Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23157
Title: Palmprint verification using binary orientation co-occurrence vector
Authors: Guo, Z
Zhang, D 
Zhang, L 
Zuo, W
Keywords: Biometrics
Gabor filter
Orientation code
Palmprint recognition
Issue Date: 2009
Publisher: North-Holland
Source: Pattern recognition letters, 2009, v. 30, no. 13, p. 1219-1227 How to cite?
Journal: Pattern recognition letters 
Abstract: The development of accurate and robust palmprint verification algorithms is a critical issue in automatic palmprint authentication systems. Among various palmprint verification approaches, the orientation based coding methods, such as competitive code (CompCode), palmprint orientation code (POC) and robust line orientation code (RLOC), are state-of-the-art ones. They extract and code the locally dominant orientation as features and could match the input palmprint in real-time and with high accuracy. However, using only one dominant orientation to represent a local region may lose some valuable information because there are cross lines in the palmprint. In this paper, we propose a novel feature extraction algorithm, namely binary orientation co-occurrence vector (BOCV), to represent multiple orientations for a local region. The BOCV can better describe the local orientation features and it is more robust to image rotation. Our experimental results on the public palmprint database show that the proposed BOCV outperforms the CompCode, POC and RLOC by reducing the equal error rate (EER) significantly.
URI: http://hdl.handle.net/10397/23157
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/j.patrec.2009.05.010
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