Presented at the
1997 IEEE Asilomar Conference on Signals, Systems, and Computers
A Fingerprint Classification Technique Using Directional Images
Meltem Ballan (1),
F. Ayhan Sakarya (1), and
Brian L. Evans (2)
(1) Department of Electronics and Telecommunication Engineering,
Yildiz Technical University,
80750 Istanbul, Turkey
Meltem's LinkedIn Page
(2) Department of Electrical and Computer Engineering,
Engineering Science Building,
The University of Texas at Austin,
Austin, TX 78712-1084 USA
We present a fast, automated fingerprint classification technique
based on the properties of singular points (delta and core point)
in fingerprints obtained from directional histograms.
The technique enhances the digitized image using adaptive clipping
and image matching, finds the directional image by checking the
orientations of individual pixels, computes directional histograms using
overlapping blocks in the directional image, and classifies the fingerprint
in to the Wirbel class (whorl and twin loop) or the Lasso class
(arch, tented arch, right loop, and left loop. The new technique is
simple, fast, and reliable.
A follow-up discussion to our paper is available.
Last Updated 01/23/14.