The Utilization of Template Matching Method for License Plate Recognition


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Abstract


License plate detection and recognition system has been an active research domain in image processing field. However, these systems are less accurate due to different styles of car plates endorsed and yet there are still unable to reach the high accuracy in recognition. Thus, the aim of this research is to develop an automated method of determining the best recognition performance based on Malaysia license plate vehicle registration number. Towards achieving this aim, a database of characters and license plate image has been created by collecting images from various type of car. The initial pre-processing involves image enhancement, binarization and followed by filtering and segmenting license plate. Template matching method is used to recognize the characters, from A-Y and 0-9, using standard Malaysia license plate font which is Arial. There are 100 license plates that contain 693 characters have been tested, and the result shown that 92.78% of all characters is correctly recognized. Thus, template matching can be classified as one of the best algorithm for recognizing Malaysia license plate
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Keywords


Malaysia License Plate; Image Processing; Character Recognition; Template Matching

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References


M. F. Zakaria and S. A. Suandi, “Malaysian Car Number Plate Detection System Based on Template Matching and Colour Information,” Int. J. Comput. Sci. Eng., vol. 02, no. 04, pp. 1159–1164, 2010.

N. K. Ibrahim, E. Kasmuri, and A. Norazira, “License Plate Recognition ( LPR ): A Review with Experiments for Malaysia Case Study,” Int. J. Soft Comput. Softw. Eng., vol. 3, no. 3, 2013.

S. R. Tare, “Review Paper On CarPooling Using Android Operating System-A Step Towards Green Environment,” Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 3, no. 4, pp. 54–57, 2013.

B. R. Dandu and A. Chopra, “Vehicular Number Plate Recognition Using Edge Detection and Characteristic Analyisis of National Number Plates,” Inernational J. Comput. Eng. Res., vol. 2, no. 3, pp. 795–799, 2012.

L. A. K. T. K. Teo and F. Wong, “Smearing Algorithm for Vehicle Parking Management System,” Proc. 2nd Semin. Eng. Inf. Technol., no. July, pp. 331–337, 2009.

B. Indira, M. Shalini, M. V. R. Murthy, and M. S. Shaik, “Classification and Recognition of Printed Hindi Characters Using Artificial Neural Networks,” Int. J. Image, Graph. Signal Process., vol. 4, no. 6, pp. 15–21, Jul. 2012.

A. Mousa, “Canny Edge-Detection Based Vehicle Plate Recognition,” Int. J. Signal Process. Image Process. Pattern Recognit., vol. 5, no. 3, pp. 1–8, 2012.

A. Sedighi and M. Vafadust, “A new and robust method for character segmentation and recognition in license plate images,” Expert Syst. Appl., vol. 38, pp. 13497–13504, Apr. 2011.

M. H. Dashtban, “A Novel Approach for Vehicle License Plate Localization and Recognition,” Int. J. Comput. Appl., vol. 26, no. 11, pp. 22–30, 2011.

L. Jin, H. Xian, J. Bie, Y. Sun, H. Hou, and Q. Niu, “License plate recognition algorithm for passenger cars in Chinese residential areas.,” Sensors (Basel)., vol. 12, no. 6, pp. 8355–70, Jan. 2012.

A. Mukherjee, “Enhancement of Image Resolution by Binarization,” Int. J. Comput. Appl., vol. 10, no. 10, pp. 15–19, 2010.

S. Sivanandan and Y. Saiyyad, “Automatic Vehicle Identification Using License Plate Recognition for Indian Vehicles,” Int. J. Comput. Appl., vol. 2012, pp. 23–28, 2012.

R. Goyal and A. Kaur, “A Review of Optimal Binarization Techniques on Documents with Damaged Background,” Int. J. Comput. Sci. Technol., vol. 4333, pp. 237–239, 2011.

G. Sun, X. Sun, and X. Han, “A New Method for Edge Detection Based on the Criterion of Separability,” J. Multimed., vol. 6, no. 1, pp. 66–73, Feb. 2011.

S. B. C. Gaur, “Comparison of Edge Detection Techniques for Segmenting Car License Plates,” Int. J. Comput. Appl. Electron. Inf. Commun. Eng., no. 5, pp. 8–12, 2011.

P. Li and J. Connan, “Numberplate detection using double segmentation,” Proc. 2010 Annu. Res. Conf. South African Inst. Comput. Sci. Inf. Technol. - SAICSIT ’10, pp. 386–389, 2010.

L. Zheng, X. He, B. Samali, and L. T. Yang, “An algorithm for accuracy enhancement of license plate recognition,” J. Comput. Syst. Sci., vol. 79, no. 2, pp. 245–255, Mar. 2013.

S. Akter, “Automatic License Plate Recognition (ALPR) for Bangladeshi Vehicles,” Glob. J. Comput. Sci. Technol., vol. 11, no. 21, 2011.

K. Prasad, D. C. Nigam, A. Lakhotiya, D. Umre, and B. I. T. Durg, “Character Recognition Using Matlab ’ s Neural Network Toolbox,” Int. J. u- e- Serv. Sci. Technol., vol. 6, no. 1, pp. 13–20, 2013.

T. F. S. Adebayo Daramola, E. Adetiba, A. U. Adoghe, J. A. Badejo, I. A. Samuel, “Automatic Vehicle Identification System Using License Plate,” Int. J. Eng. Sci. Technol., vol. 3, no. 2, pp. 1712–1719, 2011.

S. Kranthi, K. Pranathi, and A. Srisaila, “Automatic Number Plate Recognition,” Int. J. Adv. Technol., vol. 2, no. 3, pp. 408–422, 2011.

P. Reshma, “Noise Removal and Blob Identification Approach for Number Plate Recognition,” Int. J. Comput. Appl., vol. 47, no. 8, pp. 13–17, 2012.

Kamranian, Z., Monadjemi, S.A., Bakhsh, N.N., Statistical and template matching features for Persian handwritten postal code recognition, (2011) International Review on Computers and Software (IRECOS), 6 (2), pp. 185-190.

M. I. Khalil, “Car Plate Recognition Using the Template Matching Method,” Int. J. Comput. Theory Eng., vol. 2, no. 5, pp. 3–7, 2010.

N. K. Ibrahim, E. Kasmuri, and N. A. Jalil, “A Review on License Plate Recognition with Experiments for Malaysia Case Study,” Middle-East J. Sci. Res., vol. 14, no. 3, pp. 409–422, 2013.

D. Gilly and D. K. Raimond, “License Plate Recognition- A Template Matching Method,” Int. J. Eng. Res. Appl., vol. 3, no. 2, pp. 1240–1245, 2013.

M. Suvarna, “Diagnosis of Burn Images using Template Matching , k-Nearest Neighbor and Artificial Neural Network,” Int. J. Image Process., no. 7, pp. 191–202, 2013.

Sebdani, F.M., Pourghassem, H., Vehicle detection based on template matching in traffic surveillance system, (2012) International Review on Computers and Software (IRECOS), 7 (3), pp. 1114-1121.


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