Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

Rong Choi Lee; King Chu Hung; Huan Sheng Wang

doi:10.4028/www.scientific.net/AMM.284-287.2402

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 284-287Real-Time Vehicle License Plate Recognition Based...

Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

Abstract:

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.

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Periodical:

Applied Mechanics and Materials (Volumes 284-287)

Pages:

2402-2406

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.284-287.2402

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Online since:

January 2013

Authors:

Rong Choi Lee, King Chu Hung, Huan Sheng Wang

Keywords:

Artificial Neural Network (ANN), Haar Discrete Wavelet Transform, Real Time

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References

[1] H. Sheng, C. Li, Q. Wen, and Z. Xiong: IEEE Intelligent Transportation Systems Magazine (2009).

Google Scholar

[2] A.W.G.C.D. Wijetunge and D.A.A.C. Ratnaweera: 2011 6th International Conference on Industrial and Information Systems, ICIIS 2011, pp.82-87, Aug. 16-19, Sri Lanka (2011).

DOI: 10.1109/iciinfs.2011.6038045

Google Scholar

[3] M.K. Wu, L.S. Wei, H.C. Shih, and C.C. Ho#: Embedded SoC Lab, Department of Electrical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan, ROC, IEEE International Symposium on Industrial Electronics (ISlE 2009), Seoul Olympic Parktel, Seoul, Korea, July 5-8 (2009).

DOI: 10.18057/ijasc.2014.10.3.1

Google Scholar

[4] Y. Song: Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, IEEE IRI 2010, Las Vegas, Nevada, USA, August 4-6, pp.403-404, IEEE (2010).

Google Scholar

[5] P. M P, M.S.A. l Majid, S. Yaacob, M.H.F. Rahiman and R.P. Krishnan: School of Mechatronics Engineering, University Malaysia Perlis, Perlis, Malaysia, International Colloquium on Signal Processing & Its Applications (CSPA) IEEE, pp.33-35, May, (2009).

DOI: 10.15676/ijeei.2012.4.2.9

Google Scholar

[6] N. Chen and L. Xing: College of computer science Xi'an Polytechnic University Xi'an, China, International Conference on Computer Application and System Modeling (2010).

Google Scholar