Image Representation Using 2D Gabor Wavelets
IEEE Transactions on Pattern Analysis and Machine Intelligence
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Segmentation using 2-D Gabor Elementary Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Online Palmprint Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gabor-Based Kernel PCA with Fractional Power Polynomial Models for Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Minutiae feature analysis for infrared hand vein pattern biometrics
Pattern Recognition
A new palm vein matching method based on ICP algorithm
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
Radiation optimization and image processing algorithms in the identification of hand vein patterns
Computer Standards & Interfaces
Palm vein extraction and matching for personal authentication
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Biometric verification using thermal images of palm-dorsa vein patterns
IEEE Transactions on Circuits and Systems for Video Technology
Human Identification Using Palm-Vein Images
IEEE Transactions on Information Forensics and Security
An improved method of identification based on thermal palm vein image
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Hi-index | 0.10 |
Vein pattern recognition is one of the newest biometric techniques researched today. In this paper, one of the reliable and robust personal identification authentication approaches using palm vein patterns is presented. We consider the palm vein as a piece of texture and apply texture-based feature extraction techniques to palm vein authentication in our work. A 2-D Gabor filter provides the optimized resolution in both the spatial and frequency domains, thus it is a basis for extracting local features in the palm vein recognition. In order to obtain effective pattern of palm vascular, we proposed an innovative and robust directional coding technique to encode the palm vein features in bit string representation. The bit string representation, called VeinCode, offers speedy template matching and enables more effective template storage and retrieval. The similarity of two VeinCodes is measured by normalized hamming distance. A total of 4140 palm vein images were collected form 207 persons to verify the validity of the proposed palm vein recognition approach. High accuracy has been obtained by the proposed method and the speed of the method is rapid enough for real-time palm vein recognition. Experimental results demonstrate that our proposed approach is feasible and effective for palm vein recognition.