Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Fingerprint quality assessment based on wave atoms transform

Fingerprint quality assessment based on wave atoms transform Fingerprint image quality is of great importance for an automatic fingerprint identification system (AFIS), and affects its performance. In this paper, a new fingerprint image quality measure based on wave atoms transform is proposed. Indeed, fingerprint features are extracted by exploiting wave atoms multi-scale and multi-directional properties. Hence, for good quality block, the singularities are concentrated in a same directional subbands. In the opposite, for poor quality, the singularities are scattered over several directional subbands. In order to evaluate the performance of the algorithm, FVC (2002) databases have been considered. The results show that this method has a serious potential in fingerprint quality evaluation and will improve the performance and effectiveness of AFIS. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

Fingerprint quality assessment based on wave atoms transform

Loading next page...
 
/lp/inderscience-publishers/fingerprint-quality-assessment-based-on-wave-atoms-transform-rMDzmpwFJz
Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2014.060979
Publisher site
See Article on Publisher Site

Abstract

Fingerprint image quality is of great importance for an automatic fingerprint identification system (AFIS), and affects its performance. In this paper, a new fingerprint image quality measure based on wave atoms transform is proposed. Indeed, fingerprint features are extracted by exploiting wave atoms multi-scale and multi-directional properties. Hence, for good quality block, the singularities are concentrated in a same directional subbands. In the opposite, for poor quality, the singularities are scattered over several directional subbands. In order to evaluate the performance of the algorithm, FVC (2002) databases have been considered. The results show that this method has a serious potential in fingerprint quality evaluation and will improve the performance and effectiveness of AFIS.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2014

There are no references for this article.