Journal
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
Volume 30, Issue 2, Pages 468-481Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSVT.2019.2890835
Keywords
Palmprint recognition; exponential and Gaussian fusion model; direction binary pattern; discriminant direction representation
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Funding
- National Natural Science Foundation of China [61702110, 61673175, 61602540]
- Shenzhen Municipal Science and Technology Innovation Council [JCYJ20170811155725434]
- University of Macau Multi-Year Research Grant [MYRG2018-00053-FST]
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Direction-based methods are the most powerful and popular palmprint recognition methods. However, there is no existing work that completely analyzes the essential differences among different direction-based methods and explores the most discriminant direction representation of a palmprint. In this paper, we attempt to establish the connection between the direction feature extraction model and the discriminability of direction features, and we propose a novel exponential and Gaussian fusion model (EGM) to characterize the discriminative power of different directions. The EGM can provide us with a new insight into the optimal direction feature selection of palmprints. Moreover, we propose a local discriminant direction binary pattern (LDDBP) to completely represent the direction features of a palmprint. Guided by the EGM, the most discriminant directions can be exploited to form the LDDBP-based descriptor for palmprint representation and recognition. Extensive experiment results conducted on four widely used palmprint databases demonstrate the superiority of the proposed LDDBP method over the state-of-the-art direction-based methods.
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