Authors: Safaa S. Omran,Jumana A. Jarallah
Computer Engineering Techniques, College of Electrical and Electronic Techniques
DOI: http://dx.doi.org/10.24086/cuesj.si.2017.n1a2
Abstract
License plate recognition (LPR) system is an important system in our life. LPR is an image processing and a character recognition system that used to recognize any car from the others. An automatic license plate recognition system for Iraqi car license plates is proposed in this paper. An optical character recognition (OCR) is used with correlation approach and templates matching for plate recognition in this system. The software used is MATLAB R2014a. The algorithm is successfully constructed with sample of images correctly identified.
Keywords: license plate recognition, optical character recognition, image processing, correlation, Otsu’s thresholding, tophat filtering.
References
[1] N. Najeel Kamal and L. E. George, “License Plate Numerics and Characters
Recognition,” International Journal of Advanced Research in Computer Science
and Software Engineering, vol. 4, no. 4, pp. 824-835, April 2014.
[2] R. Bhat and B. Mehandia, “Recognition of Vehicle Number Plate Using Matlab,”
International Journal of Innovative Research in Electrical, Electronics,
Instrumentation and Control Engineering, vol. 2, no. 8, pp.1899-1903, August
2014.
[3] S. D. Mohammed, “Iraqi License Plate Recognition System,” Journal of
International Academic Research for Multidisciplinary, vol. 1, no. 11, pp. 386-
400, december 2013.
[4] N. Simin and F. Choong Chiao Mei, “Automatic Car-plate Detection and
Recognition System,” EURECA, pp. 113-114, 2013.
[5] M.Gunasekaran and S.Ganeshmoorthy, “OCR Recognition System Using Feed
Forward and Back Propagation Neural Network,” Second National Conference on
Signal Processing, Communications and VLSI Design – NCSCV’10, pp. 345-350,
January 2010.
[6] C. Zhang, W. Zou, G. Yu and G. Sun, “A New Recognition Method of Vehicle
License Plate Based on Genetic Neural Network,” 5th IEEE Conference on
Industrial Electronics and Applicationsis, pp. 1662-1666, 2010.
[7] D. González Balderrama, H. de Jesús Ochoa Domínguez, V. Guadalupe Cruz
Sánchez and O. Osiris Vergara Villegas, “License Plate Recognition Using a
Novel Fuzzy Multilayer Neural Network,” International Journal of Computers,
vol. 3, no. 1, pp. 32-40, 2009.
[8] A. Gupta, D. Yadav, R. Bodade, R. Bilas Pachori and P. Kanani, “Vehicle License
Plate Localization Using Wavelets,” IEEE Conference on Information and
Communication Technologies, April 2013.
[9] J. Kumawat, H. G. Bhavsar and R. Chahar, “Automatic License Plate
Recoganization System Based on Based on Image Processing Using LabVIEW,”
International Journal of Advanced Research in Computer Science and Software
Engineering, vol. 4, no. 4, pp. 999-1002, April 2014.
[10] E. I. Abbas and T. A. Hashim, “Iraqi Cars License Plate Detection and Recognition
System using Edge Detection and Template Matching Correlation,” Eng.
&Tech.Journal, vol. 34, pp. 257-271, 2016.
[11] S. L. Eddins, R. E. Woods and R. C. Gonzalez, Digital Image Processing Using
Matlab, Second Edition ed. United States of America: Gatesmark Publishing,
LLC, 2009.
[12] V. Ganapathy and W. Lik Dennis Lui, “A Malaysian Vehicle License Plate
Localization and Recognition System,” Systemics, Cybernetics and Informatics,
vol. 6, pp. 13-20, January 2008.
[13] V.Harish, M.Swathi, CH. Deepthi and P. K Charles, “A Review on the Various
Techniques used for Optical Character Recognition,” International Journal of
Engineering, vol. 2, no. 1, pp. 659-662, January- February 2012.
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