3-D Palmprint Recognition With Joint Line and Orientation Features

Authors:
Wei Li;D. Zhang;Lei Zhang;Guangming Lu;Jingqi Yan
Affiliations:
Inst. of Image Process. & Pattern Recognition, Shanghai Jiao Tong Univ., Shanghai, China;-;-;-;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Year:
2011

Citing 0
Cited 3

A wavelet-based dominant feature extraction algorithm for palm-print recognition

Digital Signal Processing
A sparse representation method of bimodal biometrics and palmprint recognition experiments

Neurocomputing
2D and 3D palmprint information, PCA and HMM for an improved person recognition performance

Integrated Computer-Aided Engineering

Quantified Score

Hi-index	0.00

Visualization

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.