Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/1184
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | - |
| dc.creator | Wu, X | - |
| dc.creator | Wang, K | - |
| dc.creator | Zhang, DD | - |
| dc.date.accessioned | 2014-12-11T08:23:22Z | - |
| dc.date.available | 2014-12-11T08:23:22Z | - |
| dc.identifier.isbn | 0-7803-9091-1 | - |
| dc.identifier.uri | http://hdl.handle.net/10397/1184 | - |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.rights | © 2005 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. | en_US |
| dc.rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | en_US |
| dc.subject | Biometrics | en_US |
| dc.subject | Palmprint recognition | en_US |
| dc.subject | Valley feature | en_US |
| dc.subject | Morphological operator | en_US |
| dc.title | Palmprint recognition using valley features | en_US |
| dc.type | Conference Paper | en_US |
| dc.description.otherinformation | Author name used in this publication: David Zhang | en_US |
| dc.description.otherinformation | Biometrics Research Centre, Department of Computing | en_US |
| dcterms.abstract | This paper presents a novel approach for palmprint recognition based on the valley features. This approach uses the bothat operation to extract the valleys from a very low-resolution palm image in different directions to form the valley feature, and then define a matching score to measure the similarity of the valley features. The experimental results shows that the proposed approach can effectively discriminate palmprints and can obtain about 98% accuracy in palmprint verification. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Proceedings of the 2005 International Conference on Machine Learning and Cybernetics : August 18-21, 2005, Guangzhou, China, p. 4881-4885 | - |
| dcterms.issued | 2005 | - |
| dc.identifier.scopus | 2-s2.0-28444454517 | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
| dc.description.pubStatus | Published | en_US |
| Appears in Collections: | Conference Paper | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| valley-features_05.pdf | 580.2 kB | Adobe PDF | View/Open |
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