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
Link To Document :
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