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Guelma, Algeria

Benzaoui A.,University of May 08 1945 | Hezil N.,University of May 08 1945 | Boukrouche A.,University of May 08 1945
2015 1st International Conference on Applied Research in Computer Science and Engineering, ICAR 2015 | Year: 2015

External shape of the human ear presents a rich and stable information embedded on the curved 3D surface, which has invited lot attention from the forensic and engineer scientists in order to differentiate and recognize people. However, recognizing identity from external shape of the human ear in unconstrained environments, with insufficient and incomplete training data, dealing with strong person-specificity, and high within-range variance, can be very challenging. In this work, we implement a simple yet effective approach which uses and exploits recent local texture-based descriptors to achieve faster and more accurate results. Support Vector Machines (SVM) are used as a classifier. We experiment with two publicly available databases, which are IIT Delhi-1 and IIT Delhi-2, consisting of several ear benchmarks of different natures under varying conditions and imaging qualities. The experiments show excellent results beyond the state-of-the-art. © 2015 IEEE. Source

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