Research on synergetic fingerprint classification and matching

被引：1

作者：

Gao, J ^{[1
]}

Dong, BM ^{[1
]}

Chen, DG ^{[1
]}

Gan, L ^{[1
]}

Dong, WW ^{[1
]}

机构：

[1] Hefei Univ Technol, Sch Comp & Informat, Lab Image Infroamt Proc, Hefei 230009, Anhui, Peoples R China

来源：

2003 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-5, PROCEEDINGS | 2003年

关键词：

fingerprint classification; fingerprint matching; synergetics; pattern recognition;

D O I：

10.1109/ICMLC.2003.1260104

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：3066 / 3071

页数：6

共 20 条

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