DocumentCode :
432732
Title :
Classification of fingerprints using singular points and their principal axes
Author :
Klimanee, C. ; Nguyen, D.T.
Author_Institution :
Sch. of Eng., Tasmania Univ., Hobart, Tas., Australia
Volume :
2
fYear :
2004
fDate :
24-27 Oct. 2004
Firstpage :
849
Abstract :
This paper proposes a rule-based algorithm for classification of a fingerprint into one of six well-known classes: plain arch, tented arch, right loop, left loop, whorl and twin loop. The rules are formed using the relative locations and types of singular points and the relative directions of their associated principal axes. The reliable and fast classification algorithm is made possible by a simple but effective combination of ridge flow-code technique and orientation variance calculation in the determination of singular points and principal axes. The Poincare indices of these singular points are used to determine their type: ordinary, delta, core or double-core. For a small test sample of 157 fingerprints available to the authors, the correct classification rate is better than 90%.
Keywords :
fingerprint identification; image classification; image resolution; Poincare indices; fingerprint classification; fingerprint identification; image resolution; orientation variance calculation; principal axes; ridge flow-code technique; rule-based algorithm; singular point detection; Australia; Bidirectional control; Bifurcation; Databases; Fingerprint recognition; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2004. ICIP '04. 2004 International Conference on
ISSN :
1522-4880
Print_ISBN :
0-7803-8554-3
Type :
conf
DOI :
10.1109/ICIP.2004.1419432
Filename :
1419432
Link To Document :
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