• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.72-77
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• 2008

Identification of humans from multiple view points is an important task for surveillance and security purposes. For optimal performance the system should use the maximum information available from sensors. Multimodal biometric systems are capable of utilizing more than one physiological or behavioral characteristic for enrollment, verification, or identification. Since gait alone is not yet established as a very distinctive feature, this paper presents an approach to fuse face and gait for identification. In this paper we will use the single camera case i.e both the face and gait recognition is done using the same set of images captured by a single camera. The aim of this paper is to improve the performance of the system by utilizing the maximum amount of information available in the images. Fusion in considered at decision level. The proposed algorithm is tested on the NLPR database.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.245-251
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• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.43-53
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• 2007

e-Learning education system as the next educational trend supporting remote and multimedia education. However, the students stay mainly at remote place and it is hard to certificate whether he is really studying now or not. To solve this problem, some solutions were proposed such as instructor's supervision by real time motion picture or message exchanging. Unhappily, as you can see, it needs much cost to establish the motion exchanging system and trampling upon human rights could occasion to reduce the student's will. Accordingly, we propose the new intelligent system based on face recognition to reduce the system cost. The e-Learning system running on the web page can check the student's status by motion image, and the images transfer to the instructor. For this study, 20 students and one instructor takes part in capturing and recognizing the face images. And the result produces the prevention the leave of students from lecture and improvement of attention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.11
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• pp.994-999
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• 2014

Nowadays we use biometrics such as face, fingerprint or palm print for registration and authentication with smart phone. When use camera function of smart phone, normally they overlay a specific image on camera preview as guideline and induce user to take picture uniformly. In this paper, use palm print for authentication factor with smart phone, we propose a new guideline and show the result about user experiment in terms of authentication success ratio.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.425-426
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• 2021

Recently, there have been frequent incidents of talent accidents caused by youth driving without a license. Driving without a license is becoming a hotbed of curiosity and challenge for some young people, and there is a limit to managing smart keys at home to prevent this. Therefore, in this paper, using the facial recognition algorithm, the face of the driver sitting in the driver's seat is compared with the information stored in advance, and the system is designed to control the engine by determining that it is a registered driver. If the registered driver authentication is successful, the matching accuracy and Unlock message are output to the LCD connected to the Raspberry Pi.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.161-163
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• 2021

In an apartment or private building, it is difficult for the user to operate the elevator button in a similar situation with luggage in both hands. In an environment where human contact must be minimized due to a highly infectious virus such as COVID-19, it is inevitable to operate an elevator based on untact. This paper proposes an operating system capable of operating the elevator by using the user's voice and image processing through the user's face without pressing the elevator button. The elevator can be operated to a designated floor without pressing a button by detecting the face of a person entering the elevator by detecting the person's face from the camera installed in the elevator, matching the information registered in advance. When it is difficult to recognize a person's face, it is intended to enhance the convenience of elevator use in an untouched environment by controlling the floor of the elevator using the user's voice through a microphone and automatically recording access information.

• Convergence Security Journal
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• v.22 no.1
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• pp.29-38
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• 2022

The importance of prevention of epidemics is increasing due to the serious spread of infectious diseases. For prevention of epidemics, we need to focus on the non-contact industry. Therefore, in this paper, a face recognition door lock that controls access through non-contact is designed and developed. First very simple features are combined to find objects and face recognition is performed using Haar-based cascade algorithm. Then the texture of the image is binarized to find features using LBPH. An non-contact door lock system which composed of Raspberry PI 3B+ board, an ultrasonic sensor, a camera module, a motor, etc. are suggested. To verify actual performance and ascertain the impact of light sources, various experiment were conducted. As experimental results, the maximum value of the recognition rate was about 85.7%.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1043-1045
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• 2017

기존 아이디-패스워드 방식의 사용자 인증에서 망각, 도난, 분실, 복제의 피해가 증가하자, 그러한 문제가 보완된 새로운 인증 수단인 생체 인증 시스템이 주목을 받기 시작했다. 본 연구에서는 생체 인증 시스템 중 얼굴 인식을 통해 등록된 사용자를 인증, 출입문을 통제하는 방법에 대해 다루었다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.289-290
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• 2020

본 논문에서는 오픈 소스인 openpose skeleton tracking 기술을 이용하여 특정 운동 동작을 영상처리 기술과 딥러닝 기술로 인체 자세에 대해서 인지와 상황 판단하여 운동 동작에 대한 인식 결과를 도출할 수 있다. 먼저 입력받은 영상을 전달받아서 딥러닝 인식 시스템를 통해 인식 결과을 추출한 뒤 비교, 분석한 후에 사전 등록된 운동 동작 명칭으로 화면에 표시하여 이용자가 정확한 동작을 취할 수 있도록 지도하는 데 활용할 수 있다. 또한, 이 기술은 행동 인식부터 얼굴 인식, 손동작 인식 등에 다양하게 활용할 수 있다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.251-256
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• 2010

In times past, simple numeric password was the commonly used method in security system. For complement this method, the security system using biometric information is appeared. But it usually uses the scheme to utilize portion of biometric information, and has limited application fields. This biometric security system has low reliability because of some problems such as steal, robbery, and so on. Furthermore, it is associated secondary crime as leaking personal information. For this reason new security system using the unique individual biometric is required. In this paper, we propose the security scheme which used face image and iris analysis. While face image processing for specific person identification, it calculate some feature points of face image and iris's features in our proposed scheme. After person identification applying RFID tags in doorway, several feature information is extracted from camera image, and these compare with registered information of our system for final identification.