License plate extraction method for identification of vehicle violations at a railway level crossing

被引:0
|
作者
B. K. Cho
S. H. Ryu
D. R. Shin
J. I. Jung
机构
[1] Korea Railroad Research Institute,Department of Electronics and Computer Engineering
[2] Hanyang University,School of Information & Communication Engineering
[3] Sungkyunkwan University,undefined
关键词
Railway level crossing; License plate extraction; Digital image processing;
D O I
暂无
中图分类号
学科分类号
摘要
The primary cause of most railroad accidents is vehicle entry into railway level crossings despite warning messages. To identify drivers who violate railway level crossing regulations, vehicle license plate recognition can be applied at railway level crossings. The purpose of this paper is to present an effective method for extracting the license plate region from vehicle images taken at railway level crossings. The method proposed in this paper uses the variation in the gray-level values across the image of a license plate. For license plate region extraction, the character region is first recognized by identifying the character width and the difference between the background region and the character region. The license plate region is then extracted by finding the inter-character distance in the plate region. In addition, the license plate type is identified by the difference in the gray-level value between the background region and the character region. The proposed method is effective in solving the current challenges in extracting the license plate region from the damaged frames of license plates issued for domestic use, including new types of license plates. According to the experimental results, the proposed method yields a high extraction rate of 99.5% for vehicle license plates.
引用
收藏
页码:281 / 289
页数:8
相关论文
共 50 条
  • [21] License Plate Extraction and Recognition of a Thai Vehicle Based on MSER and BPNN
    Hong, Tao
    Gopalakrishnam, Anilkumar Kothalil
    2015 7TH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SMART TECHNOLOGY (KST), 2015, : 48 - 53
  • [22] Vehicle trajectory extraction algorithm based on license plate recognition data
    Ruan S.-B.
    Wang F.-J.
    Ma D.-F.
    Jin S.
    Wang D.-H.
    Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 2018, 52 (05): : 836 - 844
  • [23] A Novel License Plate Character Segmentation Method for Different Types of Vehicle License Plates
    Sarker, Md. Mostafa Kamal
    Song, Moon Kyou
    2014 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE (ICTC), 2014, : 84 - 88
  • [24] Extraction of critical scenarios in a railway level crossing control system
    Medjoudj, Malika
    Yim, Pascal
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2007, 2 (03) : 252 - 268
  • [25] Level set method for license plate localization technology
    Yang, Yuwang
    Tao, Jun
    Yang, Jingyu
    CIS: 2007 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, PROCEEDINGS, 2007, : 347 - 350
  • [26] A rapid segmentation method of vehicle license plate based on knowledge
    Yuan, XH
    Li, JX
    Xia, LZ
    IMAGE EXTRACTION, SEGMENTATION, AND RECOGNITION, 2001, 4550 : 358 - 362
  • [27] Automatic US vehicle license plate extraction and license number splitting under various illumination conditions
    Li, CC
    Pyeatt, L
    International Conference on Computing, Communications and Control Technologies, Vol 2, Proceedings, 2004, : 143 - 148
  • [28] Research on identification technology of vehicle license plate based on image processing
    Shi Guiming
    Wu Tong
    Su Hang
    Wei Qingtao
    APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY, 2014, 513-517 : 2827 - 2830
  • [29] Dual license plate recognition and visual features encoding for vehicle identification
    Ramajo-Ballester, Alvaro
    Moreno, Jose Maria Armingol
    Hueso, Arturo de la Escalera
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2024, 172
  • [30] Application of Phase Correlation Algorithm in Vehicle License Plate Character Identification
    Lang Liying
    Zhang Xiaofang
    INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL 1, PROCEEDINGS, 2008, : 995 - 998