| Issue |
ITM Web Conf.
Volume 43, 2022
The International Conference on Artificial Intelligence and Engineering 2022 (ICAIE’2022)
|
|
|---|---|---|
| Article Number | 01014 | |
| Number of page(s) | 10 | |
| DOI | https://doi.org/10.1051/itmconf/20224301014 | |
| Published online | 14 March 2022 | |
Fast Fourier transform for fingerprint enhancement and features extraction with adaptive block size using orientation fields
1 Université des Sciences et de la Technologie Houari Boumediene (USTHB), BP 32 Bab Ezzouar, 16111 - Alger, Algeria
2 Laboratoire d’Informatique de Bourgogne (LIB), EA 7534, 21000 Dijon, France
* Corresponding author. Email: aaitaoudia@usthb.dz
Extracting minutiae from a digital fingerprint is a crucial step in a fingerprint-based recognition systems. This work deals with poor-quality fingerprint images containing broken ridges. The enhancement stage connects broken ridges and is essential for extracting correct minutiae. We use a FFT variant [8] for this stage, but, to truly benefit from FFT in a block, it is essential to determine a suitable block size, depending on ridges orientation field. We propose to use a quadtree to partition the ridges orientation field into homogeneous blocks. A block is homogeneous when at least seventy percent of its ridges orientations are within ten degrees. Another issue addressed in this article is the choice of a suitable neighborhood window size W for computing orientation field image, depending on the fingerprint image quality. The performance improvements of our algorithm are evaluated and compared with standard measures MSE, PSNR and GI, on databases DB1 to DB4 of FVC2004 and NIST special database SD302d.
Key words: Minutiae / fingerprint enhancement / orientation field / quadtree decomposition / FFT
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.