License Plate Occlusion Detection Based on Character Jump

  • Wenzhen Nie
  • Pengyu LiuEmail author
  • Kebin JiaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)


The license plate location is the basis of the license plate occlusion detection. On the basis of the positioning, the key is to accurately determine the license plate occlusion. This paper proposes a license plate occlusion detection algorithm based on character jumping. For the positioned occluded license plate area, it is determined whether the license plate is occluded according to the number of license plate character jumps. The number of jumps of a normal license plate is greater than or equal to 14 times. If the license plate is blocked, the number of jumps is less than 14 times. The experimental results show that the detection effect of the license plate occlusion based on this algorithm has a good judgment result.


License plate positioning Character jump License plate occlusion determination 



This paper is supported by the Project for the National Natural Science Foundation of China under Grants No. 61672064, the Beijing Natural Science Foundation under Grant No. 4172001, the China Postdoctoral Science Foundation under Grants No. 2016T90022, 2015M580029, the Science and Technology Project of Beijing Municipal Education Commission under Grants No. KZ201610005007, Beijing Municipal Education Committee Science Foundation under Grants No. KM201810005030, and Beijing Laboratory of Advanced Information Networks under Grants No. 040000546617002, Beijing Municipal Communications Commission Science and Technology Project under Grants No. 2017058.


  1. 1.
    Xiujuan, L.I., Hebiao, Y.A.N.G., Ying, W.E.I.: Partially occluded license plate location method based on multi-layer edge constraint and region merging. Softw. Guide 14(7), 196–199 (2015)Google Scholar
  2. 2.
    Nianfeng, S.: Intelligent detection of illegal vehicles involved in card-based images. Nanjing Normal University (2013)Google Scholar
  3. 3.
    Yu, W.: Research on license plate recognition algorithm based on PCA and grid features. Xidian University (2013)Google Scholar
  4. 4.
    Yongquan, C., Ying, C., Xuesan, C.: Vehicle detection and tracking algorithm based on adaboost classifier. Comput. Technol. Dev. 27(9), 165–168 (2017)Google Scholar
  5. 5.
    Yulin, D.: Research and implementation of license plate detection based on adaboost algorithm in OpenCV. J. Guangxi Teachers Univ. (Nat. Sci.) 28(1), 109–112 (2011)Google Scholar
  6. 6.
    Wenfeng, L., Hongying, Z.: License plate location method based on texture features. Microcomput. Appl. 3, 41–43 (2014)Google Scholar
  7. 7.
    Qian, X.: License plate location algorithm based on image preprocessing and texture features. Electron. Des. Eng. 22(16), 13–17 (2014)Google Scholar
  8. 8.
    Yang, J., Feihu, Q.I.: A license plate locating approach based on shape and texture characteristics. Comput. Eng. 32(2), 170–172 (2006)Google Scholar
  9. 9.
    Ning, L., Yanlei, X., Ning, L., et al.: License plate location method based on mathematical morphology and color features. J. Gr. 35(5), 774–779 (2014)Google Scholar
  10. 10.
    Lili, L., Xingwu, W.: Vehicle license plate location algorithm based on Sobel operator edge detection and mathematical morphology. MODERN Electron. Technol. v.38 445(14), 98–100 (2015)Google Scholar
  11. 11.
    Jing, F.: Vehicle detection and license plate location based on deep learning. Jiangxi University of Science and Technology (2017)Google Scholar
  12. 12.
    Haiyan, L., Furong, C.: A complex environment license plate location method based on deep learning text detection. Mod. Comput. Prof. Edit. 33, 10–14 (2017)Google Scholar
  13. 13.
    Fei, G., Kaicheng, M., Zhenggao, H., et al.: Research on license plate location method based on grayscale jump and character interval mode. J. Comput. Measure. Control 24(4), 219–221 (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Faculty of Information TechnologyBeijing University of TechnologyBeijingChina
  2. 2.Beijing Laboratory of Advanced Information NetworksBeijingChina
  3. 3.Beijing Key Laboratory of Computational Intelligence and Intelligent SystemBeijing University of TechnologyBeijingChina

Personalised recommendations