Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4635456 | Applied Mathematics and Computation | 2007 | 11 Pages |
Abstract
An accurate estimation of fingerprint orientation fields is an essential step in the overall fingerprint recognition process. Conventional gradient-based approaches are popular but very sensitive to noise. In this paper, we propose a novel implementation to improve the performance of gradient-based methods. The enhanced algorithm chooses the best orientation estimate from four overlapping neighborhoods of every image block, where the voting scheme is based on the reliability measures. We test our algorithm on real fingerprint images. The experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with modest computation time in comparison with other gradient-based methods.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Yi Wang, Jiankun Hu, Fengling Han,