Detection optimization of license plate targets based on AdvancedEAST

被引:0
作者
Yin, Feifei [1 ]
Wang, Jingxuan [2 ]
Xiong, Wei [1 ]
Gao, Juanjuan [2 ]
Gong, Yu [2 ]
机构
[1] North China Elect Power Univ, Network & Informat Off, Baoding 071000, Hebei, Peoples R China
[2] North China Elect Power Univ, Dept Comp, Baoding, Hebei, Peoples R China
关键词
License plate detection; AdvancedEAST; transfer learning; target detection; object detection; LOCALIZATION;
D O I
10.3233/JCM-215046
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
As an important core in the intelligent traffic management system, the technology and application of license plate recognition have become research focus. Detecting the accurate location of a license plate from a vehicle image is considered to be the most crucial step of license plate recognition, which greatly affects the recognition rate and speed of the whole system. Nevertheless, due to the low accuracy of license plate detection in natural scenes, further investigations are still needed in this field in order to make the detection process very efficient. In this paper, We have studied and implemented a convolutional neural network license plate detection algorithm based on transfer learning. According to the invention, new energy license plates and ordinary license plates are adopted as the research objects. The text detection model AdvancedEAST is trained on the license plate images through the transfer learning method, and experiments are carried out on the self-built license plate dataset. The experimental results show that the algorithm can better adapt to light complexity, low resolution, target interference, license plate tilt and other complex conditions. The license plate positioning algorithm has high accuracy in natural scenes, and it is superior to the traditional license plate detection methods.
引用
收藏
页码:1521 / 1529
页数:9
相关论文
共 32 条
  • [1] [Anonymous], 2012, J. Transp. Tech.
  • [2] [Anonymous], 2013, ADV COMPUT SCI INT J
  • [3] An Iranian License Plate Recognition System Based on Color Features
    Ashtari, Amir Hossein
    Nordin, Md. Jan
    Fathy, Mahmood
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2014, 15 (04) : 1690 - 1705
  • [4] Focusing Attention: Towards Accurate Text Recognition in Natural Images
    Cheng, Zhanzhan
    Bai, Fan
    Xu, Yunlu
    Zheng, Gang
    Pu, Shiliang
    Zhou, Shuigeng
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2017, : 5086 - 5094
  • [5] Dai JF, 2016, ADV NEUR IN, V29
  • [6] Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
    Du, Shan
    Ibrahim, Mahmoud
    Shehata, Mohamed
    Badawy, Wael
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2013, 23 (02) : 322 - 336
  • [7] Chinese License Plate Localization in Multi-Lane with Complex Background Based on Concomitant Colors
    Dun, Jingyu
    Zhang, Sanyuan
    Ye, Xiuzi
    Zhang, Yin
    [J]. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2015, 7 (03) : 51 - 61
  • [8] A Convnet for Non-maximum Suppression
    Hosang, Jan
    Benenson, Rodrigo
    Schiele, Bernt
    [J]. PATTERN RECOGNITION, GCPR 2016, 2016, 9796 : 192 - 204
  • [9] Hossen M.K., 2014, SMART COMPUT REV, V4, P371
  • [10] Huang ZK, 2018, 2018 INTERNATIONAL CONFERENCE ON CONTROL AND ROBOTS (ICCR), P84, DOI 10.1109/ICCR.2018.8534484