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Ear Biometrics in Human Identification System


Affiliations
1 Ganadipathy Tulsi’s Jain Engineering College, Vellore, India
     

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Biometrics is physical or behavior characteristics that can be used for human identification. We propose the ear as a biometric and investigate it with both 2D and 3D data. The ICP-based algorithm also demonstrates good scalability with size of dataset. These results are encouraging in that they suggest a strong potential for 3D ear shape as a biometric. Multi-biometric 2D and 3D ear recognition are also explored. The proposed automatic ear detection method will integrate with the current system, and the performance will be evaluated with the original one. The investigation of ear recognition under less controlled conditions will focus on the robustness and variability of ear biometrics. Multi-modal biometrics using 3D ear images will be explored, and the performance will be compared to existing biometrics experimental results.


Keywords

Ear, Biometrics, Recognition, Detection and Extraction.
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  • Ear Biometrics in Human Identification System

Abstract Views: 143  |  PDF Views: 3

Authors

S. Adhikesavan
Ganadipathy Tulsi’s Jain Engineering College, Vellore, India
S. Ammathul Fareedha
Ganadipathy Tulsi’s Jain Engineering College, Vellore, India

Abstract


Biometrics is physical or behavior characteristics that can be used for human identification. We propose the ear as a biometric and investigate it with both 2D and 3D data. The ICP-based algorithm also demonstrates good scalability with size of dataset. These results are encouraging in that they suggest a strong potential for 3D ear shape as a biometric. Multi-biometric 2D and 3D ear recognition are also explored. The proposed automatic ear detection method will integrate with the current system, and the performance will be evaluated with the original one. The investigation of ear recognition under less controlled conditions will focus on the robustness and variability of ear biometrics. Multi-modal biometrics using 3D ear images will be explored, and the performance will be compared to existing biometrics experimental results.


Keywords


Ear, Biometrics, Recognition, Detection and Extraction.