Automatic Ear Detection for Online Biometric Applications

The popularity of the ear biometrics is due to its unique distinct structure and high user convenience. However, the presence of hair and other skin attributes makes the automatic detection of ear contour a real challenge for online applications. This paper presents an online biometric authentication using ear contours acquired from a robust peg free acquisition set up. The Gaussian classifiers are used to first segment the skin and non-skin areas in the ear images. Laplacian of Gaussian is then used to compute edges of the skin areas, which helped to get ear-ROI images. A localized region based active contour is finally located in the ear-ROI images. The ear-contours are then employed for the authentication using log Gabor and SIFT features. The experimental results carried out on 700 ear images confirm the utility of the proposed approach.