Texture analysis for ear recognition using local feature descriptor and transform filter

Jun Feng; Zhichun Mu

doi:10.1117/12.832749

30 October 2009 Texture analysis for ear recognition using local feature descriptor and transform filter

Jun Feng, Zhichun Mu

Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 74962P (2009) https://doi.org/10.1117/12.832749
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

Ear recognition is a kind of the novel representative subjects in the field of non-disturbance biometrics authentication and is becoming received wide attention in academic research. In this paper, the ear recognition problem based on texture analysis is discussed. A novel local wavelet binary pattern descriptor combining local binary pattern descriptor with wavelet transform filter is presented. And an ear recognition approach based on local wavelet binary pattern descriptor and support vector machines classification is proposed, which is tested on USTB ear image set. The experiment results show that the ear recognition scheme using local feature descriptor and transform filter is effective and promising. The performance of support vector machines classifier is better than that of K Nearest Neighbor classifier. The best combination occurs under the Chi square distance and 'reverse biorthogonal 3.1' wavelet, and the 96.86% cross- validation recognition rate is obtained.

Citation Download Citation

Jun Feng and Zhichun Mu "Texture analysis for ear recognition using local feature descriptor and transform filter", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74962P (30 October 2009); https://doi.org/10.1117/12.832749

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