Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25046
Title: A new approach to personal identification in large databases by hierarchical palmprint coding with multi-features
Authors: You, J 
Kong, WK
Zhang, D 
Cheung, KH
Issue Date: 2004
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2004, v. 3072, p. 739-745 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: This paper presents a new approach to personal identification using palmprints. To tackle the key issues such as feature extraction, representation, indexing, similarity measurement and fast search for the best match, we propose a hierarchical multi-feature coding scheme to facilitate coarse-to-fine matching for efficient and effective palmprint verification and identification in a large database. In contrast to the existing systems that employ a fixed mechanism for feature extraction and similarity measurement, we extract multiple features and adopt different matching criteria at different levels to achieve high performance by coarse-to-fine guided search. Our experimental results demonstrate the feasibility and effectiveness of the proposed method.
URI: http://hdl.handle.net/10397/25046
ISSN: 0302-9743
EISSN: 1611-3349
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