• Title/Summary/Keyword: Iris Recognition System

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Multi-views face detection in Omni-directional camera for non-intrusive iris recognition (비강압적 홍채 인식을 위한 전 방향 카메라에서의 다각도 얼굴 검출)

  • 이현수;배광혁;김재희;박강령
    • Proceedings of the IEEK Conference
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    • 2003.11b
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    • pp.115-118
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    • 2003
  • This paper describes a system of detecting multi-views faces and estimating their face poses in an omni-directional camera environment for non-intrusive iris recognition. The paper is divided into two parts; First, moving region is identified by using difference-image information. Then this region is analyzed with face-color information to find the face candidate region. Second part is applying PCA (Principal Component Analysis) to detect multi-view faces, to estimate face pose.

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Implementation for the Biometric User Identification System Based on Smart Card (SMART CARD 기반 생체인식 사용자 인증시스템의 구현)

  • 주동현;고기영;김두영
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.1
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    • pp.25-31
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    • 2004
  • This paper is research about the improvement of recognition rate of the biometrics user identification system using the data previously stored in the non contact Ic smart card. The proposed system identifies the user by analyzing the iris pattern his or her us. First, after extracting the area of the iris from the image of the iris of an eye which is taken by CCD camera, and then we save PCA Coefficient using GHA(Generalized Hebbian Algorithm) into the Smart Card. When we confirmed the users, we compared the imformation of the biometrics of users with that of smart card. In case two kinds of information was the same, we classified the data by using SVM(Support Vector Machine). The Experimental result showed that this system outperformed the previous developed system.

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An Iris Detection Algorithm for Disease Prediction based Iridology (홍채학기반이 질병예측을 위한 홍채인식 알고리즘)

  • Cho, Young-bok;Woo, Sung-Hee;Lee, Sang-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.1
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    • pp.107-114
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    • 2017
  • Iris diagnosis is an alternative medicine to diagnose the disease of the patient by using different of the iris pattern, color and other characteristics. This paper proposed a disease prediction algorithm that using the iris regions that analyze iris change to using differential image of iris image. this method utilize as patient's health examination according to iris change. Because most of previous studies only find a sign pattern in a iris image, it's not enough to be used for a iris diagnosis system. We're developed an iris diagnosis system based on a iris images processing approach, It's presents the extraction algorithms of 8 major iris signs and correction manually for improving the accuracy of analysis. As a result, PNSR of applied edge detection image is about 132, and pattern matching area recognition presented practical use possibility by automatic diagnostic that presume situation of human body by iris about 91%.

Human Iris Recognition System using Wavelet Transform and LVQ (웨이브렛 변환과 LVQ를 이용한 홍채인식 시스템)

  • Lee, Gwan-Yong;Im, Sin-Yeong;Jo, Seong-Won
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.7
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    • pp.389-398
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    • 2000
  • The popular methods to check the identity of individuals include passwords and ID cards. These conventional method for user identification and authentication are not altogether reliable because they can be stolen and forgotten. As an alternative of the existing methods, biometric technology has been paid much attention for the last few decades. In this paper, we propose an efficient system for recognizing the identity of a living person by analyzing iris patterns which have a high level of stability and distinctiveness than other biometric measurements. The proposed system is based on wavelet transform and a competitive neural network with the improved mechanisms. After preprocessing the iris data acquired through a CCD camera, feature vectors are extracted by using Haar wavelet transform. LVQ(Learning Vector Quantization) is exploited to classify these feature vectors. We improve the overall performance of the proposed system by optimizing the size of feature vectors and by introducing an efficient initialization of the weight vectors and a new method for determining the winner in order to increase the recognition accuracy of LVQ. From the experiments, we confirmed that the proposed system has a great potential of being applied to real applications in an efficient and effective way.

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Periocular Recognition Using uMLBP and Attribute Features

  • Ali, Zahid;Park, Unsang;Nang, Jongho;Park, Jeong-Seon;Hong, Taehwa;Park, Sungjoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.12
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    • pp.6133-6151
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    • 2017
  • The field of periocular biometrics has gained wide attention as an alternative or supplemental means to conventional biometric traits such as the iris or the face. Periocular biometrics provide intermediate resolution between the iris and the face, which enables it to support both. We have developed a periocular recognition system by using uniform Multiscale Local Binary Pattern (uMLBP) and attribute features. The proposed system has been evaluated in terms of major factors that need to be considered on a mobile platform (e.g., distance and facial pose) to assess the feasibility of the use of periocular biometrics on mobile devices. Experimental results showed 98.7% of rank-1 identification accuracy on a subset of the Face Recognition Grand Challenge (FRGC) database, which is the best performance among similar studies.

Efficient Iris Recognition through Improvement of Feature Vector and Classifier

  • Lim, Shin-Young;Lee, Kwan-Yong;Byeon, Ok-Hwan;Kim, Tai-Yun
    • ETRI Journal
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    • v.23 no.2
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    • pp.61-70
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    • 2001
  • In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by using wavelet transform, and two straightforward but efficient mechanisms for a competitive learning method such as a weight vector initialization and the winner selection. With all of these novel mechanisms, the experimental results showed that the proposed system could be used for personal identification in an efficient and effective manner.

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Face Recognition Using a Facial Recognition System

  • Almurayziq, Tariq S;Alazani, Abdullah
    • International Journal of Computer Science & Network Security
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    • v.22 no.9
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    • pp.280-286
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    • 2022
  • Facial recognition system is a biometric manipulation. Its applicability is simpler, and its work range is broader than fingerprints, iris scans, signatures, etc. The system utilizes two technologies, such as face detection and recognition. This study aims to develop a facial recognition system to recognize person's faces. Facial recognition system can map facial characteristics from photos or videos and compare the information with a given facial database to find a match, which helps identify a face. The proposed system can assist in face recognition. The developed system records several images, processes recorded images, checks for any match in the database, and returns the result. The developed technology can recognize multiple faces in live recordings.

Feature Extraction for Iris Recognition Using Scale-Space Filtering (스케일 스페이스 필터링을 이용한 홍채 특징 추출)

  • Hong, Jin-Il;Kim, Dong-Min;Yang, Woo-S.
    • Journal of IKEEE
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    • v.6 no.2 s.11
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    • pp.169-177
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    • 2002
  • In this paper, we introduce a new technology to extract the unique features from an iris image, which uses scale-space filtering. Resulting iris code can be used to develop a system for rapid and automatic identification of persons, with high reliability and confidence levels. First, an iris part is separated from the whole image. Then the radius and center of the iris are obtained. Once the regions that have a high possibility of being noise are discriminated, the features presented in the highly detailed pattern is then extracted from the iris image. Scale-space filtering technique is applied for feature extraction.

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A study of intelligent system to improve the accuracy of pattern recognition (패턴인식의 정화성을 향상하기 위한 지능시스템 연구)

  • Chung, Sung-Boo;Kim, Joo-Woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.7
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    • pp.1291-1300
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    • 2008
  • In this paper, we propose a intelligent system to improve the accuracy of pattern recognition. The proposed intelligent system consist in SOFM, LVQ and FCM algorithm. We are confirmed the effectiveness of the proposed intelligent system through the several experiments that classify Fisher's Iris data and face image data that offered by ORL of Cambridge Univ. and EMG data. As the results of experiments, the proposed intelligent system has better accuracy of pattern recognition than general LVQ.

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.