Extracting and Classifying for Ear Recognition in Biometrics Knowledge

Abstract

Ear detection is an important part of an ear recognition system. This paper proposes ear recognition based on Gabor wavelets and Support Vector Machine (SVM). The framework has three steps. In the first step, the ear is detected from an image of the face. In the second step, Gabor wavelets are used to extract ear feature. The Gabor wavelets, whose kernels are similar to the 2D receptive field profiles of the mammalian cortical simple cells, exhibit desirable characteristics of spatial locality and orientation selectivity. In the third step, when the Gabor wavelets features were obtained, classifications were done by SVM. Research of ear recognition and its application is a new subject in the field of authentication. Ear normalization and alignment is a fundamental module in the ear recognition system.