• Title/Summary/Keyword: Biometrics Information

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An Algorithm for Filtering False Minutiae in Fingerprint Recognition and its Performance Evaluation (지문의 의사 특징점 제거 알고리즘 및 성능 분석)

  • Yang, Ji-Seong;An, Do-Seong;Kim, Hak-Il
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.3
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    • pp.12-26
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    • 2000
  • In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.

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Human Identification using EMG Signal based Artificial Neural Network (EMG 신호 기반 Artificial Neural Network을 이용한 사용자 인식)

  • Kim, Sang-Ho;Ryu, Jae-Hwan;Lee, Byeong-Hyeon;Kim, Deok-Hwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.4
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    • pp.142-148
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    • 2016
  • Recently, human identification using various biological signals has been studied and human identification based on the gait has been actively studied. In this paper, we propose a human identification based on the EMG(Electromyography) signal of the thigh muscles that are used when walking. Various features such as RMS, MAV, VAR, WAMP, ZC, SSC, IEMG, MMAV1, MMAV2, MAVSLP, SSI, WL are extracted from EMG signal data and ANN(Artificial Neural Network) classifier is used for human identification. When we evaluated the recognition ratio per channel and features to select approptiate channels and features for human identification. The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human identification. Experimental results also show that the average recognition ratio of method of using all channels and features is 99.7% and that of using selected 3 channels and 5 features is 96%. Therefore, we confirm that the EMG signal can be applied to gait based human identification and EMG signal based human identification using small number of adaptive muscles and features shows good performance.

An Incremental Elimination Method of EEG Samples Collected by Single-Channel EEG Measurement Device for Practical Brainwave-Based User Authentication (실용적 뇌파 기반 사용자 인증을 위한 단일 채널 EEG 측정 장비를 통해 수집된 EEG 샘플의 점진적 제거 방법)

  • Ko, Han-Gyu;Cho, Jin-Man;Choi, Daeseon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.27 no.2
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    • pp.383-395
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    • 2017
  • Brainwave-based user authentication technology has advantages such as changeability, shoulder-surfing resistance, and etc. comparing with conventional biometric authentications, fingerprint recognition for instance which are widely used for smart phone and finance user authentication. Despite these advantages, brainwave-based authentication technology has not been used in practice because of the price for EEG (electroencephalography) collecting devices and inconvenience to use those devices. However, according to the development of simple and convenient EEG collecting devices which are portable and communicative by the recent advances in hardware technology, relevant researches have been actively performed. However, according to the experiment based on EEG samples collected by using a single-channel EEG measurement device which is the most simplified one, the authentication accuracy decreases as the number of channels to measure and collect EEG decreases. Therefore, in this paper, we analyze technical problems that need to be solved for practical use of brainwave-based use authentication and propose an incremental elimination method of collected EEG samples for each user to consist a set of EEG samples which are effective to authentication users.

Image Distortion Compensation for Improved Gait Recognition (보행 인식 시스템 성능 개선을 위한 영상 왜곡 보정 기법)

  • Jeon, Ji-Hye;Kim, Dae-Hee;Yang, Yoon-Gi;Paik, Joon-Ki;Lee, Chang-Su
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.4
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    • pp.97-107
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    • 2009
  • In image-based gait recognition systems, physical factors, such as the camera angle and the lens distortion, and environmental factors such as illumination determines the performance of recognition. In this paper we present a robust gait recognition method by compensating various types of image distortions. The proposed method is compared with existing gait recognition algorithm with consideration of both physical and environmental distortion factors in the input image. More specifically, we first present an efficient compensation algorithm of image distortion by using the projective transform, and test the feasibility of the proposed algorithm by comparing the recognition performances with and without the compensation process. Proposed method gives universal gait data which is invariant to both distance and environment. Gained data improved gait recognition rate about 41.5% in indoor image and about 55.5% in outdoor image. Proposed method can be used effectively in database(DB) construction, searching and tracking of specific objects.

A Study on Multi-modal Near-IR Face and Iris Recognition on Mobile Phones (휴대폰 환경에서의 근적외선 얼굴 및 홍채 다중 인식 연구)

  • Park, Kang-Ryoung;Han, Song-Yi;Kang, Byung-Jun;Park, So-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.2
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    • pp.1-9
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    • 2008
  • As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.

Iris Feature Extraction using Independent Component Analysis (독립 성분 분석 방법을 이용한 홍채 특징 추출)

  • 노승인;배광혁;박강령;김재희
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.6
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    • pp.20-30
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    • 2003
  • In a conventional method based on quadrature 2D Gator wavelets to extract iris features, the iris recognition is performed by a 256-byte iris code, which is computed by applying the Gabor wavelets to a given area of the iris. However, there is a code redundancy because the iris code is generated by basis functions without considering the characteristics of the iris texture. Therefore, the size of the iris code is increased unnecessarily. In this paper, we propose a new feature extraction algorithm based on the ICA (Independent Component Analysis) for a compact iris code. We implemented the ICA to generate optimal basis functions which could represent iris signals efficiently. In practice the coefficients of the ICA expansions are used as feature vectors. Then iris feature vectors are encoded into the iris code for storing and comparing an individual's iris patterns. Additionally, we introduce two methods to enhance the recognition performance of the ICA. The first is to reorganize the ICA bases and the second is to use a different ICA bases set. Experimental results show that our proposed method has a similar EER (Equal Error Rate) as a conventional method based on the Gator wavelets, and the iris code size of our proposed methods is four times smaller than that of the Gabor wavelets.

Joint Angles Analysis of Intelligent upper limb and lower extremities Wheelchair Robot System (지능형 상 · 하지 재활 휠체어 로봇 시스템의 관절각도 분석)

  • Song, Byoung-Ho;Kim, Kwang Jin;Lee, Chang Sun;Lim, Chang Gyoon
    • Journal of Internet Computing and Services
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    • v.14 no.6
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    • pp.33-39
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    • 2013
  • When the eldery with limited mobility and disabled use a wheelchairs to move, it can cause decreased exercise ability like decline muscular strength in upper limb and lower extremities. The disabled people suffers with spinal cord injuries or post stroke hemiplegia are easily exposed to secondary problems due to limited mobility. In this paper, We designed intelligent wheelchair robot system for upper limb and lower extremities exercise/rehabilitation considering the characteristics of these severely disabled person. The system consists of an electric wheelchair, biometrics module for Identification characteristics of users, upper limb and lower extremities rehabilitation. In this paper, describes the design and configurations and of developed robot. Also, In order to verify the system function, conduct performance evaluation targeting non-disabled about risk context analysis with biomedical signal change and upper limb and lower extremities rehabilitation over wheelchair robot move. Consequently, it indicate sufficient tracking performance for rehabilitation as at about 86.7% average accuracy for risk context analysis and upper limb angle of 2.5 and lower extremities angle of 2.3 degrees maximum error range of joint angle.

Fingerprint Recognition Algorithm using Clique (클릭 구조를 이용한 지문 인식 알고리즘)

  • Ahn, Do-Sung;Kim, Hak-Il
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.2
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    • pp.69-80
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    • 1999
  • Recently, social requirements of personal identification techniques are rapidly expanding in a number of new application ares. Especially fingerprint recognition is the most important technology. Fingerprint recognition technologies are well established, proven, cost and legally accepted. Therefore, it has more spot lighted among the any other biometrics technologies. In this paper we propose a new on-line fingerprint recognition algorithm for non-inked type live scanner to fit their increasing of security level under the computing environment. Fingerprint recognition system consists of two distinct structural blocks: feature extraction and feature matching. The main topic in this paper focuses on the feature matching using the fingerprint minutiae (ridge ending and bifurcation). Minutiae matching is composed in the alignment stage and matching stage. Success of optimizing the alignment stage is the key of real-time (on-line) fingerprint recognition. Proposed alignment algorithm using clique shows the strength in the search space optimization and partially incomplete image. We make our own database to get the generality. Using the traditional statistical discriminant analysis, 0.05% false acceptance rate (FAR) at 8.83% false rejection rate (FRR) in 1.55 second average matching speed on a Pentium system have been achieved. This makes it possible to construct high performance fingerprint recognition system.

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An Analysis of ICT-Retail Convergence(IRC) and Consumer Value Creation (소비자 구매단계별 기술-유통 통합(IRC)과 가치에 대한 연구)

  • Park, Sunny;Cho, Eunsun;Rha, Jong-Youn;Lee, Yuri;Kim, Suyoun
    • Journal of Digital Convergence
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    • v.15 no.7
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    • pp.147-157
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    • 2017
  • Recently, ICT Retail Convergence(IRC) has been rapidly increasing to improve consumer satisfaction and consumer experience. In this paper, we aim to diagnose IRC from consumers' point of view by reviewing the present status and value of IRC according to consumer purchase decision making process. Based on the previous studies in retail industry, we classified IRC into 4 types: Experience-specific tech(Virtual Reality and Augmented Reality); Information-specific tech(Artificial Intelligence and Big Data); Location-based tech(Radio Frequency Identification and Beacon); Payment-related tech(Fin-tech and Biometrics). Next, we found that there is a difference in value provided to consumers according to the type of technology, analysing the value by consumer purchase decision making process. This study can be useful to introduce IRC for improving consumer satisfaction as well as ICT and Retail. Also, it can be basic data for future technology studies with a consumer perspective.

Smartphone Security Using Fingerprint Password (다중 지문 시퀀스를 이용한 스마트폰 보안)

  • Bae, Kyoung-Yul
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.45-55
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    • 2013
  • Thereby using smartphone and mobile device be more popular the more people utilize mobile device in many area such as education, news, financial. In January, 2007 Apple release i-phone it touch off rapid increasing in user of smartphone and it create new market and these broaden its utilization area. Smartphone use WiFi or 3G mobile radio communication network and it has a feature that can access to internet whenever and anywhere. Also using smartphone application people can search arrival time of public transportation in real time and application is used in mobile banking and stock trading. Computer's function is replaced by smartphone so it involves important user's information such as financial and personal pictures, videos. Present smartphone security systems are not only too simple but the unlocking methods are spreading out covertly. I-phone is secured by using combination of number and character but USA's IT magazine Engadget reveal that it is easily unlocked by using combination with some part of number pad and buttons Android operation system is using pattern system and it is known as using 9 point dot so user can utilize various variable but according to Jonathan smith professor of University of Pennsylvania Android security system is easily unlocked by tracing fingerprint which remains on the smartphone screen. So both of Android and I-phone OS are vulnerable at security threat. Compared with problem of password and pattern finger recognition has advantage in security and possibility of loss. The reason why current using finger recognition smart phone, and device are not so popular is that there are many problem: not providing reasonable price, breaching human rights. In addition, finger recognition sensor is not providing reasonable price to customers but through continuous development of the smartphone and device, it will be more miniaturized and its price will fall. So once utilization of finger recognition is actively used in smartphone and if its utilization area broaden to financial transaction. Utilization of biometrics in smart device will be debated briskly. So in this thesis we will propose fingerprint numbering system which is combined fingerprint and password to fortify existing fingerprint recognition. Consisted by 4 number of password has this kind of problem so we will replace existing 4number password and pattern system and consolidate with fingerprint recognition and password reinforce security. In original fingerprint recognition system there is only 10 numbers of cases but if numbering to fingerprint we can consist of a password as a new method. Using proposed method user enter fingerprint as invested number to the finger. So attacker will have difficulty to collect all kind of fingerprint to forge and infer user's password. After fingerprint numbering, system can use the method of recognization of entering several fingerprint at the same time or enter fingerprint in regular sequence. In this thesis we adapt entering fingerprint in regular sequence and if in this system allow duplication when entering fingerprint. In case of allowing duplication a number of possible combinations is $\sum_{I=1}^{10}\;{_{10}P_i}$ and its total cases of number is 9,864,100. So by this method user retain security the other hand attacker will have a number of difficulties to conjecture and it is needed to obtain user's fingerprint thus this system will enhance user's security. This system is method not accept only one fingerprint but accept multiple finger in regular sequence. In this thesis we introduce the method in the environment of smartphone by using multiple numbered fingerprint enter to authorize user. Present smartphone authorization using pattern and password and fingerprint are exposed to high risk so if proposed system overcome delay time when user enter their finger to recognition device and relate to other biometric method it will have more concrete security. The problem should be solved after this research is reducing fingerprint's numbering time and hardware development should be preceded. If in the future using fingerprint public certification becomes popular. The fingerprint recognition in the smartphone will become important security issue so this thesis will utilize to fortify fingerprint recognition research.