Robust Ear Detection for Biometric Verification

Ear biometric recognition has received increasing attention in recent years. However, not so much work has been done on the ear verification problem. Automatic ear detection (or segmentation) from facial profile images becomes an essential preprocessing stage with high impact on the subsequent recognition/verification tasks. This paper presents a new ear detection method based on the use of circular Hough transform and some anthropometric proportions to detect the ear region accurately. After detection, the extracted contours of the segmented ear region are used to verify the identity of an individual by adjusting a fuzzy snake model on it. The proposed ear detection and verification methods were successfully tested with images from three different databases presenting different variations to evaluate the robustness of this approach.