并提取直方图特征,用BFLD对特征进行降维。这样能有效提升特征的判别能力并降低算法的时间和空间复杂度。在CAS-PEAL人脸库和AR人脸库上的实验证明了该算法的有效性。

In order to take advantages of the monogenic magnitude and phase information for face recognition, a new method based on pattern of monogenic magnitudes with same phase is proposed. Multi-scale monogenic filters are used to extract the monogenic magnitude and phase information of the image. This paper obtains the phase quantization images, accumu-lates the magnitude according to the quantization results and codes the accumulative results by binary strategy. After that the patterns of monogenic magnitudes with same phase image are obtained. PMMSP maps are divided into blocks and the histo-gram is extracted from the blocks. BFLD is not only used to reduce the dimension of the features but also enhance its discrimi-native power. The experimental results on the CAS-PEAL and AR face databases show that the proposed algorithm is effective.