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Article: Improvement of fingerprint retrieval by a statistical classifier
Title | Improvement of fingerprint retrieval by a statistical classifier |
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Authors | |
Keywords | Distorted sample fingerprint identification fingerprint retrieval FVC database NIST-4 database |
Issue Date | 2011 |
Publisher | I E E E. The Journal's web site is located at http://www.ieee.org/organizations/society/sp/tifs.html |
Citation | Ieee Transactions On Information Forensics And Security, 2011, v. 6 n. 1, p. 59-69 How to Cite? |
Abstract | The topics of fingerprint classification, indexing, and retrieval have been studied extensively in the past decades. One problem faced by researchers is that in all publicly available fingerprint databases, only a few fingerprint samples from each individual are available for training and testing, making it inappropriate to use sophisticated statistical methods for recognition. Hence most of the previous works resorted to simple $k$-nearest neighbor ($k$-NN) classification. However, the $k$-NN classifier has the drawbacks of being comparatively slow and less accurate. In this paper, we tackle this problem by first artificially expanding the set of training samples using our previously proposed spatial modeling technique. With the expanded training set, we are then able to employ a more sophisticated classifier such as the Bayes classifier for recognition. We apply the proposed method to the problem of one-to-$N$ fingerprint identification and retrieval. The accuracy and speed are evaluated using the benchmarking FVC 2000, FVC 2002, and NIST-4 databases, and satisfactory retrieval performance is achieved. © 2010 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/139266 |
ISSN | 2023 Impact Factor: 6.3 2023 SCImago Journal Rankings: 2.890 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Leung, KC | en_HK |
dc.contributor.author | Leung, CH | en_HK |
dc.date.accessioned | 2011-09-23T05:47:46Z | - |
dc.date.available | 2011-09-23T05:47:46Z | - |
dc.date.issued | 2011 | en_HK |
dc.identifier.citation | Ieee Transactions On Information Forensics And Security, 2011, v. 6 n. 1, p. 59-69 | en_HK |
dc.identifier.issn | 1556-6013 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/139266 | - |
dc.description.abstract | The topics of fingerprint classification, indexing, and retrieval have been studied extensively in the past decades. One problem faced by researchers is that in all publicly available fingerprint databases, only a few fingerprint samples from each individual are available for training and testing, making it inappropriate to use sophisticated statistical methods for recognition. Hence most of the previous works resorted to simple $k$-nearest neighbor ($k$-NN) classification. However, the $k$-NN classifier has the drawbacks of being comparatively slow and less accurate. In this paper, we tackle this problem by first artificially expanding the set of training samples using our previously proposed spatial modeling technique. With the expanded training set, we are then able to employ a more sophisticated classifier such as the Bayes classifier for recognition. We apply the proposed method to the problem of one-to-$N$ fingerprint identification and retrieval. The accuracy and speed are evaluated using the benchmarking FVC 2000, FVC 2002, and NIST-4 databases, and satisfactory retrieval performance is achieved. © 2010 IEEE. | en_HK |
dc.language | eng | en_US |
dc.publisher | I E E E. The Journal's web site is located at http://www.ieee.org/organizations/society/sp/tifs.html | en_HK |
dc.relation.ispartof | IEEE Transactions on Information Forensics and Security | en_HK |
dc.rights | ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | - |
dc.subject | Distorted sample | en_HK |
dc.subject | fingerprint identification | en_HK |
dc.subject | fingerprint retrieval | en_HK |
dc.subject | FVC database | en_HK |
dc.subject | NIST-4 database | en_HK |
dc.title | Improvement of fingerprint retrieval by a statistical classifier | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Leung, KC:kcleung@eee.hku.hk | en_HK |
dc.identifier.email | Leung, CH:chleung@eee.hku.hk | en_HK |
dc.identifier.authority | Leung, KC=rp00147 | en_HK |
dc.identifier.authority | Leung, CH=rp00146 | en_HK |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/TIFS.2010.2100382 | en_HK |
dc.identifier.scopus | eid_2-s2.0-79951835585 | en_HK |
dc.identifier.hkuros | 194879 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-79951835585&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 6 | en_HK |
dc.identifier.issue | 1 | en_HK |
dc.identifier.spage | 59 | en_HK |
dc.identifier.epage | 69 | en_HK |
dc.identifier.eissn | 1556-6021 | - |
dc.identifier.isi | WOS:000287409400007 | - |
dc.publisher.place | United States | en_HK |
dc.identifier.scopusauthorid | Leung, KC=7401860663 | en_HK |
dc.identifier.scopusauthorid | Leung, CH=7402612415 | en_HK |
dc.identifier.issnl | 1556-6013 | - |