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Robust Automated License Plate and Character Recognition
Abstract
A robust approach for extracting car license plate from
images with complex background and relatively poor quality is
presented in this paper .The paper represents the automatic plate localization component of Car License Plate Recognition system an character recognition. The approach concerns stages of preprocessing, edge detection, filtering, detection of the plate's position, slope evaluation, and character segmentation and recognition. Single frame gray-level images are used as the only source of information. In the experiments all types of license plate were used, camera obtained at different daytime and whether conditions. The results derived have shown that the approach is
robust to illumination, plate slope, scale, and is insensitive to plate‟s country peculiarities. The proposed paper provides character recognizer for the identification of the characters in the license plate. These results could be also usable for other applications in the inputoutput transport systems, where automatic recognition of registration plates, shields, signs, etc., is often necessary.
Keywords
References
M. Yu and Y. D. Kim, “An approach to Korean license plate recognition
based on vertical edge matching,” IEEE Int. conf. on SMC, vol. 4, pp.
-2980, 2000.
C. Busch, et al, “ Feature based recognition of traffic video streams for
online route tracing,” IEEE Conference on VTC, vol. 3, pp. 1790-1794,
R. Zunino, S. Rovetta, “Vector quantization for license-plate location
and image coding,” IEEE Transactions on Industrial Electronics, vol. 47
Issue: 1, pp. 159–167, 2000.
K.K. Kim, et al, “Learning-based approach for license plate
recognition,” IEEE Signal Processing Society Workshop on Neural
Networks for Signal Processing, vol. 2, pp. 614–623, 2000.
T. Naito, et al, “Robust license-plate recognition method for passing
vehicles under outside environment,” IEEE Transactions on Vehicular
Technology, vol. 49, no. 6, pp. 2309–2319, 2000.
D.-S. Kim and S. Chien, “Automatic car license plate ex-traction using
modified generalized symmetry transform and image warping,” IEEE
International Symposium on In-dustrial Electronics, vol. 3, pp. 2022–
, 2001.
Maged M. M. Fahmy, “Automatic number-plate recognition: neural
network approach,” Proceedings of Vehicle Navigation and Information
Systems Conference,pp. 99-101, September 1994.
D. Irecki & D. G. Bailey, “Vehicle registration plate localization and
recognition”, Proceedings of the Electronics New Zealand Conference,
ENZCon‟01, New Plymouth, New Zealand, September 2001.
D. G. Bailey, D. Irecki, B. K. Lim and L. Yang, “Test bed for number
plate recognition applications,” Proceeding of the IEEE International
Workshop on Electronic Design, Test and Applications, 2002.
B. H. Cho & S. H. Jung, “Non feature-based vehicle plate recognition
system using neural network”, Proceeding of ITC-CSCC 98
International Conference,Korea, Vol. 2, 1065-1068, July 1998.
J. Barroso, J. Bulas-Cruz & E. L. Dagless, “Real Time Number Plate
Reading”, 4th IFAC Workshop on Algorithms and Architectures for
Real-time Control,Portugal, April 1997.
[6] J. R. Parker & P. Federl, “An approach to licence plate recognition”,
Computer Science Technical reports,University of Calgary, Alberta
Canada, Vol. 59111, October 1996.
J.Barroso, A. Rafael, E. L. Dagless and J. Bulas-Cruz, “Number plate
reading using computer vision”, IEEE Intern. Symposium on Industrial
Electronics, ISIE97, 1997.
Shokri Gendy, Clifton L. Smith and Stefan Lachowicz, “Automatic car
registration plate recognition using fast Haugh Transform”, Proceedings
of the Institute of Electrical and Electronics Engineers, Carnahan, pp.
-218, October 1997.
R. van Heerden and C. Nieuwoudt, “Automatic number plate
segmentation and recognition”, Department of Electrical and Electronic
Engineering Reports, University of Pretoria, 1998.
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