• Journal of Digital Convergence
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• v.19 no.4
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• pp.19-24
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• 2021

In this paper, an index of women's safety facilities was created and visualized using public data related to Seoul. CPTED, the women's safety facilities index was created by collecting and analyzing eight data related to the local women's safety index and five major crime victims of women. As a result of the correlation analysis between the factors of the female safety facility index and the number of female crime victims, three data were selected as the main factors, "CCTV," "street lamps," and "female security guardians", which were found to be meaningful at the 95% level of reliability. The distinction women's safety facility index was calculated by weighting the correlation coefficient between the main factors for calculating the women's safety facility index, and visualized using Python's Follium library.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.463-466
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• 2010

In this paper, CCTV based fire surveillance system should aim to development. Advantages and Disadvantages analyzed of Existing sensor-based fire surveillance system and video-based fire surveillance system. To national support U-City, U-Home, U-Campus, etc, spread the ubiquitous environment appropriate to fire surveillance system model and a fire judgement technology. For this study, Microsoft LifeCam VX-1000 using through the capturing images and analyzed for apple and tomato, Finally we used H.264. The client uses the Linux OS with ARM9 S3C2440 board was manufactured, the client's role is passed to the server to processed capturing image. Client and the server is basically a 1:1 video communications. So to multiple receive to video multicast support will be a specification. Is fire surveillance system designed for multiple video communication. Video data from the RGB format to YUV format and transfer and fire detection for Y value. Y value is know movement data. The red color of the fire is determined to detect and calculate the value of Y at the fire continues to detect the movement of flame.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.173-176
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• 2004

영상압축 표준인 MPEG알고리즘은 다양한 분야에서 응용되고있다. 최근에는 기존의 아날로그 CCTV 영상 감시시스템 분야에서도 MPEG을 응용한 IP Surveillance 시스템으로 급속히 전환되고 있는 추세이다. 본 논문은 IP Surveillance를 위한 MPEG 알고리즘의 최적 Qp에 대해 분석하고 실제 전송구간에서의 지연과 품질에 대해 분석하였다. 네트워크를 통한 영상전송에서 QoS에 영향을 미치는 주요 요인으로는 압축된 영상데이터의 bit rate와 전송구간인 네트워크에서의 지연으로 인한 문제이다. 따라서 본 논문은 IP Surveillance를 위한 디지털 CCTV 네트워크를 구성하기 위한 방안을 MPEG 알고리즘과 전송부분에서 분석하고 효율적인 구성방안을 제시하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.1056-1058
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• 2022

본 연구는 항만에서 안전 수칙을 위반하여 발생하는 사고 및 이상행동을 실시간 탐지를 수행한 후 위험 상황을 관리자가 신속하고 정확하게 대처할 수 있도록 지원하는 지능형 CCTV, Smart Eye를 제안한다. Smart Eye는 컴퓨터 비전(Computer Vision) 기반의 다양한 객체 탐지(Object Detection) 모델과 행동 인식(Action Recognition) 모델을 통해 낙하 및 전도사고, 안전 수칙 미준수 인원, 폭력적인 행동을 보이는 인원을 복합적으로 판단하며, 객체 추적(Object Tracking), 관심 영역(Region of Interest), 객체 간의 거리 측정 알고리즘을 구현하여, 제한구역 접근, 침입, 배회, 안전 보호구 미착용 인원 그리고 화재 및 충돌사고 위험도를 측정한다. 해당 연구를 통한 자동화된 24시간 감시체계는 실시간 영상 데이터 분석 및 판단 처리 과정을 거친 후 각 장소에서 수집된 데이터를 관리자에게 신속히 전달하고 항만 내 통합관제센터에 접목함으로써 효율적인 관리 및 운영할 수 있게 하는 '지능형 인프라'를 구축할 수 있다. 이러한 체계는 곧 스마트 항만 시스템 도입에 이바지할 수 있을 것으로 기대된다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.10-18
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• 2024

Vehicle loading is one of the main causes of bridge deterioration. Although WiM (Weigh in Motion) can be used to measure vehicle loading on a bridge, it has disadvantage of high installation and maintenance cost due to its contactness. In this study, a non-contact method is proposed to estimate the vehicle loading history of bridges using deep learning and CCTV images. The proposed method recognizes the vehicle type using an object detection deep learning model and estimates the vehicle loading based on the load-based vehicle type classification table developed using the weights of empty vehicles of major domestic vehicle models. Faster R-CNN, an object detection deep learning model, was trained using vehicle images classified by the classification table. The performance of the model is verified using images of CCTVs on actual bridges. Finally, the vehicle loading history of an actual bridge was obtained for a specific time by continuously estimating the vehicle loadings on the bridge using the proposed method.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.419-432
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• 2019

Most of deep learning model training was proceeded by supervised learning, which is to train labeling data composed by inputs and corresponding outputs. Labeling data was directly generated manually, so labeling accuracy of data is relatively high. However, it requires heavy efforts in securing data because of cost and time. Additionally, the main goal of supervised learning is to improve detection performance for 'True Positive' data but not to reduce occurrence of 'False Positive' data. In this paper, the occurrence of unpredictable 'False Positive' appears by trained modes with labeling data and 'True Positive' data in monitoring of deep learning-based CCTV accident detection system, which is under operation at a tunnel monitoring center. Those types of 'False Positive' to 'fire' or 'person' objects were frequently taking place for lights of working vehicle, reflecting sunlight at tunnel entrance, long black feature which occurs to the part of lane or car, etc. To solve this problem, a deep learning model was developed by simultaneously training the 'False Positive' data generated in the field and the labeling data. As a result, in comparison with the model that was trained only by the existing labeling data, the re-inference performance with respect to the labeling data was improved. In addition, re-inference of the 'False Positive' data shows that the number of 'False Positive' for the persons were more reduced in case of training model including many 'False Positive' data. By training of the 'False Positive' data, the capability of field application of the deep learning model was improved automatically.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.2
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• pp.24-29
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• 2009

Sound source localization system is used in a robot, a video conference and CCTV(Closed-circuit television) systems. In this Sound source localization systems are applied to human and they can receive a number of sound data frames during speaking. In this paper, we propose methods which is reducing angle estimation error by selecting sound data frame which can more precisely compute the angles from inputted sound data frame. After selected data converted to angle, the error of sound source localization recognition system can be reduced by applying to medium filter. By the experiment using proposed system it is shown that the average error of angle estimation in sound source recognition system can be reduced up to 31 %.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.125-133
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• 2016

In recent years, various crimes such as "random killing' crime continue to rise. Despite the government's crime prevention efforts and crime related researches, crime increases and a different approach is needed. Therefore, this study proposes the alternative for crime prevention by analyzing big data. To achieve this objective, this study was to perform visualization utilizing the histogram, the bubble chart and the hit map and association analysis. To analyze the relationship between crime and some variables, this study analyzed data of Seongnam city, Korea National Police Agency and etc. The results of analysis showed that CCTV will be to reduce the crime rate and security light is not significantly relevant. And the result showed that other types of crime focused by time of the day and day of the week and showed that an increase of the foreigners and crime increase are associated. This study presents a scheme for reducing the crime rate on the basis of this analysis result.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.488-490
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• 2022

Recently, interest in industrial accidents such as the Industrial Safety and Health Act and the Serious Accident Punishment Act is increasing, and the demand for safety managers for safety management of workers in research institutes and industrial fields of various fields is increasing. For worker safety management, CCTVs are being installed in factories and workplaces, and workers are monitored to enhance safety management. In this paper, we intend to design a dangerous situation assessment system by constructing data using CCTV in such a workplace and modeling it in JSON format. The data modeling was produced by referring to the data set construction guide for artificial intelligence learning and the quality management guideline of the Korea National Information Society(NIA). Through this system, we want to check what kind of risk management exists in the workplace by risk situation scenario and use it to build a more systematic system.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.148-152
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• 2007

This paper develops an integrated optic transmitter/receiver based on ring-type WDM PON. The optic transmitter/receiver can transmit real-time images from the CCTV of a remote street without compression and transmit TCP/IP data using an optic fiber. This system can also perform remote controls of the CCTV camera. The developed optic transmitter/receiver can provide the monitoring service of an advanced image quality of remote traffic using a broadband technology.