Person Authentication System Research Articles

Robust palmprint verification using 2D and 3D features

This paper presents a new personal authentication system that simultaneously exploits 2D and 3D palmprint features. The objective of our work is to improve accuracy and robustness of existing palmprint authentication systems using 3D palmprint features. The proposed multilevel framework for personal authentication efficiently utilizes the robustness (against spoof attacks) of the 3D features and the high discriminating power of the 2D features. The developed system uses an active stereo technique, structured light, to simultaneously capture 3D image or range data and a registered intensity image of the palm. The surface curvature feature based method is investigated for 3D palmprint feature extraction while Gabor feature based competitive coding scheme is used for 2D representation. We comparatively analyze these representations for their individual performance and attempt to achieve performance improvement using the proposed multilevel matcher that utilizes fixed score level combination scheme to integrate information. Our experiments on a database of 108 subjects achieved significant improvement in performance with the integration of 3D features as compared to the case when 2D palmprint features alone are employed. We also present experimental results to demonstrate that the proposed biometric system is extremely difficult to circumvent, as compared to the currently proposed palmprint authentication approaches in the literature.

USER AUTHENTICATION USING FUSION OF FACE AND PALMPRINT

This paper presents a new method of personal authentication using face and palmprint images. The facial and palmprint images can be simultaneously acquired by using a pair of digital camera and integrated to achieve higher confidence in personal authentication. The proposed method of fusion uses a feed-forward neural network to integrate individual matching scores and generate a combined decision score. The significance of the proposed method is more than improving performance for bimodal system. Our method uses the claimed identity of users as a feature for fusion. Thus the required weights and bias on individual biometric matching scores are automatically computed to achieve the best possible performance. The experimental results also demonstrate that Sum, Max, and Product rule can be used to achieve significant performance improvement when consolidated matching scores are employed instead of direct matching scores. The fusion strategy used in this paper outperforms even its existing facial and palmprint modules. The performance indices for personal authentication system using two-class separation criterion functions have been analyzed and evaluated. The method proposed in this paper can be extended for any multimodal authentication system to achieve higher performance.

Design of Complex BPF with Automatic Digital Tuning Circuit for Low-IF Receivers

This paper describes the architecture and implementations of an automatic digital tuning circuit for a complex bandpass filter (BPF) in a low-power and low-cost transceiver for applications such as personal authentication and wireless sensor network systems. The architectural design analysis demonstrates that an active RC filter in a low-IF architecture can be at least 47.7% smaller in area than a conventional gm-C filter; in addition, it features a simple implementation of an associated tuning circuit. The principle of simultaneous tuning of both the center frequency and bandwidth through calibration of a capacitor array is illustrated as based on an analysis of filter characteristics, and a scalable automatic digital tuning circuit with simple analog blocks and control logic having only 835 gates is introduced. The developed capacitor tuning technique can achieve a tuning error of less than ±3.5% and lower a peaking in the passband filter characteristics. An experimental complex BPF using 0.18µm CMOS technology can successfully reduce the tuning error from an initial value of -20% to less than ±2.5% after tuning. The filter block dimensions are 1.22mm × 1.01mm; and in measurement results of the developed complex BPF with the automatic digital tuning circuit, current consumption is 705µA and the image rejection ratio is 40.3dB. Complete evaluation of the BPF indicates that this technique can be applied to low-power, low-cost transceivers.

Finger-based personal authentication: a comparison of feature-extraction methods based on principal component analysis, most discriminant features and regularised-direct linear discriminant analysis

In this study, feature-extraction methods based on principal component analysis, most discriminant features, and regularised-direct linear discriminant analysis (RD-LDA) are tested and compared in an experimental finger-based personal authentication system. The system is multimodal and based on features extracted from eight regions of the hand: four fingerprints (the prints of the finger tips) and four digitprints (the prints of the fingers between the first and third phalanges). All of the regions are extracted from one-shot grey-level images of the palmar surface of four fingers of the right hand. The identification and verification experiments were conducted on a database consisting of 1840 finger images (184 people). The experiments showed that the best results were obtained with the RD-LDA-based feature-extraction method−99.98% correct identification for 920 tests and an equal error rate of 0.01% for 64170 verification tests.

Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach

Biometric based systems for individual authentication are increasingly becoming indispensable for protecting life and property. They provide ways for uniquely and reliably authenticating people, and are difficult to counterfeit. Biometric based authenticity systems are currently used in governmental, commercial and public sectors. However, these systems can be expensive to put in place and often impose physical constraint to the users. This paper introduces an inexpensive, powerful and easy to use hand geometry based biometric person authentication system using neural networks. The proposed approach followed to construct this system consists of an acquisition device, a pre-processing stage, and a neural network based classifier. One of the novelties of this work comprises on the introduction of hand geometry's related, position independent, feature extraction and identification which can be useful in problems related to image processing and pattern recognition. Another novelty of this research comprises on the use of error correction codes to enhance the level of performance of the neural network model. A dataset made of scanned images of the right hand of fifty different people was created for this study. Identification rates and Detection Cost Function (DCF) values obtained with the system were evaluated. Several strategies for coding the outputs of the neural networks were studied. Experimental results show that, when using Error Correction Output Codes (ECOC), up to 100% identification rates and 0% DCF can be obtained. For comparison purposes, results are also given for the Support Vector Machine method.

Processing the Shadow of a Hand Image

In the field of the personal authentication system, types of hands are popularly used to certificate the identity of a person. There is an important part in the hand-shape recognition system. That is how to take the photographs of hands. Whether you use a camera or a scanner to take a photograph, there exist some shadow parts around a hand image. As for this part, to judge whether the shadow is true or it is just the hand plays an important role to improve the recognition rate. Actually if we can judge the range of the shadow of the hand image clearly we can raise the probability of the certification. In this paper we focus on the shadow part of hand images. We propose some algorithm to convert an original image into a better image to handle the hand-shape. Firstly, we make the convert the input color image into a grayscale image, then we extract the outline by using Fourier transform, and the true outline of the hand will be determined. Now the recognition methods using biometrics are spread in the world, we believe our project of processing the shadow part will be useful to the recognition system.

4-10 本人認証システムにおける等濃線分布の作成方法に関する検討(第4部門 ヒューマンインフォメーション)

4-10 本人認証システムにおける等濃線分布の作成方法に関する検討(第4部門 ヒューマンインフォメーション)

The Improvement of Extraction Method for Noncontact Fingerprint Authentication

In personal authentication systems (PAS) using fingerprints, there is a decline in authentication accuracy because of the dirt on the contact surface with the present input equipment. We have already examined the possibility of noncontact fingerprint authentication to address these problems. In this paper, we propose an improvement for the extraction of a fingerprint and a compensation method for a rotation error for the noncontact fingerprint authentication. In the preprocessing, the compensation of a rotation error from two dimensions to three dimensions. In the proposed rotation compensation technique, the front view and side view of a fingertip are used. Moreover, we examined the cause of decreasing the quality of the principal line in our technique. The extraction error is caused by the change in a red component of the skin caused in blood circulation. Then we propose the technique for correcting an input image by using the approximation image obtained by the wavelet transform. As a result of the experiment, the quality of the output image has improved greatly that the extraction errors of the principal lines are decreased.

The Fusion of Two User-friendly Biometric Modalities: Iris and Face

In this paper, we present the biometric authentication system based on the fusion of two user-friendly biometric modalities: Iris and Face. Using one biometric feature can lead to good results, but there is no reliable way to verify the classification. To achieve robust identification and verification we are combining two different biometric features. We specifically apply 2-D discrete wavelet transform to extract the feature sets of low dimensionality from the iris and face. And then to obtain Reduced Joint Feature Vector (RJFV) from these feature sets, Direct Linear Discriminant Analysis (DLDA) is used in our multimodal system. This system can operate in two modes: to identify a particular person or to verify a person's claimed identity. Our results for both cases show that the proposed method leads to a reliable person authentication system.

Application of an Array-structured Sensor and Modified Verification Algorithms to the Personal Authentication System using Tactile Information

In recent years, security problems have been concerned in the well-developed information society. Although personal authentication methods such as password-systems and key-systems are used widely, various problems are pointed out. Therefore, biometric authentication which uses the information of physical or behavioral characteristics is becoming important technology as a personal authentication. In the present study, a new biometric authentication system using finger-friction is proposed. This system utilizes tactile information of which recording and playing technologies have not been established, in contrast to visual and auditory information. Moreover, it is using both physical characteristics related to the 3-D shapes of fingerprints and behavioral characteristics related to the way of rubbing. In the present system, an array-structured sensor generates 12-channel frictional signals which are distinctive to an individual when a subject rubs it with a finger. In the present paper, 100 samples of frictional signals are used for verification which is based on dynamic programming. As a result, improvements of verification algorithm make it possible to reduce False Rejection Rate (FRR) and False Acceptance Rate (FAR) to 1% and 0.05% respectively.

Multimodal System by Data Fusion and Synergetic Neural Network

In this paper, we present the multimodal system based on the fusion of two user-friendly biometric modalities: Iris and Face. In order to reach robust identification and verification we are going to combine two different biometric features. we specifically apply 2-D discrete wavelet transform to extract the feature sets of low dimensionality from iris and face. And then to obtain Reduced Joint Feature Vector(RJFV) from these feature sets, Direct Linear Discriminant Analysis (DLDA) is used in our multimodal system. In addition, the Synergetic Neural Network(SNN) is used to obtain matching score of the preprocessed data. This system can operate in two modes: to identify a particular person or to verify a person's claimed identity. Our results for both cases show that the proposed method leads to a reliable person authentication system.

Fusion of multiple fingerprint matchers by single-layer perceptron with class-separation loss function

In this paper, a perceptron-based algorithm for fusion of multiple fingerprint matchers is presented. The person to be identified submits to the personal authentication system her/his fingerprint and claimed identity. Multiple fingerprint matchers provide a set of verification scores, that are then fused by a single-layer perceptron with class-separation loss function. Weights of such perceptron are explicitly optimised to increase the separation between genuine users and impostors (i.e., unauthorized users). Reported experiments show that such modified perceptron allows improving the performances and the robustness of the best individual fingerprint matcher, and outperforming some commonly used fusion rules.

Proposal on personal identifiers generated from the STR information of DNA

The individual differences in the repeat count of several bases, short tandem repeat (STR), among all of the deoxyribonucleic acid (DNA) base sequences, can be used as unique DNA information for a personal identification (ID). We propose a method to generate a personal identifier (hereafter referred to as a “DNA personal ID”) by specifying multiple STR locations (called “loci”) and then sequencing the repeat count information. We also conducted a validation experiment to verify the proposed principle based on actual DNA data. We verified that the matching probability of DNA personal IDs becomes exponentially smaller, to about 10-n, as n stages of loci are used and that no correlation exists among the loci. Next, we considered the various issues that will be encountered when applying DNA personal IDs to information security systems, such as biometric personal authentication systems.

Personal authentication using palm-print features

Biometrics-based authentication is a verification approach using the biological features inherent in each individual. They are processed based on the identical, portable, and arduous duplicate characteristics. In this paper, we propose a scanner-based personal authentication system by using the palm-print features. It is very suitable in many network-based applications. The authentication system consists of enrollment and verification stages. In the enrollment stage, the training samples are collected and processed by the pre-processing, feature extraction, and modeling modules to generate the matching templates. In the verification stage, a query sample is also processed by the pre-processing and feature extraction modules, and then is matched with the reference templates to decide whether it is a genuine sample or not. The region of interest (ROI) for each sample is first obtained from the pre-processing module. Then, the palm-print features are extracted from the ROI by using Sobel and morphological operations. The reference templates for a specific user are generated in the modeling module. Last, we use the template-matching and the backpropagation neural network to measure the similarity in the verification stage. Experimental results verify the validity of our proposed approaches in personal authentication.

Evaluation of the security against tamper resistance attacks on person authentication system by using the IC-cards and fingerprint recognition technology

Evaluation of the security against tamper resistance attacks on person authentication system by using the IC-cards and fingerprint recognition technology

W4 生体認識技術の開発動向 : 生体認識技術の標準化および指紋認証システム

This paper describes two themes about biometric authentication techniques. Firstly, this paper describes a standardization of testing and evaluating for fingerprint verification. We had been commissioned to consider the standardization by the Information-technology promotion Agency (IPA) of Japan in 1999. The Standardization composites of two guidelines, (1) Guidelines for accuracy test, and (2) Guidelines for requirements decision. System-integrators and users can compare some vender's authentication products through these guidelines. Secondly, this paper presents a proposal of a personal authentication system via the open network by using a smart card including a fingerprint template with the digital signature such as X.509. We developed a prototype authentication system in where verification process is operated in the smart card. The proposed system can realize a high security and easy authentication on the public key infrastructure.

SESAM: A biometric person identification system using sensor fusion

In the present paper we describe the person authentication system SESAM. Person identification and verification still is a very difficult task. Using one biometric feature, i.e. the photograph or the sound of the voice, leads to good results, but there is no reliable way to verify the classification. In order to reach robust identification and verification we are combining three different biometric cues. These cues are dynamic, i.e., the sound of the voice and the lip motion, and static, i.e., the fixed image of the face. Each branch is preprocessed and classified separately and the results are combined, e.g., in a 2-from-3 manner. The recognition of persons may be used for pure identification or can be varied to a verification system. For both cases we have done a field test to show that this approach leads to a reliable person authentication system.