Palmprint verification based on principal lines |
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| Authors: | De-Shuang Huang Wei Jia David Zhang |
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| Affiliation: | 1. Intelligent Computation Laboratory, Hefei Institute of Intelligent Machines, Chinese Academy of Science, P.O. Box 1130, Hefei, Anhui 230031, China;2. Department of Automation, University of Science and Technology of China, Hefei 230027, China;3. Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Hong Kong;1. College of Information Engineering, Qingdao University, Qingdao 266071, China;2. Department of Computing, Curtin University, Perth, WA 6102, Australia;3. School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China;4. School of Communications and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;1. LAMEL Lab., University of Jijel, BP 98 Ouled Aissa, Jijel 18000, Algeria;2. LIASD research Lab., Department of Computer Science, University of Paris 8, 2 rue de la Liberté 93526 Saint-Denis, France;3. Department of Computer Science and Digital Technologies, University of Northumbria, Newcastle upon Tyne NE2 1XE, UK;1. College of Information Engineering, Qingdao University, Qingdao 266071, China;2. Department of Computing, Curtin University, Perth WA 6102, Australia;3. School of Communications and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;1. School of Computer and Communication Engineering, Universiti Malaysia Perlis, Perlis, Malaysia;2. School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom;1. Bio-Computing Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China;2. School of Software, East China Jiaotong University, Nanchang, China;3. Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China |
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| Abstract: | In this paper, we propose a novel palmprint verification approach based on principal lines. In feature extraction stage, the modified finite Radon transform is proposed, which can extract principal lines effectively and efficiently even in the case that the palmprint images contain many long and strong wrinkles. In matching stage, a matching algorithm based on pixel-to-area comparison is devised to calculate the similarity between two palmprints, which has shown good robustness for slight rotations and translations of palmprints. The experimental results for the verification on Hong Kong Polytechnic University Palmprint Database show that the discriminability of principal lines is also strong. |
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