Online Palmprint Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ordinal Palmprint Represention for Personal Identification
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
A new use of the ridgelets transform for describing linear singularities in images
Pattern Recognition Letters
Palmprint verification based on principal lines
Pattern Recognition
Palmprint verification based on robust line orientation code
Pattern Recognition
An automated palmprint recognition system
Image and Vision Computing
Characterization of palmprints by wavelet signatures via directional context modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Personal recognition using hand shape and texture
IEEE Transactions on Image Processing
A note on computational intelligence methods in biometrics
International Journal of Biometrics
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As one of the most important biometrics features, palmprint with many strong points has significant influence on research. In this paper, we propose a novel method of palmprint feature extraction and identification using ridgelet transforms and rough sets. Firstly, the palmprints are first converted into the time-frequency domain image by ridgelet transforms without any further preprocessing such as image enhancement and texture thinning, and then feature extraction vector is conducted. Different features are used to lead a detection table. Then rough set is applied to remove the redundancy of the detection table. By this way, the length of conduction attribute is much shorter than that by traditional algorithm. Finally, the effectiveness of the proposed method is evaluated by the classification accuracy of SVM classifier. The experimental results show that the method has higher recognition rate and faster processing speed.