Palm Vein Image Research Articles

Extracting Palm Vein Patterns Based on Low-Cost Devices

Abstract. In order to figure out the low-cost imaging apparatus’ problems, such as the low image contrast, the indistinct vein characteristics, which are affected by the photoelectric noise during the collection process. In this paper, the vein imaging principle is discussed, and a low-cost collection device is designed, at the same time a two-dimensional multi-directional Gaussian filter is constructed to achieve the enhancement of low quality palm vein image, and the Local Dynamic Threshold Segmentation Method (Niblack) is adopted to extract vein characteristics. The results show that this method is able to extract distinct vein characteristics, and also can provide reliable characteristics basis for palm vein recognition system.

Palm vein recognition using adaptive Gabor filter

Vein pattern recognition is one of the newest biometric techniques researched today. One of the reliable and robust personal identification authentication approaches using palm vein patterns is presented in this paper. In our work, we consider the palm vein as a piece of texture and apply texture-based feature extraction techniques to palm vein authentication. A 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. However, Gabor filter has many potential parameter combinations to use, and it is a common practice now to use multiple Gabor filters or to determine desired single combination by experience. The overall aim of this work is to discuss the optimization algorithm that determines the best parameter values of a single Gabor filter for palm vein recognition. In order to obtain effective pattern of palm vascular, we proposed an innovative and robust adaptive Gabor filter method 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 this method is rapid enough for real-time palm vein recognition. Experimental results demonstrate that our proposed approach is feasible and effective in palm vein recognition.

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.

Palm vein image enhancement based on mirror extended curvelet transform

A novel low contrast IR image enhancement method based on multi-scale mirror-extended curvelet transform was proposed to solve the problems of the palm vein IR images,such as low SNR(Signal/Noise) and low grayscale contrast as the results of incorrect feature extraction of palm vein.Based on the analysis of the strong relationship between multi-scale curvelet coefficients and different scales of detailed vein features,coefficients of high frequency subbands,where most of the noises and few features located,were set zero.The coefficients of middle frequency subbands,where most of the features concentrated,were nonlinearly enhanced during the denoising process.The coefficients of low frequency subbands who determined the global grayscale contrast were stretched.Experimental results show that the proposed method can efficiently enhance the features of low contrast palm vein IR images with increased evaluation indexes such as SNR and Entropy.By this method the features of vein edges are better preserved and more smoothly emphasized than enhancement methods of biorthogonal wavelet and histogram equalization.

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.

WAVELET-BASED PALM VEIN RECOGNITION SYSTEM

A new personal recognition system using the palm vein pattern is presented in this article. It is the first time that the palm vein pattern is used for personal recognition. The texture feature of palm vein is extracted by wavelet decomposition. With our palm vein image database, we employed the nearest neighbor (NN) classifier to test the performance of the system. Experimental results show that the algorithm based on wavelet transform can reach a correct recognition rate (CRR) of 98.8%.

Person recognition by fusing palmprint and palm vein images based on "Laplacianpalm" representation

Unimodal analysis of palmprint and palm vein has been investigated for person recognition. One of the problems with unimodality is that the unimodal biometric is less accurate and vulnerable to spo...

Person recognition by fusing palmprint and palm vein images based on “Laplacianpalm” representation

Unimodal analysis of palmprint and palm vein has been investigated for person recognition. One of the problems with unimodality is that the unimodal biometric is less accurate and vulnerable to spoofing, as the data can be imitated or forged. In this paper, we present a multimodal personal identification system using palmprint and palm vein images with their fusion applied at the image level. The palmprint and palm vein images are fused by a new edge-preserving and contrast-enhancing wavelet fusion method in which the modified multiscale edges of the palmprint and palm vein images are combined. We developed a fusion rule that enhances the discriminatory information in the images. Here, a novel palm representation, called “Laplacianpalm” feature, is extracted from the fused images by the locality preserving projections (LPP). Unlike the Eigenpalm approach, the “Laplacianpalm” finds an embedding that preserves local information and yields a palm space that best detects the essential manifold structure. We compare the proposed “Laplacianpalm” approach with the Fisherpalm and Eigenpalm methods on a large data set. Experimental results show that the proposed “Laplacianpalm” approach provides a better representation and achieves lower error rates in palm recognition. Furthermore, the proposed multimodal method outperforms any of its individual modality.