• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.1987-1996
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• 2009

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4100-4107
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• 2010

The wrecker truck of lift type is used to move damaged car in accident spot or to move illegal vehicle in towaway zone toward pound.. This special vehicle drives by lifting front or rear side of car with the driving type of towed car. Each car is modelled with CATIA and is simulated with FEM analysis program ANSYS. This study analyzes how dangerous is the triple collision among the wrecker-towed car-driving car as comparing with the usual collision accident with cars. It is studied how responsible is the towed car in case of crashing its back side by driving car. The influence on the driving angle of towed car by lifting wrecker is also considered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.830-833
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• 2016

자동차 번호판 인식은 대중적인 감시 기술 중의 한 종류로서, 주어진 비디오나 영상 내 광학문자 인식을 수반한다. 고속도로나 국도 상에 과속 단속 시스템, 재형 건물이나 유통센서 및 주차장 등에서 주차 정산 시스템, 고속도로 톨 게이트에서 hi-pass 에러 및 불법 도주 차량 잔속 시스템, 전국 주요 도로 불법 주 정차 단속 시스템, 공공기관, 기업 출퇴근 시간 확인 및 외부 차양 안내 시스템 등의 지능형 교통 시스템(ITS)이나 국도 상에 범위 차량 검거 시스템, 사건 발생 시 주요 도로상에 설치된 CCTV를 통해 용의 차량 이동 추적 시스템, 이동식 범죄 차량 조회, 버스에 탑재된 버스 전용차선 위반 단속들의 지능형 방범 시스템 등에 활용하고 있다. 번호판 인식은 자동차 번호판 국부화, 번호판의 크기, 차원, 명암대비, 밝기를 조정하는 정규화, 개별문자를 얻어내는 문자 분할, 문자를 인식하는 광학 문자 인식, 번호판의 형태, 크기, 위치 들이 연도별, 지역별로 차이가 있는 번호판들의 데이터베이스를 비교하여 구문 분석을 하는 절차를 거친다. 본 논문에서는 EmguCV를 이용하여 구현한 번호판 감지를 수행하여 위치를 찾아내고, 오픈 소스 광학 문자 인식 엔진으로 잘 알려져 있는 테서렉트 OCR을 이용하여 번호판의 문자를 인식하는 자동 인식 프로그램을 구현하고 기술하였다.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.143-156
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• 2003

도시로의 집중현상에 따라 차량이 증가함으로 한정된 공간에서의 도시교통난이 계속 악화되고 있는 실정이다. 도로상의 불법 주ㆍ정차위반차량으로 인해 차량소통에 불편을 주고, 주거 및 교통환경을 저해하기 때문에 견인업무는 주차정책을 실현시키는 강력한 수단으로써 반드시 필요하지만, 우리나라에서 불법 주ㆍ정차 차량의 견인부분에 대한 연구 및 결과는 극히 미비한 실정이다. 이에 따라 본 연구에서는 우리나라 주요 도시를 대상으로 불법 주ㆍ정차 차량의 견인운행 실태 및 특징을 비교, 견인제도의 문제점을 분석하여 개선방안을 검토하고자 하였다. 이의 내용으로는 각 시에서 추진 및 계획중인 지능형 교통체계(ITS), 버스 정보시스템(BIS) 및 차량 위치 자동 표시기(AVM)를 연계시켜 공차거리를 줄이는 등의 첨단체계를 구축하여 견인차량에 대한 운영을 효율적으로 하여야 할 것이고, 요금의 구조도 서울을 제외한 기존의 3단계 톤급별 요금구조에서 장래 대형차의 견인을 감안한 4단계의 톤급별 요금구조로의 조정방안이 필요하다. 견인비용에 있어서도 대부분의 도시가 수년전의 여건을 근거로 산출한 결과를 기준으로 요금을 징수하고 있어 현실에 맞지 않는 요금체계를 적용시키고 있는 실정이다. 따라서, 견인비용부분에 대하여도 장래의 경제여건을 감안한 탄력적 요금체계를 설정하여 경영합리화를 유도함이 바람직하다. 부가하여, 견인원가에 대한 사례분석 결과는 부천시를 중심으로 하여 현실성 있는 견인비용을 제시코자 하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.1
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• pp.6-17
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• 2013

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.273-278
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• 2008

Cars attaching new license plates are increasing after introducing the new format of car license plate in Korea. Therefore, a car new license plate recognition system is required for various fields using automatic recognition of car license plates, automatic parking management systems and arrest of criminal or missing vehicles. In this paper, we proposed an intelligent new car license plate recognition method for the various fields. The proposed method is as follows. First of all, an acquired color image from a surveillance camera is converted to a gray level image and binarized by block binarization method. Second, noises of the binarized image removed by morphological characteristics of cars and then license plate area is extracted. Third, individual characters are extracted from the extracted license plate area using Grassfire algorithm. lastly, the extracted characters are learned and recognized by a fuzzy ART algorithm for final car license plate recognition. In the experiment using 100 car images, we could see that the proposed method is efficient.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.349-352
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• 2006

To cope with traffic congestion, traffic accidents and lack of parking facilities, caused by dramatic increase in total vehicle number, vigorous researches on managing vehicles efficiently are done, both domestically and internationally. The vehicle license plate recognition makes effective management of traffic possible, with its wide application in many fields, covering from speed enforcement, collecting toll, stolen vehicle detection to parking management. The vehicle license plate recognition system causes high cost for collecting training data. Many researches are done by using the virtual sample method, which can be effective for utilizing limited number of training data by generating virtual sample. This paper investigates techniques to improve the performance of vehicle license plate recognition by using the training data's annexation. Also, popular methods for virtual sample creation used for text recognition algorithm are analyzed and their effectiveness is verified.