SIFT 기반의 귀 영역을 이용한 개인 식별

Abstract

In recent years, ear has emerged as a new biometric trait, because it has advantage of higher useracceptance than fingerprint and can be captured at remote distance in an indoor or outdoor environment. This paper proposes an individual identification method using ear region based on SIFT(shift invariantfeature transform). Unlike most of the previous studies using rectangle shape for extracting a regionof interest(ROI), this study sets an ROI as a flexible expanded region including ear. It also presents aneffective extraction and matching method for SIFT keypoints. Experiments for evaluating the performanceof the proposed method were performed on IITD public database. It showed correct identification rateof 98.89%, and it showed 98.44% with a deformed dataset of 20% occlusion. These results show thatthe proposed method is effective in ear recognition and robust to occlusion