Ear recognition via sparse representation and Gabor filters

Rahman Khorsandi, Steven Cadavid, Mohamed Abdel-Mottaleb

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

In this paper, we present a fully automated approach for ear recognition based upon sparse representation. In sparse representation, features extracted from the training data of each subject are used to develop a dictionary. In this work, Gabor filters are used for feature extraction. Classification is performed by extracting features from the test data and using the dictionary for representing the test data. The class of the test data is then determined based upon the involvement of the dictionary entries in its representation. Experimental results conducted on the University of Notre Dame (UND) collection G dataset, containing large appearance, pose, and lighting variability, yielded a rank-one recognition rate of 98.46%. The proposed system outperforms the method described in [1], which achieves a recognition rate of 96.88% when evaluated on the same dataset. Moreover, the proposed system was evaluated on a greater number of test images per subject, demonstrating its robustness.

Original languageEnglish (US)
Title of host publication2012 IEEE 5th International Conference on Biometrics
Subtitle of host publicationTheory, Applications and Systems, BTAS 2012
Pages278-282
Number of pages5
DOIs
StatePublished - Dec 1 2012
Event2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012 - Arlington, VA, United States
Duration: Sep 23 2012Sep 27 2012

Publication series

Name2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012

Other

Other2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012
CountryUnited States
CityArlington, VA
Period9/23/129/27/12

Keywords

  • Ear Recognition
  • Feature extraction
  • Gabor Filters
  • Sparse Representation

ASJC Scopus subject areas

  • Computer Science Applications
  • Biomedical Engineering

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  • Cite this

    Khorsandi, R., Cadavid, S., & Abdel-Mottaleb, M. (2012). Ear recognition via sparse representation and Gabor filters. In 2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012 (pp. 278-282). [6374589] (2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012). https://doi.org/10.1109/BTAS.2012.6374589