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A Survey on Detecting License Plates from Low Quality Images

by S. Neeraja, S. Rathi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 27
Year of Publication: 2018
Authors: S. Neeraja, S. Rathi
10.5120/ijca2018916643

S. Neeraja, S. Rathi . A Survey on Detecting License Plates from Low Quality Images. International Journal of Computer Applications. 180, 27 ( Mar 2018), 9-15. DOI=10.5120/ijca2018916643

@article{ 10.5120/ijca2018916643,
author = { S. Neeraja, S. Rathi },
title = { A Survey on Detecting License Plates from Low Quality Images },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2018 },
volume = { 180 },
number = { 27 },
month = { Mar },
year = { 2018 },
issn = { 0975-8887 },
pages = { 9-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number27/29143-2018916643/ },
doi = { 10.5120/ijca2018916643 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:01:55.601966+05:30
%A S. Neeraja
%A S. Rathi
%T A Survey on Detecting License Plates from Low Quality Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 27
%P 9-15
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In real-time, identifying license plates from low quality images affected by multiple factors, such as severe brightness condition, tough background, distinct weather conditions, darkness, and appearance distortions is a difficult process. This paper gives a comparative analysis of different license plate detection (LPD) techniques in terms of their detection ratios. Super-resolution and enhancement techniques are discussed to overcome the problems faced by license plate recognition systems such as detecting license plates from blurred images. It is realized that image enhancement techniques are superior to image super-resolution techniques for improving low quality images.

References
  1. Yule Yuan, Member, IEEE, Wenbin Zou, Young Zhao, Xinan Wang, Xuefeng Hu, and Nikos Komodakis, “ A Robust and Efficient Approach to License Plate Detection”, IEEE Transactions on image processing, Vol. 26, No. 3, pp. 1057-7149, March 2017.
  2. D. Zheng, Y. Zhao, and J. Wang, “ An efficient method of license plate location.” , Pattern Recognition Letter, Vol. 26, pp. 2431-2438, June 2005.
  3. Yong Zhao, Yule Yuan, Member, IEEE, Subin Bai, Kai Liu, Wei Fang, “ Voting-based License Plate Location.”, International IEEE Conference on Intelligent Transportation Systems Washington, DC, USA, Oct 2011.
  4. Wengang Zhou, Houqiang Li, Yijuan Lu, Member, IEEE, and Qi Tian, Senior Member, IEEE, “Principal Visual Word Discovery for Automatic License Plate Detection.”, IEEE Transactions on image processing, Vol. 21, No. 9, pp. 1057-7149, September 2012.
  5. Bo Li, Bin Tian, Ye Li, and Ding Wen, Senior Member, IEEE, “Component-Based-Based License Plate Detection Using Conditional Random Field Model.”, IEEE Transactions on Intelligent Transportation Systems, Vol. 14, No. 4, pp. 1524-9050, Dec 2013.
  6. Runmin Wang, Nong Sang, Rui Huang, Yuehuan Wang, “License plate detection using gradient information and cascade detectors”, Optik, Vol. 125, No. 1, pp. 186-190, 2014.
  7. Shan Du, Member, IEEE, Mahmoud Ibrahim, Mohamed Shehata, Senior Member, IEEE and Wael Badawy, Senior Member, IEEE, “Automatic License Plate Recognition(ANPR): A State-of-the-Art Review”, IEEE Transactions on Circuits and systems for Video Technology, Vol. 23, No. 2, pp. 1051-8215, Feb 2013.
  8. Kai Zhang, Baoquan Wang, Wangmeng Zuo, Senior Member IEEE, Hongzhi Zhang, Member IEEE, Lei Zhang, Senior Member IEEE, “Joint Learning of Multiple Regressors for Single Image Super-Resolution.”, IEEE Transactions on Signal Processing Letters, Vol. 23, No. 1, pp. 1070-9908, Jan2016.
  9. Chao Dong, Chen Change Loy, Member, IEEE, Kaiming He, Member, IEEE, and Xiaoou Tang, Fellow, IEEE, “Image Super-Resolution Using Deep Convolutional Networks.”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 38, No. 2, pp. 0162-8828, Feb 2016.
  10. Alexandre Nata Vicente, Helio Pedrini, “A Learning-Based Single-Image Super-Resolution Method for Very Low Quality License Plate Images.”, IEEE International Conference on Systems, Oct 2016.
  11. K.S. Raghunandan, Palaiahnakote Shivakumara, Member IEEE, Hamid A. Jalab, Member IEEE, Rabha W. Ibrahim, Member IEEE, G. Hemantha Kumar, Umapada Pal, Senior Member IEEE and Tong Lu, Member IEEE, “Riesz Fractional Based Model for Enhancing License Plate Detection and Recognition”, IEEE Personal use is permitted, pp. 1051-8215, 2016.
  12. Paheding Sidike, Evan Krieger, M. Zahangir Alom, Vijayan K. Asari and Tarek Taha, “A fast single-image super resolution via directional edge guided regularized extreme learning regression”, Springer, Received: 15 March 2016/Revised: 7 September 2016/Accepted: 15 December 2016/ Published online: 11 Jan 2017.
  13. R. C. Gonzalez and R. E. Woods, Digital Image Processing, Second Edition, Pearson Education, 2002.
Index Terms

Computer Science
Information Sciences

Keywords

LPD low resolution super-resolution image enhancement

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