A Method for Obtaining Electronic Voting Systems based Voter Confidentiality and Voting Accuracy

A Voting is common in our daily life, from electing president to electing committee. A complete electronic voting scheme suitable for all kinds of voting with safe guaranty where the voter?s privacy can be protected. Fingerprint system security have been investigated, including the use of fake fingerprints for masquerading identity, the problem of fingerprint alteration or obfuscation has received very little attention. Fingerprint image quality assessment software (e.g., NFIQ) cannot always detect altered fingerprints since the implicit image quality due to alteration may not change significantly. The main contributions of this Research are-1.Compiling case studies of incidents where individuals were found to have altered their fingerprints for circumventing AFIS.2.Identifying the damages of fingerprint alteration on the accuracy of a commercial fingerprint matcher.3.Classifying the alterations into three major categories and suggesting possible countermeasures.4.Developing a technique to automatically detect altered fingerprints based on analyzing orientation field and minutiae distribution.5.Evaluating the proposed technique and the NFIQ algorithm on a big database of altered fingerprints provided by a law enforcement agency. Experimental results show the feasibility of the proposed approach in detecting altered fingerprints and highlight the need to further pursue this problem

A Dorsal Hand Vein Recognition-based on Local Gabor Phase Quantization with Whitening Transformation

The hand vein pattern is a biometric feature in which the actual pattern is the shape of the vein network and its characteristics are the vein features. This paper investigates a new approach for dorsal hand vein pattern identification from grey level dorsal hand vein information. In this study Gabor filter quadrature pair is employed to compute locally in a window for every pixel position to extract the phase information. The phases of six frequency coefficients are quantized and it is used to form a descriptor code for the local region. These local descriptors are decorrelated using whitening transformation and a histogram is generated for every pixel which describes the local pattern.  Experiments are evaluated on North China University of Technology  dorsal hand vein image dataset with minimum distance classifier and the results are analyzed for recognition rate, run time and equal error rate. The proposed method gives 100 per cent recognition rate and 1 per cent EER for fusion of both left and right hands.Defence Science Journal, 2014, 64(2), pp. 159-167. DOI: http://dx.doi.org/10.14429/dsj.64.465

Dorsal Hand Vein Identification using Transfer Learning from AlexNet

Dorsal hand vein pattern is a highly secured biometric system that has been used in many applications due to its non-contact attributes. Prior studies focused on investigation of different deep networks for hand vein classification task using different training parameters. It is the aim of this study to propose the use of systematic fine-tuning system for identifying the best parameters value for enhanced model learning efficiency. In this study, pre-trained AlexNet was trained using Bosphorus hand vein database for identification of 100 users. The experiments were carried out using original images, and preprocessed (cropped) images for comparison. The testing accuracies of these datasets were compared following tuning of training parameters, namely training and testing split ratio, number of epochs, mini-batch size and initial learning rate. It was observed that the testing accuracy of the model trained using cropped images is higher than that using the original images. The model from preprocessed dataset shows a good testing accuracy of 96 % using a split ratio of 90:10, epoch 50, mini-batch-size of 10 and an initial learning rate of 0.0001. The performance of our trained model is more superior than many reported results in the field. In future, the performance of this classification system may be further enhanced with automatic search of parameters for improved model training efficiency

An Efficient Dorsal Hand Vein Recognition Based on Firefly Algorithm

Biometric technology is an efficient personal authentication andidentification technique. As one of the main-stream branches, dorsal handvein recognition has been recently attracted the attention of researchers. It is more preferable than the other types of biometrics becuse it’s impossible to steal or counterfeit the patterns and the pattern of the vessels of back of the hand is fixed and unique with repeatable biometric features. Also, the recent researches have been obtained no certain recognition rate yet becuse of the noises in the imaging patterns, and impossibility of Dimension reducing because of the non-complexity of the models, and proof of correctness of identification is required. Therefore, in this paper, first, the images of blood vessels on back of the hands of people is analysed, and after pre-processing of images and feature extraction (in the intersection between the vessels) we began to identify people using firefly clustering algorithms. This identification is done based on the distance patterns between crossing vessels and their matching place. The identification will be done based on the classification of each part of NCUT data set and it consisting of 2040 dorsal hand vein images. High speed in patterns recognition and less computation are the advantages of this method. The recognition rate of this method ismore accurate and the error is less than one percent. At the end thecorrectness percentage of this method (CLU-D-F-A) for identification iscompared with other various algorithms, and the superiority of the proposed method is proved.DOI:http://dx.doi.org/10.11591/ijece.v3i1.176

A Dynamic Biometric Authentication Algorithm for Near-Infrared Palm Vascular Patterns

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Authentication of damaged hand vein patterns by modularization

As security is a major concern in present times, reliable authentication systems are in great demand. A biometric trait like the vascular pattern on the back of the hand of a person is unique and secure. A biometric system working on this principle often fails to authenticate a person either because of the varying hand posture or due to an injury altering the vein pattern. In this paper we propose an authentication system to overcome these disadvantages by modularizing the image and then comparing the features. This method of authentication reduces the False Rejection Ratio (FRR) and also False Acceptance Ratio (FAR) of the system

Handbook of Vascular Biometrics

This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers