Palm Vein Recognition Research Articles

A novel biometric system based on palm vein image

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.

手掌静脉识别典型波长选择

手掌静脉识别典型波长选择

Online joint palmprint and palmvein verification

As a unique and reliable biometric characteristic, palmprint verification has achieved a great success. However, palmprint alone may not be able to meet the increasing demand of highly accurate and robust biometric systems. Recently, palmvein, which refers to the palm feature under near-infrared spectrum, has been attracting much research interest. Since palmprint and palmvein can be captured simultaneously by using specially designed devices, the joint use of palmprint and palmvein features can effectively increase the accuracy, robustness and anti-spoof capability of palm based biometric techniques. This paper presents an online personal verification system by fusing palmprint and palmvein inforA fast palmprint and palmvein recognition systemA fast palmprint and palmvein recognition system quality can vary much, a dynamic fusion scheme which is adaptive to image quality is developed. To increase the anti-spoof capability of the system, a liveness detection method based on the image property is proposed. A comprehensive database of palmprint–palmvein images was established to verify the proposed system, and the experimental results demonstrated that since palmprint and palmvein contain complementary information, much higher accuracy could be achieved by fusing them than using only one of them. In addition, the whole verification procedure can be completed in 1.2 s, which implies that the system can work in real time.

An Enhanced Palm Vein Recognition System Using Multi-level Fusion of Multimodal Features and Adaptive Resonance Theory

An improved palm vein recognition system using multimodal features and neural network classifier has been developed and presented in this paper. The effects of fusion of multiple features at various levels have been demonstrated. The shape and texture features have been considered for recognition of authenticated users and it is validated using neural network classifier. The recognition accuracy of the proposed system has been compared with the existing techniques. It is found that the recognition accuracy is 99.61% when the multimodal features fused at matching score level. This proposed multimodal palm vein recognition system is expected to provide reliable security.

An Improved Multimodal Palm Vein Recognition System Using Shape and Texture Features

1 Abstract—Multimodal analysis of palm vein for biometric authentication has been carried out and presented in this paper. The proposed system is based on parallel mode multiple feature analysis and multilevel fusion. The directional information of the palm vein has been considered for better analysis. The developed multimodal palm vein recognition system has very low value of matching error rate and false acceptance or rejection rate. Index Terms—Palm vein recognition, Multimodal Biometrics, Feature subset selection, ASFFS, FAR, FRR