Versatile and Economical Acquisition Setup for Dorsa Palm Vein Authentication

AbstractVarious biometrics were employed in many applications for security purposes, amongst palm vein biometrics is one of the best methods for unique identification of a person owing to the indestructible quality of the inner vein structures. In this paper, we have proposed our own setup for capturing vein structures of human dorsal palm using a web camera modified into a near infrared camera. The illumination for capturing images is provided with the help of 30 Infrared LEDs. The objective of this paper is to produce a versatile and an economical way for obtaining vein images rather than using a high priced Near Infrared Camera and can easily deployed in any small scale applications. This setup can be used to acquire finger veins too simultaneously. We have modified the web camera by removing the infrared filter present in it and replacing it with a visible light filter. The quality and performance of the newly acquired samples are tested with two different feature extraction methods namely Correlation filter and Speeded Up Robust Features (SURF) algorithm. Correlation method has obtained very good results than SURF in identifying the genuine samples

An Efficient Vein Pattern-based Recognition System

This paper presents an efficient human recognition system based on vein pattern from the palma dorsa. A new absorption based technique has been proposed to collect good quality images with the help of a low cost camera and light source. The system automatically detects the region of interest from the image and does the necessary preprocessing to extract features. A Euclidean Distance based matching technique has been used for making the decision. It has been tested on a data set of 1750 image samples collected from 341 individuals. The accuracy of the verification system is found to be 99.26% with false rejection rate (FRR) of 0.03%.Comment: IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 8 No. 1, April 2010, USA. ISSN 1947 5500, http://sites.google.com/site/ijcsis

A Hand-Based Biometric Verification System Using Ant Colony Optimization

This paper presents a novel personal authentication system using hand-based biometrics, which utilizes internal (beneath the skin) structure of veins on the dorsal part of the hand and the outer shape of the hand. The hand-vein and the hand-shape images can be simultaneously acquired by using infrared thermal and digital camera respectively. A claimed identity is authenticated by integrating these two traits based on the score-level fusion in which four fusion rules are used for the integration. Before their fusion, each modality is evaluated individually in terms of error rates and weights are assigned according to their performance. In order to achieve an adaptive security in the proposed bimodal system, an optimal selection of fusion parameters is required. Hence, Ant Colony Optimization (ACO) is employed in the bimodal system to select the weights and also one out of the four fusion rules optimally for the adaptive fusion of the two modalities to meet the user defined security levels. The databases of hand-veins and the hand-shapes consisting of 150 users are acquired using the peg-free imaging setup. The experimental results show genuine acceptance rate (GAR) of 98% at false acceptance rate (FAR) of 0.001% and the system has the potential for any online personal authentication based application.

Vein Pattern Extraction Using Near Infrared Imaging for Biometric Purposes

Biomedical verification has been broadly examined for many years and pulled in much consideration because of its huge potential security application. Vein is less prone to damage and almost improbable to copy than any other physiological as well as behavioural biometric features such as fingerprint, iris, face and voice recognition. This paper proposes an efficient vein extraction method on low quality vein images taken by a camera absorbing near infrared light (NIR camera). At first, the image is contrast enhanced using contrast limited adaptive histogram equalization (CLAHE); secondly, local threshold method is applied on small blocks of the image followed by several morphological operations such as fill, erosion, dilation, clean and bridge, performed sequentially, for better accuracy. Experimental results obtained for extraction show that the proposed method can reap better results with reduced complexity. After extraction, matching of the test image with the template images stored in the database are matched using minutiae (point-to-point pattern). An orientation detector which filters out missing or unnecessary or unnatural spurious minutiae pairings while simultaneously using path or ridge orientations to increase performance and similarity score calculation. Thus the obtained processed images can be used in biometric purposes which in turn enhances the security of the syste

An Analytical Survey on Vein Pattern Recognition

Biometric is term of science to identify a person identity using their physiological features. Currently, vein pattern recognition has attracted the attention of the technology and industry all over the world. A vein is network of blood vessels under the skin of an individual. The vascular pattern is different for every person in the same part or region of the body. It is stable till very long age. As the veins are underneath the skin it is very difficult for intruder or forger to copy the feature. This uniqueness and strong immunity from intruders make it more potent biometric system which avails us secure features for individual identity verification. This paper involves the description of vein pattern recognition, its requirement and its importance in biometric system. Different feature extraction algorithms are reviewed as independent component analysis, principal component analysis method. For classification in vein pattern recognition we have reviewed support vector machine and neural network techniques. Parameters are described based on which results are computed like true positive, false positive, true negative, false negative, accuracy and precision