Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/1184
Title: | Palmprint recognition using valley features | Authors: | Wu, X Wang, K Zhang, DD |
Issue Date: | 2005 | Source: | Proceedings of the 2005 International Conference on Machine Learning and Cybernetics : August 18-21, 2005, Guangzhou, China, p. 4881-4885 | 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. | Keywords: | Biometrics Palmprint recognition Valley feature Morphological operator |
Publisher: | IEEE | ISBN: | 0-7803-9091-1 | 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. 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. |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
valley-features_05.pdf | 580.2 kB | Adobe PDF | View/Open |
Page views
154
Last Week
1
1
Last month
Citations as of Sep 8, 2024
Downloads
191
Citations as of Sep 8, 2024
SCOPUSTM
Citations
10
Last Week
0
0
Last month
0
0
Citations as of Jun 21, 2024
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.