2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:MP-P5.6
Session:Biometrics III: Fingerprints, Iris, Palmprints
Time:Monday, September 17, 14:30 - 17:10
Presentation: Poster
Title: WAVELET MAXIMA AND MOMENT INVARIANTS BASED IRIS FEATURE EXTRACTION
Authors: Makram Nabti; Queen’s University Belfast 
 Ahmed Bouridane; Queen’s University Belfast 
Abstract: Iris recognition is one of the most reliable personal identification methods and is becoming the most promising technique for high security. In this paper, we propose an efficient method for personal iris identification by investigating iris textures that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by using wavelet transform (wavelet maxima components), and moment invariants. The proposed scheme is invariant to translation, rotation, and scale changes. Experimental results have shown that the proposed system could be used for personal identification in an efficient and effective manner.



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