Ear Recognition Based on Statistical Shape Model

Authors:
Lu Lu;Xiaoxun Zhang;Youdong Zhao;Yunde Jia
Affiliations:
Beijing Institute of Technology, China;Beijing Institute of Technology, China;Beijing Institute of Technology, China;Beijing Institute of Technology, China
Venue:
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 3
Year:
2006

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Abstract

Alfred system suggests that ear shape can be used as a unique and comparable feature for identity recognition. In this paper, we aim to extract ear shape features for recognition. Active Shape Models (ASMs) is applied to model the shape and local appearance of the ear in a statistical manner. In addition, steerable features are extracted from the ear image ahead of ASMs. Steerable features encode rich discriminant information of the local structural texture and provide accurate guidance for shape location. Eigenearshape is used for final classification. Experiments on an ear database show an encouraging performance. Some experiments on double ears combined for recognition are also carried out, and indicate that the fusion outperforms either ear alone.