• Title/Summary/Keyword: Biometric Recognition System

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Hand Biometric Information Recognition System of Mobile Phone Image for Mobile Security (모바일 보안을 위한 모바일 폰 영상의 손 생체 정보 인식 시스템)

  • Hong, Kyungho;Jung, Eunhwa
    • Journal of Digital Convergence
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    • v.12 no.4
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    • pp.319-326
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    • 2014
  • According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

Face Recognition System Technologies for Authentication System - A Survey (인증시스템을 위한 얼굴인식 기술 : 서베이)

  • Hwang, Yooncheol;Mun, Hyung-Jin;Lee, Jae-Wook
    • Journal of Convergence Society for SMB
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    • v.5 no.3
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    • pp.9-13
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    • 2015
  • With the advance of ICT, the necessity of user authentication to verify the identity of an opponent online not face to face is increasing. The authentication, the basis of the security, is used in various fields. Because ID-based authentication has weaknesses in terms of stability and losses, two or more than two authentication tools are used in the place in which the security is important. Recently, biometric authentication rather than ID, OTP, SMS authentication has been an issue in terms of credibility and efficiency. As the fields applied to current biometric recognition technologies are increasing, the application of the biometric recognition is being used in various fields such as mobile payment system, intelligent CCTV, immigration inspection, and access control. As the biometric recognition, finger print, iris, retina, vein, and face recognition have been studied actively. This study is to inspect the current state of domestic and foreign standardization including understanding of the face recognition and the trend of technology.

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Human Iris Recognition using Wavelet Transform and Neural Network

  • Cho, Seong-Won;Kim, Jae-Min;Won, Jung-Woo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.178-186
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    • 2003
  • Recently, many researchers have been interested in biometric systems such as fingerprint, handwriting, key-stroke patterns and human iris. From the viewpoint of reliability and robustness, iris recognition is the most attractive biometric system. Moreover, the iris recognition system is a comfortable biometric system, since the video image of an eye can be taken at a distance. In this paper, we discuss human iris recognition, which is based on accurate iris localization, robust feature extraction, and Neural Network classification. The iris region is accurately localized in the eye image using a multiresolution active snake model. For the feature representation, the localized iris image is decomposed using wavelet transform based on dyadic Haar wavelet. Experimental results show the usefulness of wavelet transform in comparison to conventional Gabor transform. In addition, we present a new method for setting initial weight vectors in competitive learning. The proposed initialization method yields better accuracy than the conventional method.

A Study on the Development of Embedded Serial Multi-modal Biometrics Recognition System (임베디드 직렬 다중 생체 인식 시스템 개발에 관한 연구)

  • Kim, Joeng-Hoon;Kwon, Soon-Ryang
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.1
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    • pp.49-54
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    • 2006
  • The recent fingerprint recognition system has unstable factors, such as copy of fingerprint patterns and hacking of fingerprint feature point, which mali cause significant system error. Thus, in this research, we used the fingerprint as the main recognition device and then implemented the multi-biometric recognition system in serial using the speech recognition which has been widely used recently. As a multi-biometric recognition system, once the speech is successfully recognized, the fingerprint recognition process is run. In addition, speaker-dependent DTW(Dynamic Time Warping) algorithm is used among existing speech recognition algorithms (VQ, DTW, HMM, NN) for effective real-time process while KSOM (Kohonen Self-Organizing feature Map) algorithm, which is the artificial intelligence method, is applied for the fingerprint recognition system because of its calculation amount. The experiment of multi-biometric recognition system implemented in this research showed 2 to $7\%$ lower FRR (False Rejection Ratio) than single recognition systems using each fingerprints or voice, but zero FAR (False Acceptance Ratio), which is the most important factor in the recognition system. Moreover, there is almost no difference in the recognition time(average 1.5 seconds) comparing with other existing single biometric recognition systems; therefore, it is proved that the multi-biometric recognition system implemented is more efficient security system than single recognition systems based on various experiments.

Multimodal Biometric Recognition System using Real Fuzzy Vault (실수형 퍼지볼트를 이용한 다중 바이오인식 시스템)

  • Lee, Dae-Jong;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.4
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    • pp.310-316
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    • 2013
  • Biometric techniques have been widely used for various areas including criminal identification due to their reliability. However, they have some drawbacks when the biometric information is divulged to illegal users. This paper proposed multimodal biometric system using a real fuzzy vault by RN-ECC for protecting fingerprint and face template. This proposed method has some advantages to regenerate a key value compared with face or fingerprint based verification system having non-regenerative nature and to implement advanced biometric verification system by fusion of both fingerprint and face recognition. From the various experiments, we found that the proposed method shows high recognition rates comparing with the conventional methods.

Biometric verified authentication of Automatic Teller Machine (ATM)

  • Jayasri Kotti
    • Advances in environmental research
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    • v.12 no.2
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    • pp.113-122
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    • 2023
  • Biometric authentication has become an essential part of modern-day security systems, especially in financial institutions like banks. A face recognition-based ATM is a biometric authentication system, that uses facial recognition technology to verify the identity of bank account holders during ATM transactions. This technology offers a secure and convenient alternative to traditional ATM transactions that rely on PIN numbers for verification. The proposed system captures users' pictures and compares it with the stored image in the bank's database to authenticate the transaction. The technology also offers additional benefits such as reducing the risk of fraud and theft, as well as speeding up the transaction process. However, privacy and data security concerns remain, and it is important for the banking sector to instrument solid security actions to protect customers' personal information. The proposed system consists of two stages: the first stage captures the user's facial image using a camera and performs pre-processing, including face detection and alignment. In the second stage, machine learning algorithms compare the pre-processed image with the stored image in the database. The results demonstrate the feasibility and effectiveness of using face recognition for ATM authentication, which can enhance the security of ATMs and reduce the risk of fraud.

The implementation of Access Control System using Biometric System (Biometric System(fingerprint Reader)을 이용한 Access Control System 구현에 관한 연구)

  • 김광환;김영길
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.439-442
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    • 2003
  • In this paper, a system that implementation of Access Control System Using Biometric System. Biometrics is science which deals with verifying or recognizing using physiological or behavioral characteristic Access Control System uses Biometric system to make an access control system. Biometrics goes under the study of bio-recognition or bio-measurement. It is a technology or study that identifies individuals using one's Biometric character. Access control system is a system used to identify one's entrance and exit, personal management, and security. Access control system can be joined with Biometric system to produce easier use and more sufficient effects. Access control system using Wiegand (Data Format) signal output, can replace earlier RF Card systems and make an access control (security) system. It uses RS-232, Rs-422 or TCP/IP type communication with the computer so an embedded system can be controlled using the software.

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Performance Evaluation of Multimodal Biometric System for Normalization Methods and Classifiers (균등화 및 분류기에 따른 다중 생체 인식 시스템의 성능 평가)

  • Go, Hyoun-Ju;Woo, Na-Young;Shin, Yong-Nyuo;Kim, Jae-Sung;Kim, Hak-Il;Chun, Myung-Geun
    • Journal of KIISE:Software and Applications
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    • v.34 no.4
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    • pp.377-388
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    • 2007
  • In this paper, we propose a multi-modal biometric system based on face, iris and fingerprint recognition system. To effectively aggregate two systems, we use statistical distribution models based on matching values for genuine and impostor, respectively. And then, We performed reveal fusion algorithms including weighted summation, Support Vector Machine(SVM), Fisher discriminant analysis, Bayesian classifier. From the various experiments, we found that the performance of multi-modal biometric system was influenced with the normalization methods and classifiers.

Video Palmprint Recognition System Based on Modified Double-line-single-point Assisted Placement

  • Wu, Tengfei;Leng, Lu
    • Journal of Multimedia Information System
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    • v.8 no.1
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    • pp.23-30
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    • 2021
  • Palmprint has become a popular biometric modality; however, palmprint recognition has not been conducted in video media. Video palmprint recognition (VPR) has some advantages that are absent in image palmprint recognition. In VPR, the registration and recognition can be automatically implemented without users' manual manipulation. A good-quality image can be selected from the video frames or generated from the fusion of multiple video frames. VPR in contactless mode overcomes several problems caused by contact mode; however, contactless mode, especially mobile mode, encounters with several revere challenges. Double-line-single-point (DLSP) assisted placement technique can overcome the challenges as well as effectively reduce the localization error and computation complexity. This paper modifies DLSP technique to reduce the invalid area in the frames. In addition, the valid frames, in which users place their hands correctly, are selected according to finger gap judgement, and then some key frames, which have good quality, are selected from the valid frames as the gallery samples that are matched with the query samples for authentication decision. The VPR algorithm is conducted on the system designed and developed on mobile device.

A Face Recognition System using Geometric Image Processing (기하학적 영상처리를 이용한 얼굴인식 시스템)

  • 이항찬
    • Journal of Korea Multimedia Society
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    • v.6 no.7
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    • pp.1139-1148
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    • 2003
  • Biometric system has been studied as an optimal solution for preventing or reducing the peculation or loss of ID. Nowadays, face recognition has been spot-lighted as a future biometric system because it is not forced to contact the part of human body with the specific input area of the system. However, there is some limitations to get the constant facial features because the size of face area is varied by the capturing distance or tilt of the face. In this paper, we can extract constant facial features within the predefined threshold using the simple geometric processing such as image scaling, transformation, and rotation for frontal face images. This face recognition system identifies faces with 92% of accuracy for the 400 images of 40 different people.

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