Automatic Number Plate Recognition (ANPR) is a real time embedded system which identifies the characters directly from the image of the license plate. Since different standard are used in different country, automatic number plate recognition system is different for each country. In this paper, a number plate recognition system for vehicles in India is proposed. This paper introduces a vehicle number plate identification system, which extracts the characters features of a plate, from an image captured by a digital camera. The system uses broad steps like thresholding, image segmentation, thinning and pattern matching for extraction of characters. The pattern matching is done using graph based method. Graph matching techniques are introduced to compute the similarity of characters extracted from number plate with the information of characters store in the database.

APNR, Segmentation, Thinning, Scaling, Pattern Matching, COG, Complete Bipartite Graph, Adjacency Matrix

[1] Central Motor Vehicle Rules 1989, Rule-50(2)(d). Government of India - Department of Road Transport & Highways. 1989. p. 4. Retrieved 2009-03-15.
[2] Wawage, P., Oza, S.: Design Approach for Vehicle License Plate Automatic Detection and character Recognition System Using Classification Algorithm, International Journal of Emerging Technology and Advanced Engineering, Volume 2, Issue 10, October 2012.
[3] Khalifa, O., Khan, S., Islam, R., Suleiman, A.: Malaysian Vehicle License Plate Recognition, The International Arab Journal ofInformation Technology, Volume 4, No. 4, October 2007.
[4] Bharath, D.K., Chandrashekar, V.E.: Vehicle Number Segmentation and Recognition by Using Region Properties and Thresholding, International Journal of Science and Research (IJSR), ISSN (Online): 2319-7064 pp. 308-311.
[5] Roy, A., Ghoshal, D.P.: Number Plate Recognition for Use in Different Countries Using an Improved Segmentation, IEEE.
[6] Parking and Traffic Technologies Ltd, Smartreg ANPR, Available: http://www.parkingandtraffic.co.uk/ANPR/smartreganpr
[7] Nijhuis, J.A.G., Brugge, M.H., Helmolt, K.A.: Car License Plate recognition with network and fuzzy logic, in Proc. Of IEEE International Conference on Neural Networks., volume 5, pp 2232-2236, Dec 1995
[8] Chang, L., Chen, L., Chung, Y., Chen, S.: Automatic license plate recognition IEEE Transaction Intelligent Transportation System, 5:42-53,2004
[9] Otsu, N.: A threshold selection method from gray-level histograms, IEEE Trans. Sys., Man., pp.62–66.
[10] Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd Edition, Prentice Hall, 2009.
[11] Ghosh, B.R., Banerjee, S., Dey, S., Ganguli, S., Sarkar, S.: Off-Line Signature Verification System Using Weighted Complete Bipartite Graph, 2nd International Conference on Business and Information Management (ICBIM), ISBN : 478-1-4799-3264-1/14/$31.00 ©2014 IEEE pp.109-113.