Abstract
Biometrics identification methods proved to be very efficient, more natural and easy for users than traditional methods of human identification. In fact, only biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. The future of biometrics leads to passive physiological methods based on images of such parts of human body as face and ear. The article introduces to ear biometrics and presents its advantages over face biometrics in passive human identification systems. Then the geometrical method of feature extraction from human ear images in order to perform human identification is presented. The proposed method is invariant to rotation, translation and scaling due to coordinates normalization and placing the major reference point in the centroid. The feature extraction algorithm consists of two steps, so that in the process of classification two feature vectors for each ear image are used.
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Choraś, M. (2004). Ear Biometrics Based on Geometrical Method of Feature Extraction. In: Perales, F.J., Draper, B.A. (eds) Articulated Motion and Deformable Objects. AMDO 2004. Lecture Notes in Computer Science, vol 3179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30074-8_7
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DOI: https://doi.org/10.1007/978-3-540-30074-8_7
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