• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.45 no.3
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• pp.177-187
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• 2009

This paper describes a automatic video surveillance system(AVSS) with long range and 360$^{\circ}$ coverage that is automatically rotated in an elevation over azimuth mode in response to the TTM(tracked target message) signal of vessels tracked by ARPA(automatic radar plotting aids) radar. This AVSS that is a video security and tracking system supported by ARPA radar, CCTV(closed-circuit television) camera system and other sensors to automatically identify and track, detect the potential dangerous situations such as collision accidents at sea and berthing/deberthing accidents in harbor, can be used in monitoring the illegal fishing vessels in inshore and offshore fishing ground, and in more improving the security and safety of domestic fishing vessels in EEZ(exclusive economic zone) area. The movement of the target vessel chosen by the ARPA radar operator in the AVSS can be automatically tracked by a CCTV camera system interfaced to the ECDIS(electronic chart display and information system) with the special functions such as graphic presentation of CCTV image, camera position, camera azimuth and angle of view on the ENC, automatic and manual controls of pan and tilt angles for CCTV system, and the capability that can replay and record continuously all information of a selected target. The test results showed that the AVSS developed experimentally in this study can be used as an extra navigation aid for the operator on the bridge under the confusing traffic situations, to improve the detection efficiency of small targets in sea clutter, to enhance greatly an operator s ability to identify visually vessels tracked by ARPA radar and to provide a recorded history for reference or evidentiary purposes in EEZ area.

• Journal of IKEEE
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• v.27 no.4
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• pp.512-517
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• 2023

In this study, we propose a liquid crystal-based polarization control technology that can control polarization by adjusting the voltage applied to the liquid crystal, and apply it to a Closed-circuit Television (CCTV) to transmit only the desired angle of polarized light. CCTV with conventional polarizing films cannot control polarization because they focus on backlight compensation, so light reflected from the water surface or highlights reflected from vehicles interfere with subject identification. However, the Vertical Alignment mode allows the polarization to be adjusted electrically, so that only the polarized light at the user's desired angle is transmitted, eliminating reflected highlights. The images obtained using this technique are optimized by computer software. Liquid crystal polarization panels, which can electrically control the polarization angle, transmittance, and polarization rate, have been applied to polarized image monitoring device to improve subject identification in conventional CCTV.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.504-511
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• 2010

In this paper, we propose the face region recognition system for City-Security CCTV(Closed Circuit Television) using hippocampal neural network which is modelling of human brain's hippocampus. This system is composed of feature extraction, learning and recognition part. The feature extraction part is constructed using PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis). In the learning part, it can label the features of the image-data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in a dentate gyrus and remove the noise through the auto-associative memory in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term memory learned by neuron. Experiments confirm the each recognition rate, that are shape change and light change. The experimental results show that we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to existing methods.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.38-50
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• 2023

Recent advances in artificial intelligence (AI) technology have enabled the integration of AI technology into image sensors, such as Closed-Circuit Television (CCTV), to detect specific traffic incidents. However, most incident detection methods have been carried out using fixed equipment. Therefore, there have been limitations to incident detection for all roadways. Nevertheless, the development of mobile image collection and analysis technology, such as image sensors and edge-computing, is spreading. The purpose of this study is to estimate the reducing effect of the incident detection time according to the introduction level of mobile image collection and analysis equipment (or connected vehicles). To carry out this purpose, we utilized data on the number of incidents collected by the Suwon branch of the Gyeongbu expressway in 2021. The analysis results showed that if the market penetration rate (MPR) of connected vehicles is 4% or higher for two-lane expressway and 3% or higher for three-lane expressways, the incident detection time was less than one minute. Furthermore, if the MPR is 0.4% or higher for two-lane expressways and 0.2% or higher for three-lane expressways, the incident detection time decreased compared to the average incident detection time announced by the Korea Expressway Corporation for both two-lane and three-lane expressways.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.625-628
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• 2004

Even though the tower crane is a major equipment in a construction of high rise buildings, there are lack of studies of it. This study is presenting a framework of developing a intelligent tower crane applied with the technology of machine-vision, RFID(Radio Frequency Identification), or GPS(Global positioning System) and proposing the prototype of machine-vision module, sub module of this Framework. Through monitoring form CCTV(Closed Circuit Television) and LCD(Liquid Crystal Display) in machine-module the real time communication between in-site workers and crane operator is possible. this will improve the productivity and safety of the tower crane.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.63-72
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• 2016

Closed-circuit television(CCTV) is a facility that forms the backbone of the ubiquitous services provided by the Integrated Management Center of the Ministry of Land, Infrastructure and Transport and the Integrated Control Center of the Ministry of the Interior. However, it is installed and managed according to different laws, as it is operated and managed by each department. Moreover, because there are no regulatory grounds for unified management of CCTV, each municipality responsible for the actual management manages it based on the individual standards of each department. Thus, the purpose of this study is to develop a standardized management form to establish an integrated management plan. The author inspected the existing situation by examining the legal system and public data and through hands-on worker interviews, and discovered the managed element by reviewing the specifications of the bidding system. The management form for integrated management comprises the above requirements along with the management histories and linkage of intelligent facilities. A uniform management form for integrated management containing specifications of the CCTVs installed by various departments is created, and is easily searched for facilities to check requirements for joint use. The result of this study can contribute to building the database of facility management system for integrated management of facilities at the integrated management center as well as for a detailed simulation of the selection of location of CCTV depending on the CCTV's specifications.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1716-1721
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• 2011

The Public Address and Passenger Information System of Rolling Stock should be able to perform automatic announcements in connection with TCMS(Train Control and Monitoring System), common announcements and emergency announcements for safe operation and the passengers. CCTV(Closed Circuit Television) System also should be able to watch passenger compartment for safety. Those equipments are very important thing for train service and safety. but the installation of equipment is restricted by space, weight, modulation. therefore, Passenger Information Intergrated System(PIIS) is required to consider economical efficiency, technical trend, expansion and space insufficiency. and system based on IP network has to be considered as new PIIS. so PIIS could meet economical efficiency and expansion. and it could go further and share network with TCMS and others.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.234-237
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• 2009

많은 건설 현장에서 카메라와 CCTV(Closed-circuit Television)와 같은 장비를 활용하여 건설 현장의 상황을 모니터링 하고 있다. 하지만 많은 작업이 실외에서 이루어지는 토목 건축공사의 특성상 적절한 수준의 영상 데이터를 축적하는 것은 쉽지 않은 일이다. 특히, 이미지 프로세싱기법을 사용 하여 자동화된 건설 관리의 수행 시, 영상 데이터의 품질에 따라 에러가 발생하여 건설 관리자가 잘못된 정보를 얻게 될 경우도 발생하게 된다. 본 연구에서는 케니엣지(Canny Edge) 인식기법과 워터쉐드(Watershed) 변환, 그리고 3D CAD Mask를 이용한 건축 구조물 기둥의 시공 상황 분석 기법에 근거하여, 영상 데이터 분석 시 오류를 최소화하기 위한 에러 제거 알고리즘을 제시한다. 실제 데이터와 비교를 통하여 그 활용 가능성 또한 검증한다.