• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.833-836
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• 2013

In this paper, we proposed an intelligent surveillance system which can be determined by the overspeed of vehicle which continuously collects by video imaging device. Imaging device to capture images continuously, and filtering errors that occur as a natural, long-distance moving objects by comparing the images collected before and after the images. To measure the size of things, it proves that able to measure speed of the vehicle, depending on the amount of growing pixels using the pixel processing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.317-319
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• 2021

In Korea, an intelligent transportation system(ITS) is established to efficiently operate traffic congestion on roads and is being used for traffic information collection and speed control systems. Currently, designated and dedicated lanes are in place to ensure traffic circulation and traffic safety, and systematic and accurate illegal vehicle crackdown systems with artificial intelligence technology are needed. In this study, we propose a vehicle number recognition model that can improve the efficiency of the traffic of designated vehicles. By applying computer vision technology, we are going to identify three-lane and four-lane multi-lane roads in real time and detect vehicle numbers by car to suggest ways to crack down on vehicles that violate the designated lane system.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.121-123
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• 2004

차량 번호판 인식 시스템은 무인 카메라 등의 영상 장치로부터 입력된 차량 이미지로부터, 차량 번호판 정보를 읽어내는 시스템이다. 이러한 차량 번호판 인식 시스템의 응용 시스템 중 과속 차량 단속과 같은 일부 응용 시스템은 번호판의 글자나 숫자를 다른 글자나 숫자로 잘못 인식할 경우 심각한 문제를 발생시킬 수 있다. 이러한 시스템을 위해 우리는 인식 결과에 대한 신뢰도가 낮은 경우 인식을 포기 또는 위임하는 신중한 분류기(Cautious Classifier)를 이용 인식 시스템을 구성하였다. 또한 학습 예제의 가중치를 조절하는 방법을 사용 이러한 신중한 분류기의 성능을 향상 시켰다. 실제 번호판 인식 실험 결과 우리가 제안한 가중치 부여 방식이 차량 번호판 인식 문제에 좋은 결과를 보임을 확인하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.549-551
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• 2006

Vehicle License Plate Recognition System reads information from vehicles license plate using image detection devices. Of many applications provided by Vehicle License Plate Recognition System, some, such as speed enforcing system, can be problematic when the system incorrectly scans letters or numbers from a vehicle's license plate. Using Cautious Classifier avoids such problems by discarding the scanned information when the confidence level is doubted to be low. This study develops the License Plate Recognition System using Cautious Classifier and investigates effectiveness of applying the Weighted Instance Method to improve the performance of Cautious Classifier.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.164-181
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• 2023

In a low speed limit environment, the speed limit tolerance of automated traffic enforcement devices is very high, which is one of the main factors for the low compliance rate. Therefore, in this study, we aimed to the improve the speed limit tolerance and to present a new standard. The effects of the operator and user errors that can cause speeding by drivers were analyzed. Based on the results of the analysis, an improvement of the tolerance was proposed by applying an error in the enforcement device and GPS speed. In addition, long-term expected safety effects such as the accident rate and severity were estimated from the operator's perspective when improving the tolerance. As a result of the estimation, the speed limit compliance rate, accident rate, and change rate of a number of severe accidents due to speed change, and pedestrian traffic accident mortality rate were all improved in all speed limit environments. The introduction of the proposed improvement is expected to improve road safety significantly.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.163-174
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• 2002

Speeding has been reported as one of the major causes for fatal traffic accidents in Korea. The resolution against this dangerous speeding comes to make the automated speed enforcement system an enforcement tool. The speed detection device, which measures speeds of each incoming vehicles using double loop sensors, requires high accuracy. The object of this study is to develop an accurate speed measurement algorithm using double loop detectors. Some important findings are summarized as follows: 1) It was found that speed measurement errors are caused by scanning rate, distance of two loops, irregular vehicle trajectories, multiple vehicles in detection zone. 2) A proposed algorithm using two signal set proved to reduce variance as well as mean of speed measurement. 3) A proposed filtering algorithm was effective to filter irregular driving vehicles and multiple vehicles in detection zone. A comprehensive field test of developed algorithm resulted in significant improvement of speed measurement accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.105-115
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• 2017

Conventional traffic detection sensors such as loop detectors and image sensors are expensive to install and maintain and require different detection algorithms depending on the night and day and have a disadvantage that the detection rate varies widely depending on the weather. On the other hand, the millimeter-wave radar is not affected by bad weather and can obtain constant detection performance regardless of day or night. In addition, there is no need for blocking trafficl for installation and maintenance, and multiple vehicles can be detected at the same time. In this study, a multi-target detection algorithm for a radar sensor with this advantage was devised / implemented by applying a conventional single target detection algorithm. We performed the evaluation and the meaningful results were obtained.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.531-538
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• 2016

Driving behaviors such as speeding and illegal u-turn which violate traffic rules are main causes of car accidents, and they can lead to serious accidents. Bus drivers are less aware of dangers of illegal u-turn, and infrastructures such as traffic enforcement equipment and watchmen are deficient. This research aims to develop technology for estimating driving behaviors based on map-matching in order to prevent illegal u-turns. For this research, 23,782 of u-turn permit data and 146,000 of speed limit data are collected nationwide, and an estimation algorithm is built with these data. Then, an application based on android is developed, and finally, tests are conducted to assess the accuracy in data computations and GPS data map-matching, and to extrapolate driving behavior. As a result of the tests, the accuracy results in the map-matching is 86% and the assessment of driving behavior is 83%, while the display of the data output yielded 100% accuracy. Additional research should focus on improvement in accuracy through the development of a robust monitoring system, and study of service scenarios for technology application.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.179-184
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• 2021

Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.