Fingerprint minutiae extraction from skeletonized binary images

Fingerprint comparison is usually based on minutiae matching. The minutiae considered in automatic identification systems are normally ridge bifurcati ons and terminations. In this paper we present a set of algorithms for the extraction of fingerprint minutiae from skeletonized binary images. The goa l of the present work is the extraction of the real 40-60 minutiae of a fin gerprint image from the 2000-3000 contained in typical skeletonized and bin arized images. Besides classical methodologies for minutiae filtering, a ne w approach is proposed for bridge cleaning based on ridge positions instead of classical methods based on directional maps. Finally, two novel criteri a and related algorithms are introduced for validating the endpoints and bi furcations. Statistical analysis of the results obtained by the proposed ap proach shows efficient reduction of spurious minutiae. The use of the finge rprint minutiae extraction algorithms has also been considered in a fingerp rint identification system in terms of timing and false reject or acceptanc e rates. The presented minutiae extraction algorithm performs correctly in dirty areas and on the background as well, making computationally expensive segmentation algorithms unnecessary. The results are confirmed by visual i nspections of validated minutiae of the NIST sdb 4 reference fingerprint im age database. (C) 1999 Pattern Recognition Society. Published by Elsevier S cience Ltd, All rights reserved.