DocumentCode
2497761
Title
Research on synergetic fingerprint classification and matching
Author
Gao, Jun ; Dong, Huo-Ming ; Chen, Dingguo ; Gan, Long ; Dong, Wen-Wen
Author_Institution
Sch. of Comput. & Inf., Hefei Univ. of Technol., China
Volume
5
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
3066
Abstract
Fingerprint recognition is one of the research hotspots of biometrics techniques. And fingerprint classification and matching are key parts in an automated fingerprint recognition system. The traditional fingerprint recognition systems have such disadvantages as high computation complexity, low speed, low recognition rate to uncompleted or defiled fingerprints, and not robust. In this paper, we propose a novel fingerprint classification and matching method based on synergetic pattern recognition, which emphasizes global features of fingerprint. With lots of artificial fingerprint samples, the results show that the proposed method is effective, fast and robust. In the end, experimental results are analyzed and a synergetic fingerprint recognition system is introduced.
Keywords
fingerprint identification; image classification; image matching; artificial fingerprint samples; automated fingerprint recognition system; biometrics techniques; computation complexity; defiled fingerprints; fingerprint matching; recognition rate; synergetic fingerprint classification; synergetic pattern recognition; Biometrics; Data mining; Fingerprint recognition; Gallium nitride; Image matching; Information security; Neural networks; Pattern formation; Pattern recognition; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1260104
Filename
1260104
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