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Journal of Electronic Imaging

Ear biometric recognition using local texture descriptors
Author(s): Amir Benzaoui; Abdenour Hadid; Abdelhani Boukrouche
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Paper Abstract

Automated personal identification using the shape of the human ear is emerging as an appealing modality in biometric and forensic domains. This is mainly due to the fact that the ear pattern can provide rich and stable information to differentiate and recognize people. In the literature, there are many approaches and descriptors that achieve relatively good results in constrained environments. The recognition performance tends, however, to significantly decrease under illumination variation, pose variation, and partial occlusion. In this work, we investigate the use of local texture descriptors, namely local binary patterns, local phase quantization, and binarized statistical image features for robust human identification from two-dimensional ear imaging. In contrast to global image descriptors which compute features directly from the entire image, local descriptors representing the features in small local image patches have proven to be more effective in real-world conditions. Our extensive experimental results on the benchmarks IIT Delhi-1, IIT Delhi-2, and USTB ear databases show that local texture features in general and BSIF in particular provide a significant performance improvement compared to the state-of-the-art.

Paper Details

Date Published: 19 September 2014
PDF: 12 pages
J. Electron. Imag. 23(5) 053008 doi: 10.1117/1.JEI.23.5.053008
Published in: Journal of Electronic Imaging Volume 23, Issue 5
Show Author Affiliations
Amir Benzaoui, Univ. of May 8th 1945 (Algeria)
Abdenour Hadid, Univ. of Oulu (Finland)
Abdelhani Boukrouche, Univ. of May 8th 1945 (Algeria)

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