• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.789-792
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• 2008

범죄 예방과 자원 보호를 위해 CCTV 카메라를 이용하는 방범 시스템의 필요성은 점차 커지고 있다. 아날로그 형식에서부터 디지털 형식으로 발전된 형태의 방범 시스템이 개발되고 사용 중이지만, 비용이 높고 효율성이 떨어지는 문제가 있다. 본 논문에서는 웹 서비스 기반의 서버에 적외선 카메라를 연결하고 사용자가 사전 인지 없이도 클라이언트에서 실시간으로 침입을 탐지하여 적절하게 대처할 수 있는 방범 시스템을 설계하고 구현한다.

• Smart Media Journal
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• v.13 no.4
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• pp.65-75
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• 2024

This paper proposes a new approach to video surveillance systems, which have become essential components in modern urban management. By utilizing blockchain and IPFS, it enhances data integrity and privacy protection. Additionally, anomaly detection and automatic video storage are enabled through object detection technology, thus improving urban safety and security. This integrated approach serves as an efficient management methodology for surveillance systems, providing city administrators and citizens with a safer and more effective monitoring environment.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.57-64
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• 2022

If the inside of a building collapses due to a disaster such as fire, collapse, or natural disaster, the physical security inside the building is likely to become ineffective. Here, physical security is needed to minimize the human casualties and physical damages in the collapsed building. Therefore, this paper proposes an algorithm to minimize the damage in a disaster situation by fusing existing research that detects obstacles and collapsed areas in the building and a deep learning-based object detection algorithm that minimizes human casualties. The existing research uses a single camera to determine whether the corridor environment in which the robot is currently located has collapsed and detects obstacles that interfere with the search and rescue operation. Here, objects inside the collapsed building have irregular shapes due to the debris or collapse of the building, and they are classified and detected as obstacles. We also propose a method to detect rescue requesters-the most important resource in the disaster situation-and minimize human casualties. To this end, we collected open-source disaster images and image data of disaster situations and calculated the accuracy of detecting rescue requesters in disaster situations through various deep learning-based object detection algorithms. In this study, as a result of analyzing the algorithms that detect rescue requesters in disaster situations, we have found that the YOLOv4 algorithm has an accuracy of 0.94, proving that it is most suitable for use in actual disaster situations. This paper will be helpful for performing efficient search and rescue in disaster situations and achieving a high level of physical security, even in collapsed buildings.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.252-263
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• 2016

Road sign is an important street furniture that gives some information such as road conditions, driving direction and condition for a driver. Thus, road sign is a major target of image recognition for self-driving car, ADAS(autonomous vehicle and intelligent driver assistance systems), and ITS(intelligent transport systems). In this paper, an enhanced road sign recognition system is proposed for MMS(Mobile Mapping System) using the single camera and GPS. For the proposed system, first, a road sign recognition scheme is proposed. this scheme is composed of detection and classification step. In the detection step, object candidate regions are extracted in image frames using hybrid road sign detection scheme that is based on color and shape features of road signs. And, in the classification step, the area of candidate regions and road sign template are compared. Second, a Geo-marking scheme for geo-content that is consist of road sign image and coordinate value is proposed. If the serious situation such as car accident is happened, this scheme can protect geographical information of road sign against illegal users. By experiments with test video set, in the three parts that are road sign recognition, coordinate value estimation and geo-marking, it is confirmed that proposed schemes can be used for MMS in commercial area.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1009-1015
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• 2017

Recently, video surveillance is becoming more and more common as many camera are installed due to crime, terrorism, traffic and security. And systems that control cameras are becoming increasingly general. Video input from the installed camera is monitored by the multiscreen at the central control center, it is essential to simultaneously monitor multiscreen in real-time to quickly respond to situations or dangers. However, monitoring of multiscreen in a mobile environment such as a smart phone is not applied to hardware specifications or network bandwidth problems. For resolving these problems, in this paper, we propose a system that can monitor multiscreen in real-time in mobile-phone environment. We reconstruct the desired multiscreen through transcoding, it is possible to monitor continuously video streaming of multiple cameras, and to have the advantage of being mobile in mobile-phone environment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.137-145
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• 2004

In this paper, a new algorithm for the segmentation of the multi moving objects at the 3 dimension space and the method of measuring the distance from the camera to the moving object by using stereo video monitoring system is proposed. It get the input image of left and right from the stereo video monitoring system, and the area of the multi moving objects segmented by using adaptive threshold and PRA(pixel recursive algorithm). Each of the object segmented by window mask, then each coordinate value and stereo disparity of the multi moving objects obtained from the window masks. The distance of the multi moving objects can be calculated by this disparity, the feature of the stereo vision system and the trigonometric function. From the experimental results, the error rate of a distance measurement be existed within 7.28％, therefore, in case of implementation the proposed algorithm, the stereo security system, the automatic moving robot system and the stereo remote control system will be applied practical application.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.51-58
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• 2017

Because of safety and security, Surveillance camera market is growing. Accordingly, Study on video recognition and tracking is also actively in progress, but There is a limit to identify object by obtaining the information of object identified and tracked. Especially, It is more difficult to identify multiple objects in open space like shopping mall, airport and others utilized surveillance camera. Therefore, This paper proposed adding object identification function by using RFID to existing video-based object recognition and tracking system. Also, We tried to complement each other to solve the problem of video and RFID based. Thus, through the interaction of system modules We propose a solution to the problems of failing video-based object recognize and tracking and the problems that could be cased by the recognition error of RFID. The system designed to identify the object by classifying the identification of object in four steps so that the data reliability of the identified object can be maintained. To judge the efficiency of this system, this demonstrated by implementing the simulation program.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.19-27
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• 2020

In this study, Developing high resolution camera and Social Network Service sharing image can be easily getting images, it cause about taking fingerprints to easy from images. So I present solution about prevent to taking fingerprints. this technology is develop python using to opencv, blur libraries. First of all 'Hand Key point Detection' algorithm is used to locate the hand in the image. Using this algorithm can be find finger joints that can be protected while minimizing damage in the original image by using the coordinates of separate blurring the area of fingerprints in the image. from now on the development of accurate finger tracking algorithms, fingerprints will be protected by using technology as an internal option for smartphone camera apps from high resolution images.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.11-20
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• 2015

In this paper, we develop an intelligent mobile surveillance system based on binary CDMA for the unmanned automatic tracking and surveillance. That is, we implement a intelligent surveillance system using the binary CDMA wireless communication technology which is applied the merit of CDMA and TDMA on it complexly. This system is able to monitor the site of the accident on network in real time and process the various situations by implementing the security surveillance system. This system pursues an object by the 360-degree using camera, expands image using a PTZ(Pan/Tilt/Zoom) camera zooming function, identifies the mobile objects image within a screen and transfers the identified image to the remote site. Finally, we show the efficiency of the implemented system through the simulation of the controlled situations, such as tracking coverage on objects, object expansion, object detection number, monitoring the remote transferred image, number of frame per second by the image output signal etc..

• 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.