Ear Recognition based on Gabor Features.

Abstract: In this paper, we propose an ear recognition system based on 2D ear images which includes three stages: ear enrollment, feature extraction and ear recognition. Ear enrollment includes ear detection and ear normalization. The ear detection approach based on Gentle Adaboost algorithm detects the ear part under complex background using two steps: off-line cascaded classifier training and on-line ear detection. Then Active Shape Model is applied to segment the ear part and normalize all the ear images to the same size. For its eminent characteristics in spatial local feature exaction and orientation selection, Gabor-based ear is presented in this paper. Kernel Fisher Discriminant Analysis is applied for dimension reduction of the high-dimensional Gabor features. Then distance based classifier is applied for ear recognition. The experimental results on USTB ear database show effectiveness of the proposed approach. [Copyright &y& Elsevier]