• Title/Summary/Keyword: 개별차량

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Car Plate Recognition using Morphological Information and Enhanced Neural Network (형태학적 정보와 개선된 신경망을 이용한 차량 번호판 인식)

  • 임은경;김광백
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.192-197
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    • 2004
  • 본 논문에서는 수평ㆍ수직 에지의 형태학적 정보를 이용한 차량 번호판 추출과 개선된 RBF 네트워크를 이용한 차량 번호판 인식 시스템을 제안한다. 번호판 영역은 수평ㆍ수직 에지의 형태학적 정보를 이용하여 추출하고 개별 문자는 히스토그램 방법과 위치 정보를 이용한 방법에 윤곽선 추적 알고리즘을 병합하여 추출한다. 개별 문자 인식은 ARTI 알고리즘을 개선하여 지도 학습 방법과 결합한 개선된 신경망을 제안하여 차량 번호판 인식에 적용한다. 제안된 방법의 성능을 확인하기 위하여 트루 컬러 차량 영상 155개와 그레이 컬러 차량 영상 100개를 대상으로 실험한 결과, 수평ㆍ수직 에지의 형태학적 정보를 이용한 차량 번호판 추출 방법이 임계화를 이용한 차량 번호판 추출 방법, RGB와 HSI 컬러 정보를 각각 이용한 차량 번호판 추출 방법보다 추출률이 개선되었으며, 인식 성능도 개선된 신경망의 학습 알고리즘이 기존의 학습 알고리즘들보다 우수한 성능이 있음을 확인하였다.

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Development of a Real Time Video Image Processing System for Vehicle Tracking (실시간 영상처리를 이용한 개별차량 추적시스템 개발)

  • Oh, Ju-Taek;Min, Joon-Young
    • International Journal of Highway Engineering
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    • v.10 no.3
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    • pp.19-31
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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 wide-area detection, i.e., multi-lane surveillance algorithm provide traffic parameters with single camera 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. The objective of this research was to relate traffic safety to VIPS tracking and this paper has developed a computer vision system of monitoring individual vehicle trajectories based on image processing, and offer the detailed information, for example, volumes, speed, and occupancy rate as well as traffic information via tripwire image detectors. Also the developed system has been verified by comparing with commercial VIP detectors.

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Development of The Signal Control Algorithm Using Travel Time Informations of Sectional Detection Systems (구간검지체계의 통행시간정보를 이용한 신호제어 알고리즘 개발)

  • Jung, Young-Je;Kim, Young-Chan;Baek, Hyon-Su
    • Journal of Korean Society of Transportation
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    • v.23 no.8 s.86
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    • pp.181-191
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    • 2005
  • This study developed an algorithm for real-time signal control based on the detection system that can collect sectional travel time. The signal control variable is maximum queue length per cycle and this variable has a sectional meaning. When a individual vehicle pass through the detector, we can gather the vehicle ID and the detected time. Therefor we can compute the travel time of an individual vehicle between consecutive detectors. This travel time informations were bisected including the delay and not. We can compute queue withdrawing time using this bisection and the max queue length is computed using the deterministic delay model. The objective function of the real-time signal control aims equalization of queue length for all direction. The distribution of the cycle is made by queue length ratios.

Estimation of Individual Vehicle Speed Using Single Sensor Configurations (단일 센서(Single Sensor)를 활용한 차량속도 추정에 관한 연구)

  • Oh, Ju-Sam;Kim, Jong-Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.461-467
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    • 2006
  • To detect individual vehicular speed, double loop detection technique has been widely used. This paper investigates four methodologies to measure individual speed using only a single loop sensor in a traveling lane. Two methods developed earlier include estimating the speed by means of (Case 1) the slop of inductance wave form generated by the sensor and (Case 2) the average vehicle lengths. Two other methods are newly developed through this study, which are estimations by measuring (Case 3) the mean of wheelbases using the sensor installed traversal to the traveling lane and (Case 4) the mean of wheel tracks by the sensor installed diagonally to the traveling lane. These four methodologies were field-tested and their accuracy of speed output was compared statistically. This study used Equality Coefficient and Mean Absolute Percentage Error for the assessment. It was found that the method (Case 1) was best accurate, followed by method (Case 4), (Case 2), and (Case 3).

A Car License Plate Recognition Using Morphological Characteristic, Difference Operator and ART2 Algorithm (형태학적 특징 및 차 연산과 ART2 알고리즘을 이용한 차량 번호판 인식)

  • Kang, Moo-Jin;Kim, Jae-Kun;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.431-435
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    • 2008
  • 2006년 11월 이후 신 차량 번호판 등장 후, 신 차량 번호판과 구 차량 번호판이 혼합되어 있다. 이에 따라 속도위반, 신호위반 단속, 무인 주차관리 시스템, 범죄 및 도주 차량 검거, 고속도로 톨게이트에서 통행료 지불로 인한 교통 체증현상을 해소하기 위한 자동 요금 징수와 같은 다양한 경우에서 자동차 번호판의 특징에 맞는 인식 시스템이 요구되고 있다. 따라서 본 논문에서는 이러한 문제를 해결하기 위해 형태학적 특징 및 차 연산과 ART2 알고리즘을 이용한 차량 번호판 인식 방법을 제안한다. 무인 카메라에서 획득된 차량 번호판 영상에서 차 연산을 이용하여 에지를 추출한 후에 블록 이진화를 한다. 이진화 된 차량 영상에서 신 구 차량 번호판의 형태학적 특성을 8방향 윤곽선 추적 알고리즘에 적용하여 잡음 영역을 제거하고, 차량의 번호판 영역을 추출한다 추출된 번호판 영역에 대하여 평균 이진화와 최대 최소 이진화를 적용하여 번호판의 개별 영역에 대한 형태학적 특성을 고려하여 잡음을 제거하고, Labeling 알고리즘을 적용하여 개별 문자를 추출한 후에 결합한다. 이렇게 분류된 개별 문자 및 숫자 코드를 ART2 알고리즘에 적용하여 학습 및 인식을 한다. 제안된 차량 번호판 추출 및 인식 방법의 성능을 평가하기 위해 녹색 번호판과 흰색 번호판 이미지 각각 100장을 대상으로 실험한 결과, 제시 된 차량 번호판 추출 및 인식 방법이 실험을 통해서 효율적인 것을 확인하였다.

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Recognition System of Car License Plate using Fuzzy Neural Networks (퍼지 신경망을 이용한 자동차 번호판 인식 시스템)

  • Kim, Kwang-Baek;Cho, Jae-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.5
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    • pp.313-319
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    • 2007
  • In this paper, we propose a novel method to extract an area of car licence plate and codes of vehicle number from a photographed car image using features on vertical edges and a new Fuzzy neural network algorithm to recognize extracted codes. Prewitt mask is used in searching for vertical edges for detection of an area of vehicle number plate and feature information of vehicle number palate is used to eliminate image noises and extract the plate area and individual codes of vehicle number. Finally, for recognition of extracted codes, we use the proposed Fuzzy neural network algorithm, in which FCM is used as the learning structure between input and middle layers and Max_Min neural network is used as the learning structure within inhibition and output layers. Through a variety of experiments using real 150 images of vehicle, we showed that the proposed method is more efficient than others.

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A Methodology for Estimating Section Travel Times Using Individual Vehicle Features (개별차량의 고유특성을 이용한 구간통행시간 산출기법 개발)

  • O, Cheol
    • 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.

Designing A V2V based Traffic Surveillance System and Its Functional Requirements (V2V기반 교통정보수집체계 설계 및 요구사항분석)

  • Hong, Seung-Pyo;Oh, Cheol;Kim, Won-Kyu;Kim, Hyun-Mi;Kim, Tae-Hyung
    • Journal of Korean Society of Transportation
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    • v.26 no.4
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    • pp.251-264
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    • 2008
  • One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

Traffic Signal Control Algorithm for Isolated Intersections Based on Travel Time (독립교차로의 통행시간 기반 신호제어 알고리즘)

  • Jeong, Youngje;Park, Sang Sup;Kim, Youngchan
    • Journal of Korean Society of Transportation
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    • v.30 no.6
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    • pp.71-80
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    • 2012
  • This research suggested a real-time traffic signal control algorithm using individual vehicle travel times on an isolated signal intersection. To collect IDs and passing times from individual vehicles, space-based surveillance systems such as DSRC were adopted. This research developed models to estimate arrival flow rates, delays, and the change rate in delay, by using individual vehicle's travel time data. This real-time signal control algorithm could determine optimal traffic signal timings that minimize intersection delay, based on a linear programming. A micro simulation analysis using CORSIM and RUN TIME EXTENSION verified saturated intersection conditions, and determined the optimal traffic signal timings that minimize intersection delay. In addition, the performance of algorithm varying according to market penetration was examined. In spite of limited results from a specific scenario, this algorithm turned out to be effective as long as the probe rate exceeds 40 percent. Recently, space-based traffic surveillance systems are being installed by various projects, such as Hi-pass, Advanced Transportation Management System (ATMS) and Urban Transportation Information System (UTIS) in Korea. This research has an important significance in that the propose algorithm is a new methodology that accepts the space-based traffic surveillance system in real-time signal operations.

Remote Vehicle Diagnostic System Using Mobile Handsets (휴대전화기를 이용한 원격차량진단 시스템)

  • Jung, Doo-Hee;Jeong, Gu-Min;Ahn, Hyun-Sik
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.2582-2584
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    • 2005
  • 차량 진단 기능이 탑재된 원격 서버, 제어신호 중계 기능을 가진 휴대폰용 어플, 그리고 신호 변환을 위한 converting 보드를 사용하여 기존의 차량진단기(scanner)와 동일한 기능을 가지는 원격차량진단 시스템을 제안한다. 원격 서버에서 직접 차량 진단 기능을 수행함으로써 진단 이력에 대한 자동 관리가 가능하며 다양한 부가 서비스를 연계하여 제공할 수 있다. 또한 신규 차종에 대하여 원격 서버 프로그램의 변경으로 대응이 가능하므로 기존 방식처럼 신규 차종에 대한 개별 upgrade가 필요 없다. 제안한 방식은 저가의 진단 시스템 구축이 가능하므로 영업소에서만 사용되던 차량진단기를 개별 사용자가 사용할 수 있게 해준다.

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