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Proceedings Paper

Fingerprint verification based on wavelet subbands
Author(s): Ke Huang; Selin Aviyente
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Paper Abstract

Fingerprint verification has been deployed in a variety of security applications. Traditional minutiae detection based verification algorithms do not utilize the rich discriminatory texture structure of fingerprint images. Furthermore, minutiae detection requires substantial improvement of image quality and is thus error-prone. In this paper, we propose an algorithm for fingerprint verification using the statistics of subbands from wavelet analysis. One important feature for each frequency subband is the distribution of the wavelet coefficients, which can be modeled with a Generalized Gaussian Density (GGD) function. A fingerprint verification algorithm that combines the GGD parameters from different subbands is proposed to match two fingerprints. The verification algorithm in this paper is tested on a set of 1,200 fingerprint images. Experimental results indicate that wavelet analysis provides useful features for the task of fingerprint verification.

Paper Details

Date Published: 25 August 2004
PDF: 9 pages
Proc. SPIE 5404, Biometric Technology for Human Identification, (25 August 2004); doi: 10.1117/12.541912
Show Author Affiliations
Ke Huang, Michigan State Univ. (United States)
Selin Aviyente, Michigan State Univ. (United States)

Published in SPIE Proceedings Vol. 5404:
Biometric Technology for Human Identification
Anil K. Jain; Nalini K. Ratha, Editor(s)

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