• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.494-498
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• 2004

In this paper, a system that implementation of Access Control System Using Biometric System. Biometries is science which deals with verifying or recognizing using physiological or behavioral characteristic Access Control System uses Bionietric 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 Weigand (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.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.83-90
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• 2010

Cancelable biometrics is a robust and secure biometric recognition method using revocable biometric template in order to prevent possible compromisation of the original biometric data. In this paper, we present a new cancelable bits extraction method for the facial data. We use our previous cancelable feature template for the bits extraction. The adopted cancelable template is generated from two different original face feature vectors extracted from two different appearance-based approaches. Each element of feature vectors is re-ordered, and the scrambled features are added. With the added feature, biometric bits string is extracted using helper data based method. In this technique, helper data is generated using statistical property of the added feature vector, which can be easily replaced with straightforward revocation. Because, the helper data only utilizes partial information of the added feature, our proposed method is a more secure method than our previous one. The proposed method utilizes the helper data to reduce feature variance within the same individual and increase the distinctiveness of bit strings of different individuals for good recognition performance. For a security evaluation of our proposed method, a scenario in which the system is compromised by an adversary is also considered. In our experiments, we analyze the proposed method with respect to performance and security using the extended YALEB face database

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.268-284
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• 2017

The dorsal hand vein biometric system developed has a main objective and specific targets; to get an electronic signature using a secure signature device. In this paper, we present our signature device with its different aims; respectively: The extraction of the dorsal veins from the images that were acquired through an infrared device. For each identification, we need the representation of the veins in the form of shape descriptors, which are invariant to translation, rotation and scaling; this extracted descriptor vector is the input of the matching step. The optimization decision system settings match the choice of threshold that allows accepting/rejecting a person, and selection of the most relevant descriptors, to minimize both FAR and FRR errors. The final decision for identification based descriptors selected by the PSO hybrid binary give a FAR =0% and FRR=0% as results.

• ETRI Journal
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• v.33 no.2
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• pp.259-266
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• 2011

We present a new method for an automated markerless system to describe, analyze, and classify human gait motion. The automated system consists of three stages: I) detection and extraction of the moving human body and its contour from image sequences, ii) extraction of gait figures by the joint angles and body points, and iii) analysis of motion parameters and feature extraction for classifying human gait. A sequential set of 2D stick figures is used to represent the human gait motion, and the features based on motion parameters are determined from the sequence of extracted gait figures. Then, a k-nearest neighbor classifier is used to classify the gait patterns. In experiments, this provides an alternative estimate of biomechanical parameters on a large population of subjects, suggesting that the estimate of variance by marker-based techniques appeared generous. This is a very effective and well-defined representation method for analyzing the gait motion. As such, the markerless approach confirms uniqueness of the gait as earlier studies and encourages further development along these lines.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.2
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• pp.133-138
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• 2014

In this paper, a simple but efficient gait recognition method using spatial-temporal silhouette analysis is proposed. For each image sequence, a background subtraction algorithm and a PBAS(pixel based adaptive segmenter) procedure are first used to segment the moving silhouettes of a walking figure. Then, to identify people, the step count and stride length of walking figure is obtained in silhouette images. Experimental results on a CASIA dataset including 124 subjects demonstrate the validity of the proposed method. Also, the proposed system are believed to have a sufficient feasibility for the application to gait recognition.

• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.445-455
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• 2007

We present a new biometric identification system based on multi-view features of teeth using principal components analysis(PCA). The multi-view features of teeth consist of the frontal view, the left side view and the right side view. In this paper, we try to stan the foundations of a dental biometrics for secure access in real life environment. We took the pictures of the three views teeth in the experimental environment designed specially and 42 principal components as the features for individual identification were developed. The classification for individual identification based on the nearest neighbor(NN) algorithm is created with the distance between the multi-view teeth and the multi-view teeth rotated. The identification performance after rotating two degree of test data is 95.2% on the left side view teeth and 91.3% on the right side view teeth as the average values.

• Convergence Security Journal
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• v.16 no.6_2
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• pp.83-88
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• 2016

Over recent years there has been considerable growth in interest in the use of biometric systems for personal authentication. Biometrics is a field of technology which has been and is being used in the identification of individuals based on some physical attribute. By using biometrics, authentication is directly linked to the person, rather than their token or password. Biometric authentication is a type of system that relies on the unique biological characteristics of individuals to verify identity for secure access to electronic systems. In 2013, Althobati et al. proposed an efficient remote user authentication protocol using biometric information. However, we uncovered Althobati et al.'s protocol does not guarantee its main security goal of mutual authentication. We showed this by mounting threat of data integrity and bypassing the gateway node attack on Althobati et al.'s protocol. In this paper, we propose an improved scheme to overcome these security weaknesses by storing secret data in device. In addition, our proposed scheme should provide not only security, but also efficiency since sensors in WSN(Wireless Sensor Networks) operate with resource constraints such as limited power, computation, and storage space.

• Journal of Integrative Natural Science
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• v.10 no.3
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• pp.162-170
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• 2017

In this paper, it is aim to implement a wheelchair monitoring system that provides users with customized medical services easily in everyday life, together with mobility guarantee, which is the most basic requirement of the elderly and disabled persons with physical disabilities. The case-based intelligent wheelchair monitoring system proposed in this study is based on a case-based k-NN algorithm, which implements a system for constructing and inferring examples of various biometric and environmental information of wheelchair users as a knowledge database and a monitoring interface for wheelchair users. In order to confirm the usefulness of the case-based k-NN algorithm, the SVM algorithm showed an average accuracy of 84.2% and the average accuracy of the proposed case-based k-NN algorithm was 86.2% And showed higher performance in terms of accuracy. The system implemented in this paper has the advantage of measuring biometric information and data communication regardless of time and place and it can provide customized service of wheelchair user through user friendly interface.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4C
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• pp.283-289
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• 2012

Web-based physiological signal monitoring system can provide appropriate healthcare services to transmit bio-signal processing, analysis of bulk in medical centers. Therefore, we constructed a design of system to analyze effect of cardiac associated auricular acupuncture reflexology based on physiological signals. System to analyze effect cardiac associated auricular acupuncture reflexology, which carried out analysis and measurement of bio-signal to apply cardiac-related biometrics input in biometric image and voice signal. In addition, we also confirmed through statistical analysis actual home healthcare system to performance evaluation of system on subjects 20.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.65-75
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• 2004

It is notorious that PIN(Personal Identification Number) is used widely for user verification and authentication in networked environment. But, when the user Identification and password are exposed by hacking, we can be damaged monetary damage as well as invasion of privacy. In this paper, we adopt face recognition-based authentication which have nothing to worry what the ID and password will be exposed. Also, we suggest the remote authentication and verification system by considering not only 2-Tier system but also 3-Tier system getting be distributed. In this research, we analyze the face feature data using the SVM(Support Vector Machine) and PCA(Principle Component Analysis), and implement artificial intelligence face recognition module in distributed environment which increase the authentication speed and heightens accuracy by utilizing artificial intelligence techniques.