Abstract
2-D palmprint has been recognized as an effective biometric identifier in the past decade. Recently, 3-D palmprint recognition was proposed to further improve the performance of palmprint systems. This paper presents a simple yet efficient scheme for 3-D palmprint recognition. After calculating and enhancing the mean-curvature image of the 3-D palmprint data, we extract both line and orientation features from it. The two types of features are then fused at either score level or feature level for the final 3-D palmprint recognition. The experiments on The Hong Kong Polytechnic University 3-D palmprint database, which contains 8000 samples from 400 palms show that the proposed feature extraction and fusion methods lead to promising performance.
Original language | English |
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Article number | 5551238 |
Pages (from-to) | 274-279 |
Number of pages | 6 |
Journal | IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews |
Volume | 41 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Mar 2011 |
Keywords
- 3-D palmprint identification
- biometrics
- feature fusion
- mean curvature
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Information Systems
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering