Exploiting color SIFT features for 2D ear recognition

Jindan Zhou, Steven Cadavid, Mohamed Abdel-Mottaleb

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

13 Scopus citations

Abstract

In this paper, we present a robust method for 2D ear recognition using color SIFT features. Firstly, we extend the Scale Invariant Feature Transform (SIFT) algorithm originally performed on the intensity channel [1] to the RGB color channels to maximize the robustness of the SIFT feature descriptor. Secondly, a feature matching algorithm for ear recognition is proposed by fusion of the features extracted from the different color channels. Experiments conducted on the University of Notre Dame (UND) and the West Virginia University (WVU) ear biometric datasets indicate that our method can achieve better recognition rates than the state-of-the-art methods applied on the same datasets.

Original languageEnglish (US)
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages553-556
Number of pages4
DOIs
StatePublished - Dec 1 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: Sep 11 2011Sep 14 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period9/11/119/14/11

Keywords

  • biometrics
  • ear recognition
  • SIFT

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Zhou, J., Cadavid, S., & Abdel-Mottaleb, M. (2011). Exploiting color SIFT features for 2D ear recognition. In ICIP 2011: 2011 18th IEEE International Conference on Image Processing (pp. 553-556). [6116405] (Proceedings - International Conference on Image Processing, ICIP). https://doi.org/10.1109/ICIP.2011.6116405