More Web Proxy on the site http://driver.im/

research-article

Automatic license plate detection in hazardous condition

Authors:

Md Monirul IslamAuthors Info & Claims

Journal of Visual Communication and Image Representation, Volume 36, Issue C

Pages 172 - 186

https://doi.org/10.1016/j.jvcir.2016.01.015

Published: 01 April 2016 Publication History

Abstract

License plate detection in hazardous condition.Five novel contributions.Compared with few existing approaches.Experimented using two image databases. Automatic detection of license plate (LP) is to localize a license plate region from an image without human involvement. So far a number of methods have been introduced for automatic license plate detection (ALPD), but most of them do not consider various hazardous image conditions that exist in many real driving situations. Hazardous image condition means an image can have rainy or foggy weather effects, low contrast environments, objects similar to LP in the background, and horizontally tilted LP area. All these issues create challenges in developing effective ALPD method. In this paper, we propose a new ALPD method which effectively detects LP area from an image in the hazardous conditions. For rain removal we apply a novel method that uses frequency domain mask to filter rain streaks from an image. A new contrast enhancement method with a statistical binarization approach is introduced in the proposed ALPD for handling low contrast indoor, night, blurry and foggy images. For correcting tilted LP, we apply Radon transform based tilt correction method for the first time. To filter non-LP regions, a new condition is used which is based on image entropy. We test the proposed ALPD method on 850 car images having different hazardous conditions, and achieve satisfactory results in LP detection.

References

[1]

Automatic Number Plate Recognition. <http://en.wikipedia.org/wiki/Automatic_number_plate_recognition> (accessed 20-May-2014).

[2]

C. Anagnostopoulos, I. Anagnostopoulos, I. Psoroulas, V. Loumos, E. Kayafas, License plate recognition from still images and video sequences: a survey, IEEE Trans. Intell. Transp. Syst., 9 (2008) 377-391.

[3]

S. Du, M. Ibrahim, M. Shehata, W. Badawy, Automatic license plate recognition (alpr): a state-of-the-art review, IEEE Trans. Circ. Syst. Video Technol., 23 (2013) 311-325.

Digital Library

[4]

Autovu Automatic Number Plate Recognition. <http://www.genetec.com/solutions/all-products/autovu> (accessed 20-August-2015).

[5]

Arh Automatic Number Plate Recognition. <http://www.anpr.net/anpr_09/anpr_introduction.html> (accessed 26-August-2015).

[6]

Vigilant Solutions. <http://vigilantsolutions.com/> (accessed 24-August-2015).

[7]

Inexzamir Precise License Plate and Vehicle Identification at Any Speed and Lighting. <http://www.inexzamir.com/> (accessed 20-August-2015).

[8]

3m Motor Vehicle Systems and Services. <http://www.3m.com/3M/en_US/transportation-us> (accessed 26-August-2015).

[9]

S. Kim, D. Kim, Y. Ryu, G. Kim, A robust license-plate extraction method under complex image conditions, in: 16th International Conference on Pattern Recognition, vol. 3, 2002, pp. 216-219.

[10]

C. Anagnostopoulos, I. Anagnostopoulos, V. Loumos, E. Kayafas, A license plate recognition algorithm for intelligent transportation system applications, IEEE Trans. Intell. Transp. Syst., 7 (2006) 377-392.

Digital Library

[11]

H. Zhang, W. Jia, X. He, Q. Wu, A fast algorithm for license plate detection in various conditions, in: IEEE International Conference on Systems, Man and Cybernetics, vol. 3, 2006, pp. 2420-2425.

[12]

K. Deb, H. Chae, K.H. Jo, Vehicle license plate detection method based on sliding concentric windows and histogram, J. Comput., 4 (2009) 771-777.

[13]

Y. Huang, C. Chen, Y. Chang, F. Sandnes, An intelligent strategy for checking the annual inspection status of motorcycles based on license plate recognition, Expert Syst. Appl., 36 (2009) 9260-9267.

Digital Library

[14]

Y. Wang, W. Lin, S. Horng, A sliding window technique for efficient license plate localization based on discrete wavelet transform, Expert Syst. Appl., 38 (2011) 3142-3146.

Digital Library

[15]

Y. Wen, Y. Lu, J. Yan, Z. Zhou, K. Deneen, P. Shi, An algorithm for license plate recognition applied to intelligent transportation system, IEEE Trans. Intell. Transp. Syst., 12 (2011) 830-845.

Digital Library

[16]

A. Ghosh, S. Sharma, M. Islam, S. Biswas, S. Akter, Automatic license plate recognition (alpr) for bangladeshi vehicles, Global J. Comput. Sci. Technol., 11 (2011) 69-73.

[17]

R. Gonzalez, R. Woods, Digital Image Processing, Prentice Hall, Pearson, 2008.

[18]

M. Joarder, K. Mahmud, T. Ahmed, M. Kawser, B. Ahamed, Bangla automatic number plate recognition system using artificial neural network, Asian Trans. Sci. Technol., 2 (2012) 1-10.

[19]

I. Benou, R. Yochanan, A license plate detection and character segmentation method under difficult conditions, in: IEEE 27th Convention of Electrical Electronics Engineers in Israel (IEEEI), 2012, pp. 1-5.

[20]

M. Hasan, Real Time Detection and Recognition of License Plate in Bengali, Bourns College of Engineering, UC Riverside, 2013.

[21]

G. Hsu, J. Chen, Y. Chung, Application-oriented license plate recognition, IEEE Trans. Veh. Technol., 62 (2013) 552-561.

[22]

G. Abo Smara, F. Khalefah, Localization of license plate number using dynamic image processing techniques and genetic algorithms, IEEE Trans. Evol. Comput., 18 (2014) 244-257.

Digital Library

[23]

W. Kusakunniran, K. Ngamaschariyakul, C. Chantaraviwat, K. Janvittayanuchit, K. Thongkanchorn, A thai license plate localization using svm, in: International Computer Science and Engineering Conference (ICSEC), 2014, pp. 163-167.

[24]

A. Davis, C. Arunvinodh, N. Arathy Menon, Automatic license plate detection using vertical edge detection method, in: International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015, pp. 1-6.

[25]

H. Karwal, A. Girdhar, Vehicle number plate detection system for indian vehicles, in: IEEE International Conference on Computational Intelligence Communication Technology (CICT), 2015, pp. 8-12.

[26]

N. More, B. Tidke, License plate identification using artificial neural network and wavelet transformed feature selection, in: International Conference on Pervasive Computing (ICPC), 2015, pp. 1-5.

[27]

K. Ahmad Yousef, M. Al-Tabanjah, E. Hudaib, M. Ikrai, Sift based automatic number plate recognition, in: 6th International Conference on and Communication Systems (ICICS), 2015, pp. 124-129.

[28]

S. Baharlou, S. Hemayat, A. Saberkari, S. Yaghoobi, Fast and adaptive license plate recognition algorithm for persian plates, in: 2nd International Conference on Pattern Recognition and Image Analysis (IPRIA), 2015, pp. 1-6.

[29]

J. Dun, S. Zhang, X. Ye, Y. Zhang, Chinese license plate localization in multi-lane with complex background based on concomitant colors, IEEE Intell. Transp. Syst. Mag., 7 (2015) 51-61.

[30]

S. Dewan, S. Bajaj, S. Prakash, Using ant's colony algorithm for improved segmentation for number plate recognition, in: IEEE/ACIS 14th International Conference on Computer and Information Science (ICIS), 2015, pp. 313-318.

[31]

Grayscale. <http://en.wikipedia.org/wiki/Grayscale> (accessed 22-May-2014).

[32]

R. Gonzalez, R. Woods, S.L. Eddins, Digital Image Processing using Matlab, Gatesmark Publisher, 2009.

[33]

J.S. Lim, Two-Dimensional Signal and Image Processing, Prentice Hall, Englewood Cliffs, NJ, 1990.

[34]

H. Tamura, S. Mori, T. Yamawaki, Textural features corresponding to visual perception, IEEE Trans. Syst., Man Cybernet., 8 (1978) 460-473.

[35]

K. Zuiderveld, Contrast limited adaptive histogram equalization, in: Graphic Gems IV, Academic Press Professional, Inc, San Diego, CA, USA, 1994.

[36]

M. Goyal, Morphological image processing, Int. J. Comput. Sci. Technol., 2 (2011) 161-165.

[37]

L. Shapiro, G. Stockman, Computer Vision, Prentice Hall, Upper Saddle River, NJ, USA, 2002.

[38]

J. Bernsen, Dynamic thresholding of gray-level images, in: Proceedings of 8th International Conference on Pattern Recognition, Paris, France, 1986, pp. 1251-1255.

[39]

K. Jafari-Khouzani, H. Soltanian-Zadeh, Radon transform orientation estimation for rotation invariant texture analysis, IEEE Trans. Pattern Anal. Mach. Intell., 27 (2005) 1004-1008.

Digital Library

[40]

A.K. Jain, Fundamentals of Digital Image Processing, Pearson, Singapore, 2003.

[41]

ALPD Image Database. <https://sites.google.com/site/samicsemist/about-the-teacher/mscthesisdetails> (accessed 12-July-2014).

[42]

English LP Database. <http://www.zemris.fer.hr/projects/LicensePlates/english/baza_slika.zip> (accessed 12-July-2014).

[43]

J. Bossu, N. Hautière, J. Tarel, Rain or snow detection in image sequences through use of a histogram of orientation of streaks, Int. J. Comput. Vision, 93 (2011) 348-367.

Digital Library

[44]

L.W. Kang, C.W. Lin, Y.H. Fu, Automatic single-image-based rain streaks removal via image decomposition, IEEE Trans. Image Process., 21 (2012) 1742-1755.

Digital Library

Cited By

Salma Saeed Mur Rahim RGufran Khan MZulfiqar ABhatti M(2021)Development of ANPR Framework for Pakistani Vehicle Number Plates Using Object Detection and OCRComplexity10.1155/2021/55973372021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/5597337
Ahn HCho H(2021)Research of automatic recognition of car license plates based on deep learning for convergence traffic control systemPersonal and Ubiquitous Computing10.1007/s00779-020-01514-z27:3(1139-1148)Online publication date: 27-Feb-2021
https://dl.acm.org/doi/10.1007/s00779-020-01514-z
Chan LZimmer ASilva JBrandmeier T(2020)European Union Dataset and Annotation Tool for Real Time Automatic License Plate Detection and Blurring2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC45102.2020.9294240(1-6)Online publication date: 20-Sep-2020
https://dl.acm.org/doi/10.1109/ITSC45102.2020.9294240
Show More Cited By

Automatic license plate detection in hazardous condition
1. Computing methodologies
  1. Artificial intelligence
  2. Computer graphics

Recommendations

Automatic license plate recognition

Automatic license plate recognition (LPR) plays an important role in numerous applications and a number of techniques have been proposed. However, most of them worked under restricted conditions, such as fixed illumination, limited vehicle speed, ...
Automatic License Plate Recognition (ALPR): A State-of-the-Art Review

Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications, such as electronic payment ...
An Autonomous License Plate Detection Method
IIH-MSP '09: Proceedings of the 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing

Detection of license plate is an important process in intelligent transportation systems before license plate recognition. In this paper, we proposed an autonomous license plate detection system with computer vision instead of sensors. Using ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Visual Communication and Image Representation

Journal of Visual Communication and Image Representation Volume 36, Issue C

April 2016

243 pages

ISSN:1047-3203

Issue’s Table of Contents

Copyright © Elsevier Inc.

Publisher

Academic Press, Inc.

United States

Publication History

Published: 01 April 2016

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 24 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Salma Saeed Mur Rahim RGufran Khan MZulfiqar ABhatti M(2021)Development of ANPR Framework for Pakistani Vehicle Number Plates Using Object Detection and OCRComplexity10.1155/2021/55973372021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/5597337
Ahn HCho H(2021)Research of automatic recognition of car license plates based on deep learning for convergence traffic control systemPersonal and Ubiquitous Computing10.1007/s00779-020-01514-z27:3(1139-1148)Online publication date: 27-Feb-2021
https://dl.acm.org/doi/10.1007/s00779-020-01514-z
Chan LZimmer ASilva JBrandmeier T(2020)European Union Dataset and Annotation Tool for Real Time Automatic License Plate Detection and Blurring2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC45102.2020.9294240(1-6)Online publication date: 20-Sep-2020
https://dl.acm.org/doi/10.1109/ITSC45102.2020.9294240
Rio-Alvarez Ade Andres-Suarez JGonzalez-Rodriguez MFernandez-Lanvin DLópez Pérez BSolanki V(2019)Effects of Challenging Weather and Illumination on Learning-Based License Plate Detection in Noncontrolled EnvironmentsScientific Programming10.1155/2019/68973452019Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1155/2019/6897345
Naim AAaroud ASaadani S(2018)Automatic approach for the extraction of indexes of electric meters and waterProceedings of the 7th International Conference on Software Engineering and New Technologies10.1145/3330089.3330105(1-5)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1145/3330089.3330105
Rizwan Asif MChun QBibi ISadiq Fareed MZhe ZZhaoqiang Z(2018)Performance Evaluation Of Local Image Features For Multinational Vehicle License Plate Verification2018 IEEE Intelligent Vehicles Symposium (IV)10.1109/IVS.2018.8500534(2170-2175)Online publication date: 26-Jun-2018
https://dl.acm.org/doi/10.1109/IVS.2018.8500534
Al-Shemarry MLi YAbdulla S(2018)Ensemble of adaboost cascades of 3L-LBPs classifiers for license plates detection with low quality imagesExpert Systems with Applications: An International Journal10.1016/j.eswa.2017.09.03692:C(216-235)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1016/j.eswa.2017.09.036
Xu ZYang WMeng ALu NHuang HYing CHuang L(2018)Towards End-to-End License Plate Detection and Recognition: A Large Dataset and BaselineComputer Vision – ECCV 201810.1007/978-3-030-01261-8_16(261-277)Online publication date: 8-Sep-2018
https://dl.acm.org/doi/10.1007/978-3-030-01261-8_16
Azam SGavrilova MMao XThalmann DGavrilova M(2017)License plate image patch filtering using HOG descriptor and bio-inspired optimizationProceedings of the Computer Graphics International Conference10.1145/3095140.3095141(1-6)Online publication date: 27-Jun-2017
https://dl.acm.org/doi/10.1145/3095140.3095141
Saini MSaini S(2017)Multiwavelet transform based license plate detectionJournal of Visual Communication and Image Representation10.1016/j.jvcir.2017.01.00344:C(128-138)Online publication date: 1-Apr-2017
https://dl.acm.org/doi/10.1016/j.jvcir.2017.01.003

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents