CONTOURLET TRANSFORM BASED EAR RECOGNITION

In this paper, we propose a novel method for ear recognition using the contourlet transform. As first, we decompose the image using the contourlet transform. Then the features of the lowpass subband and the bandpass directional subbands are extracted respectively. Here we use the normalized gray-level co-occurrence matrix and the generalized Gaussian density to extract ear features. Finally, the two kinds of features are connected and the SVM method is used for classification. Extensive experiments have performed to valid its efficiency and robustness. Moreover, we can conclude that for ear feature extraction, the contourlet transform is more suitable for wavelet transform.