• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.88-98
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• 2021

Recently, the crime prevention and culprit identification even in a low illuminated environment by CCTV is becoming ever more important. In a low lighting situation, CCTV applications capture images under infrared lighting since it is unobtrusive to human eye. Although the infrared lighting leads to advantage of capturing an image with abundant fine texture information, it is hard to capture the color information which is very essential in identifying certain objects or persons in CCTV images. In this paper, we propose a method to acquire color information through DCGAN from an image captured by CCTV in a low lighting environment with infrared lighting and a method to remove color noise in the acquired color image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.567-574
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• 2012

For the past few years, the video surveillance market has shown a rapid growth due to the increasing demand for Closed Circuit Television(CCTV) by the public sector and the private security industry. While the overall utilization of CCTV in the public and private sectors is expanding, its usage in the field of disaster management is less than sufficient. Therefore, the authors of this study, in an effort to revisit the role of CCTV in disaster situations, have carried out a case analysis in the vicinity of the Gangnam Station which has been designated as a natural disaster-prone area. First, the CCTV images around the target location are collected and the time and depth of inundation are measured through field surveys and image analyses. Next, a rainfall analysis was conducted using the Automatic Weather Station(AWS) data and the past inundation records. Lastly, the authors provide an estimate of rainfall for the areas around the station and suggest viable warning systems and countermeasures. The results from this study are expected to make positive contributions towards a significant reduction of the damages caused by the floods around the Gangnam Station.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.99-105
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• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• Journal of Information Technology Applications and Management
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• v.11 no.4
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• pp.169-179
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• 2004

There are many inductive loop detectors under the highways in Korea. Among the other detectors, some are image detectors. Almost all image detectors are focused one or two lane of the road and are measuring traffic information. This paper proposes to an algorithm for detecting traffic information automatically from CCTV camera images installed on the highway. The information which is counted in one lane or two contains some critical errors by occlusion frequently in case of passing larger vehicles. In this paper, we use a tracking algorithm in which the detection area include all lanes, then the traffic informations are collected from the vehicles individually using difference images in this detection area. This tracking algorithm is better than lane by lane detecting algorithm. The experiment have been conducted two different real road scenes for 20 minutes. For the experiments, the images are provided with CCTV camera which was installed at Kiheung Interchange upstream of Kyongbu highway, and video recording images at Chungkye Tunnel. For image processing, images captured by frame-grabber board 30 frames per second, 640${\times}$480 pixels resolution and 256 gray-levels to reduce the total amount of data to be Interpreted.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.65-70
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• 2023

In this paper, we propose a CCTV storage space securing model using YOLO v3. CCTV is installed and operated in various parts of society for disasters, disasters and safety such as crime prevention, fire prevention, and monitoring, and the number of CCTV is increasing and the quality of the video quality is improving. Due to this, as the number and size of image files increase, it is difficult to cope with the existing storage space. In order to solve this problem, we propose a model that detects specific objects in CCTV images using YOLO v3 library and deletes unnecessary frames by saving only the corresponding frames, thereby securing storage space by reducing the size of the image file, and thereby Periodic images can be stored and managed. After applying the proposed model, it was confirmed that the average image file size was reduced by 94.9%, and it was confirmed that the storage period was increased by about 20 times compared to before the application of the proposed model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1130-1135
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• 2022

In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office has built a control center for CCTV control and is performing 24-hour CCTV video control for the safety of citizens. Seoul Metropolitan Government is building a smart city integrated platform that is safe for citizens by providing CCTV images of the ward office to enable rapid response to emergency/emergency situations by signing an MOU with related organizations. In this paper, when an incident occurs at the Seoul Metropolitan Government Office, the escape route is predicted by discriminating people and vehicles using the AI DNN-based Template Matching technology, MLP algorithm and CNN-based YOLO SPP DNN model for CCTV images. In addition, it is designed to automatically disseminate image information and situation information to adjacent ward offices when vehicles and people escape from the competent ward office. The escape route prediction and tracking system using artificial intelligence can expand the smart city integrated platform nationwide.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.408-414
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• 2010

When we are collecting traffic information on CCTV images, we have to install the detect zone in the image area during pan-tilt system is on duty. An automation of detect zone with pan-tilt system is not easy because of machine error. So the fisheye lens attached camera or convex mirror camera is needed for getting wide area images. In this situation some troubles are happened, that is a decreased system speed or image distortion. This distortion is caused by occlusion of angled ray as like trembled snapshot in digital camera. In this paper, we propose two methods of de-blurring to overcome distortion, the one is image segmentation by nonlinear diffusion equation and the other is deformation for some segmented area. As the results of doing de-blurring methods, the de-blurring image has 15 decibel increased PSNR and the detection rate of collecting traffic information is more than 5% increasing than in distorted images.

• Journal of IKEEE
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• v.17 no.2
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• pp.104-110
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• 2013

In this paper, we introduce a smart care surveillance system which can support various CCTV cameras. In order to monitor an emergency requester in case of emergency, the server performs automatical CCTV Pan, Tilt, and Zoom control based on the location coordinates of the emergency requester. Also, a server finds and tracks the emergency requester using image processing and the updated location information. We implement a smart care surveillance system using the Genetec SDK tool to support various CCTV cameras. The efficiency of the rescue operation with the smart care surveillance system can be improved because rescuer can quickly control and monitor the requester's CCTV images.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.125-138
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• 2011

The highway visibility reduction caused by fog is one of the major elements of traffic accidents. Though the fog warning systems can lead drivers into safe driving by letting them aware dangerous situations in advance, the optical sensors, such as fog sensor, has been extremely costly. Through recent studies, it is delivered that visibility measurements have become obtainable with relatively cheap cameras and their functionality is as similar as a driver' visual sense. Those measurements however require additional signs or ROI, so it is still costly and unable to utilize the conventional images from the existing systems. This study proposes a new method to detect the visibility in real time based on the conventional images from the existing CCTV cameras. The proposed method builds a road model and extracts and applies vehicle movements and visible lines - those highlight easy and quick visibility measurements. The proposed method has advantages of both (1) having possible day and night visibility measurements similar to drivers' visual sense and (2) being easily applied to the existing CCTV system without additional devices. This paper presents field experiments using images acquired from the Central Inland Expressway and discusses future research directions.

• Korean Journal of Childcare and Education
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• v.13 no.6
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• pp.43-67
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• 2017

Objective: The purpose of this study was to explore the feasibility to utilize image data recorded and accumulated from CCTV at child care centers. Methods: Literature reviews, consultations and workshops with scholars studying child development, legal professionals, and engineers, focus group interviews with professionals working with young children, and surveys targeting parents, directors and teachers were implemented. Results: It was found the big data from CCTV at child care centers can be used to make policies and implement research as a secondary data set after anonymization. Extracting implicit and useful data from images stored on CCTV is technically feasible. Also, it can be legally guaranteed to analyze the data under the condition of acquiring informed consents. Conclusion/Implications: It was likely to utilize image data from CCTV at child care centers as a secondary data set in order for policy development and scholarly purposes, after overcoming obstacles of the budget for additional infrastructures and consents of information holders.