• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.114-123
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• 2023

With the development of computer vision technology, video sensors such as CCTV are detecting incident. However, most of the current incident have been detected based on existing fixed imaging equipment. Accordingly, there has been a limit to the detection of incident in shaded areas where the image range of fixed equipment is not reached. With the recent development of edge-computing technology, real-time analysis of mobile image information has become possible. The purpose of this study is to evaluate the possibility of detecting expressway emergencies by introducing computer vision technology to dash cam. To this end, annotation data was constructed based on 4,388 dash cam still frame data collected by the Korea Expressway Corporation and analyzed using the YOLO algorithm. As a result of the analysis, the prediction accuracy of all objects was over 70%, and the precision of traffic accidents was about 85%. In addition, in the case of mAP(mean Average Precision), it was 0.769, and when looking at AP(Average Precision) for each object, traffic accidents were the highest at 0.904, and debris were the lowest at 0.629.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.7
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• pp.1044-1049
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• 2014

This study was conducted in order to investigate whether the presence of light or different colors of light would influence the energy expenditure and behavior of broiler chickens. Eight 8-week-old broiler chickens were adapted to a respiration chamber (Length, 28.5 cm; Height, 38.5 cm; Width, 44.0 cm) for one week prior to the initiation of the experiment. In experiment 1, energy expenditure and behavior of the chickens were analyzed in the presence or absence of light for four days. Chickens were exposed to 6 cycles of 2 h light/2 h dark period per day. In experiment 2, the broiler chickens that had been used in experiment 1 were used to evaluate the effect of 4 different wavelength light-emitting diodes (LEDs) on the energy expenditure and behavior of broiler chickens. The LEDs used in this study had the following wavelength bands; white (control), red (618 to 635 nm), green (515 to 530 nm) and blue (450 to 470 nm). The chickens were randomly exposed to a 2-h LED light in a random and sequential order per day for 3 days. Oxygen consumption and carbon dioxide production of the chickens were recorded using an open-circuit calorimeter system, and energy expenditure was calculated based on the collected data. The behavior of the chickens was analyzed based on following categories i.e., resting, standing, and pecking, and closed-circuit television was used to record these behavioral postures. The analysis of data from experiment 1 showed that the energy expenditure was higher (p<0.001) in chickens under light condition compared with those under dark condition. The chickens spent more time with pecking during a light period, but they frequently exhibited resting during a dark period. Experiment 2 showed that there was no significant difference in terms of energy expenditure and behavior based on the color of light (white, red, green, and blue) to which the chickens were exposed. In conclusion, the energy expenditure and behavior of broiler chickens were found to be strongly affected by the presence of light. On the other hand, there was no discernible difference in their energy expenditure and behavior of broiler chickens exposed to the different LED lights.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.284-293
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• 2015

The objective of this paper is to determine the conditions of road surface by utilizing the images collected from closed-circuit television (CCTV) cameras installed on roadside. First, a technique was examined to detect wet surfaces at nighttime. From the literature reviews, it was revealed that image processing using polarization is one of the preferred options. However, it is hard to use the polarization characteristics of road surface images at nighttime because of irregular or no light situations. In this study, we proposes a new discriminant for detecting wet and dry road surfaces using CCTV image data at night. To detect the road surface conditions with night vision, we applied the wavelet packet transform for analyzing road surface textures. Additionally, to apply the luminance feature of night CCTV images, we set the intensity histogram based on HSI(Hue Saturation Intensity) color model. With a set of 200 images taken from the field, we constructed a detection criteria hyperplane with SVM (Support Vector Machine). We conducted field tests to verify the detection ability of the wet road surfaces and obtained reliable results. The outcome of this study is also expected to be used for monitoring road surfaces to improve safety.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Ecology and Resilient Infrastructure
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• v.3 no.3
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• pp.169-176
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• 2016

Roads are widely accepted to be as a major cause of habitat fragmentation. The wildlife road-crossing structure is one of the most acceptable alternatives among the solutions to provide connectivity between patches isolated by roads. We investigated noise disturbance, vegetation structure and wildlife crossing and habitation at a wildlife road-crossing structure located at the Jingmaei-Pass in Incheon, Korea, to monitor and evaluate its conservation value and ecological performance and to propose measures for their adaptive management. From the result of noise measurement, the noise disturbance from the road traffic was not properly blocked out at the wildlife crossing structure. The survey results of vegetation structure showed that the early-successional plant species such as Ambrosia trifida, Erigeron annuus, Pueraria lobata, Rosa multiflora invaded widely on the crossing structure. An efficient management of the vegetation should be necessarily considered for the facilitation of vegetation succession and the improvement of animal habitat. The crossing structure was used by limited mammal species: Apodemus agrarius, Nyctereutes procyonoides, Mogera wogura and Sciurus vulgaris coreae as the results of the monitoring using footprints and closed-circuit television. In conclusion, The Jingmaei-Pass wildlife crossing structure is unable to function properly as a biological corridor because of the interference of noise and flourishing disturbed vegetation. Therefore, proper alternatives are required for improving animal habitats and mobile environments to enhance the ecological function of a wildlife corridor.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.76-81
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• 2018

The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.

• 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.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.2
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• pp.48-61
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• 2020

The objective of this study is to estimate traffic capacity based on the heavy-vehicle ratio in a two-lane freeway work zone where one lane is blocked by construction. For this, closed circuit television (CCTV) video data of the freeway work zone was collected, and the congestion at an upstream point was observed. The traffic volume at a downstream point was analyzed after a bottleneck was created by the blockage due to the upstream congestion. A distribution model was estimated using observed-time headway, and the road capacity was analyzed using a goodness-of-fit test. Through this process, the general capacity and an equation for capacity based on the heavy-vehicle ratio passing through the work zone were presented. Capacity was estimated to be 1,181~1,422 passenger cars per hour per lane (pcphpl) at Yeongdong, and 1,475~1,589pcphpl at Jungbu Naeryuk. As the ratio of heavy vehicles increased, capacity gradually decreased. These findings can contribute to the proper capacity estimation and efficient traffic operation and management for two-lane freeway work zones that block one lane due to a work zone.

• Journal of Korea Game Society
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• v.11 no.5
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• pp.67-78
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• 2011

This paper introduces an efficient and satisfactory search interface that enables users to browse and find the video data they want from a massively huge video database widely used in various multimedia environment. The target user group is information analysts at US defense industry or governmental intelligence agencies whose job is to identify a certain person from a lot of video footage taken from CCTV(Closed-circuit Television) cameras. For the first user test, we suggested the CAVE-like virtual reality interface to be the most optimal for the tasks we designed for, so we compared this interface with desktop interface. The softwares and database developed and optimized for each task were used in this user test. For the second user test, we researched on what input devices would be most optimal for enhancing efficiency of search task in the CAVE-like virtual reality system. Especially we focused our effort on measuring the effectiveness and user satisfaction of three different types of devices that embody gestural interface input system that encourages users' ergonomic control of the interface. We also measured the time consumed for performing each task to find out the most efficient input device among the ones tested.