Comparison of different wavelets for automatic identification of vehicle license plate

被引:8
|
作者
Laxmi, V. [1 ]
Mohanta, D. K. [1 ]
Karan, B. M. [1 ]
机构
[1] Birla Inst Technol, Dept Elect & Elect Engn, Ranchi, Bihar, India
关键词
CLASSIFICATION;
D O I
10.1049/iet-its.2010.0149
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With increasing number of vehicles in developing countries, the traditional practice of manual monitoring of vehicles is becoming cumbersome, ineffective and economically unviable. This study uses an image-processing-based frequency-domain approach using wavelet multiresolution analysis (MRA) to overcome the difficulties associated with the conventional approach of employing manual observation for vehicle identification. The classification algorithm uses features extracted from an image of vehicle license plate (VLP). Wavelet MRA technique is used to extract the features of image exploiting its abrupt change of intensities. As the features of an image are wavelet dependent, a number of wavelets have been used to extract features of the same image of a VLP. The wavelet that results in features for distinct classification is selected for this application. The case studies pertaining to vehicles in India validate the efficacy of the proposed methodology.
引用
收藏
页码:231 / 240
页数:10
相关论文
共 50 条
  • [21] 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
  • [22] Automatic license plate recognition
    Chang, SL
    Chen, LS
    Chung, YC
    Chen, SW
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2004, 5 (01) : 42 - 53
  • [23] Automatic thresholding of license plate
    Aboura, Khalid
    INTERNATIONAL JOURNAL OF AUTOMATION AND CONTROL, 2008, 2 (2-3) : 213 - 231
  • [24] License Plate Verification Method For Automatic License Plate Recognition Systems
    Amirgaliyev, B. Y.
    Kuatov, K. K.
    Baibatyr, Z. Y.
    Kenshimov, C. A.
    Kairanbay, M. Z.
    Jantassov, A. K.
    2015 TWELVE INTERNATIONAL CONFERENCE ON ELECTRONICS COMPUTER AND COMPUTATION (ICECCO), 2015, : 153 - 155
  • [25] A hybrid neuro-fuzzy approach for automatic vehicle license plate recognition
    Lee, HC
    Jong, CS
    APPLICATIONS AND SCIENCE OF COMPUTATIONAL INTELLIGENCE, 1998, 3390 : 159 - 168
  • [26] FPGA based Hardware Implementation of Automatic Vehicle License Plate Detection System
    Chhabra, Surbhi
    Jain, Himanshu
    Saini, Sandeep
    2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2016, : 1181 - 1187
  • [27] Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model
    Vaiyapuri, Thavavel
    Mohanty, Sachi Nandan
    Sivaram, M.
    Pustokhina, Irina V.
    Pustokhin, Denis A.
    Shankar, K.
    CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 67 (02): : 1881 - 1897
  • [28] Automatic Vehicle License Plate Recognition System Used in Expressway Toll Collection
    Huang Wenjie
    PROCEEDINGS OF 2010 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (ICCSIT 2010), VOL 6, 2010, : 159 - 162
  • [29] 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
  • [30] 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