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	Efficient fingercode classification
	Sun, Hong-Wei ; Lam, Kwok-Yan ; Gollmann, Dieter ; Chung, Siu-Leung ; Li, Jian-Bin ; Sun, Jia-Guang
	2010-05-07 ; 2010-05-07
关键词	vector quantization fingercode fingerprint classification system software homeland security CODEWORD SEARCH ALGORITHM LOOK-UP TABLE VECTOR QUANTIZATION FINGERPRINT CLASSIFICATION HADAMARD-TRANSFORM Computer Science, Information Systems Computer Science, Software Engineering
中文摘要	In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e.g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.
语种	英语 ; 英语
出版者	IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG ; TOKYO ; KIKAI-SHINKO-KAIKAN BLDG MINATO-KU SHIBAKOEN 3 CHOME, TOKYO, 105, JAPAN
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/16759]
专题	清华大学
推荐引用方式 GB/T 7714	Sun, Hong-Wei,Lam, Kwok-Yan,Gollmann, Dieter,et al. Efficient fingercode classification[J],2010, 2010.
APA	Sun, Hong-Wei,Lam, Kwok-Yan,Gollmann, Dieter,Chung, Siu-Leung,Li, Jian-Bin,&Sun, Jia-Guang.(2010).Efficient fingercode classification..
MLA	Sun, Hong-Wei,et al."Efficient fingercode classification".(2010).

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