Human Ear Recognition Based on Phase Congruency and Kernel Discriminant Analysis
Song Ze Lei, Qiang Zhu · Applied Mechanics and Materials · 2012
To solve the multi-pose ear recognition problem under the different illumination condition, a novel method which combines phase congruency with kernel discriminant analysis (KDA) is proposed. The phase congruency of ear image is first calculated using Log-Gabor filter with 5 scales and 8 orientations, and then the phase congruency of different orientation is constructed as high dimensional vector including ample information. The high dimensional vector is mapped to kernel space to acquire discriminant feature. Experimental results show that the proposed method obtains higher recognition rate compared with the other related methods. The method of the phase congruency can eliminate the influence of illumination and phase congruency with KDA is effective to multi-pose ear recognition.