• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.134-143
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• 2020

With the worldwide spread of African swine fever, interest in livestock epidemics is growing. Livestock transport vehicles are the main cause of the spread of livestock epidemics, but no empirical quarantine procedures and standards related to the mobility of livestock transport vehicles in South Korea. This study extracted livestock-related vehicles' trajectory by utilizing the facility visit history data from the Korea Animal Health Integrated System and the DTG (Digital Tachograph) data from the Korea Transportation Safety Authority and presented them as exposure indexes aggregating the link-time occupancy of each vehicle. As a result, a total of 274,519 livestock-related vehicle trajectories were extracted, and exposure values by link and zone were quantitatively derived. Through this study, it is expected that prior monitoring of livestock transport vehicles and the establishment of post-disaster prevention policies would be provided.

• Spatial Information Research
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• v.21 no.3
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• pp.11-19
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• 2013

Compared with traditional video monitoring systems that provide a video-recording function as a main service, an intelligent video monitoring system is capable of extracting/tracking objects and detecting events such as car accidents, traffic congestion, pedestrian detection, and so on. Thus, the object tracking is an essential function for various intelligent video monitoring and surveillance systems. In this paper, we propose a background and local histogram-based object tracking approach for intelligent video monitoring systems. For robust object tracking in a live situation, the result of optical flow and local histogram verification are combined with the result of background subtraction. In the proposed approach, local histogram verification allows the system to track target objects more reliably when the local histogram of LK position is not similar to the previous histogram. Experimental results are provided to show the proposed tracking algorithm is robust in object occlusion and scale change situation.

• Spatial Information Research
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• v.2 no.2
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• pp.147-163
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• 1994

This paper presents three methods of generating the transportation network data out of the topological geographic database in the hope that the conversion of the geographic database file containing the topology to the conventional node-link type trans¬portation network file may facilitate the integration between transportation planning mod¬els and GIS by alleviating the inherent problems of both computing environments. One way of the proposed conversion method is to use the conversion software that allows the bi-directional conversion between the UTPS (Urban Transportation Planning System) type transportation planning model and GIS. The other two methods of data structure conversion approach directly transform the GIS's user-level topology into the transportation network data topology, and have been introduced with codes programmed with FORTRAN and AML (Arc Macro Language) of ARC/INFO. If used successfully, any approach would not only improve the efficiency of transportation planning process and the associated decision-making activities in it, but enhance the productivity of trans¬portation planning agencies.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.1
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• pp.32-39
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• 2016

Intelligent Transport Systems (Intelligent Transportation System: ITS) is a system for inducing a flow of ideal car for using the most advanced technology, it is determined the status of the road, and take appropriate action. In order to be measured at various time points, and is managed, the information about the traffic situation is used image using a computer mainly. The image processing using a computer, it is an easy way to collect parameters of the various traffic in real time, technology has developed more and more. Vehicle detection of transport parameters of intelligent transportation system is a very important technology basically. Therefore, technology detection method using car background images and the contour line extraction method using an edge is used, however, problems have been raised on the accuracy of the detection rate.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.167-182
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• 2022

The accident data attributes of the traffic accident report are used not only in traditional traffic safety-related research to identify the cause of traffic accidents, but also as basis data for the development of the automated vehicle driving performance verification scenarios. However, since the data attributes of the traffic accident report are limited for the purpose of reconstructing the traffic situation and developing scenarios, this study aims to provide the directions for improvement of traffic accident report, ultimately for its expanded usability for the automated vehicle test scenarios. The directions for improvement of the traffic accident report are provided by categorizing the traffic situation before the accident (pre-crash), the situation immediately before or during the accident (on-crash), and the situation after the accident (post-crash), respectively. Additional data items or data processing methods are presented. Furthermore, data elements that can be extracted from the traffic accident process data in the unstructured narrative form are explored and provided.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.83-92
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• 2005

This study if the first trial toward realizing a new methodology for vehicle re-identification based on heterogeneous sensor systems. A major interest of the author is how to effectively utilize information obtained from different sensors to derive accurate and reliable section travel times. The 'blade' sensor that is a newly developed sensor for capturing vehicle wheel information and the existing square loop sensor are employed to extract the inputs of the proposed vehicle re-identification algorithm. The fundamental idea of the algorithm developed in this study, which is so called 'anonumous vehicle re-identification,' it to match vehicle features obtained from both sensors. The results of the algorithm evaluation reveal that the proposed methodology could be successfully implemented in the field. The proposed methodology would be an invaluable tool for operating agencies in support of traffic monitoring systems and traveler information systems.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.44-51
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• 2005

In this study, the method of extracting road centerline's coordinate and road facilities is presented using RC helicopter photogrammetry system. From the survey of extracted road centerline, the errors turned out to be -0.117m ~ 0.103m on the X-axis and -0.014m ~ 0.009m on the Y-axis when RC Helicopter photogrammetry system utilized. By application of this system, hereafter, not only management of road facilities but also construction of DB would be enable which need positioning and design of alignment on the access is not easy area such as traffic congestion or toparchy area.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.859-870
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• 1997

Computerized map reading system is one of the most important application areas in the image processing.A map databaes can be used for a wide range of scial activities such as narural resource assessment,regional plan-ming,and reaffic nabigation system. The road segments,however,are extracted as briken in the area where they are overlapped and interupted by chracters and symbols.Few approaches have been taken to complete road segnents interupted by map symbols.In this paper,a movel approach for the extracation and completion of road segements interupted by map symbols is proposed using neural networks.The system is applied to 1/25,000 scaled maps published by the Grographical Survey Unstitute of Ministry of Construction of Korea.It will be shown that the system can extract and reconstruct road segmetns for the various areas of maps sucessfully.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.601-603
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• 2003

최근에 차량수의 증가로 인하여 교통량이 증가하고 그로 인하여 ITS(Intelligent Transport System)에 대한 관심이 증가하게 되었다. 그 중에서도 LPR system(License Plate Recognition system)은 ITS에서 중요한 역할을 한다. 본 논문에서는 차량의 번호를 인식하기 위해 선행되어야 하는 과정인 대상 차량의 번호판 영역을 추출하고 구성 숫자들을 분리하는 알고리즘을 제안한다. 이 알고리즘은 영상에서 차량의 번호판 영역을 찾는 부분과 번호판의 숫자를 분리하는 부분으로 구성이 되어 있다. 먼저 입력 영상에서 gradient를 구하게 된다. 구해진 gradient에서 차량의 구조와 transition의 횟수를 조사를 통해서 번호판 영역을 찾게 된다. 찾아진 번호판 영역에서 adaptive threshold를 적용하여 숫자들을 분리하게 된다. 실내 주차장 환경에서 촬영된 영상을 대상으로 실험을 수행하고 그 결과를 정리하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.367-371
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• 2019

'Scientificization' of oriental medicine is a task to be preceded for K-MEDI in the world. Also, We are trying to secure efficacy and safety through scientifically proving the efficacy of Oriental medicine. This paper. We propose a biomarker extraction algorithm for genetic lesion reading of Oriental medicine. Also, A variety of applications in terms of Oriental medicine. Oriental medicine was suggested as a basis for the diagnosis and treatment of the treatment.