Automatic Vehicle Identification by Plate Recognition
Automatic Vehicle Identification (AVI) has many
applications in traffic systems (highway electronic toll collection, red
light violation enforcement, border and customs checkpoints, etc.).
License Plate Recognition is an effective form of AVI systems. In
this study, a smart and simple algorithm is presented for vehicle-s
license plate recognition system. The proposed algorithm consists of
three major parts: Extraction of plate region, segmentation of
characters and recognition of plate characters. For extracting the
plate region, edge detection algorithms and smearing algorithms are
used. In segmentation part, smearing algorithms, filtering and some
morphological algorithms are used. And finally statistical based
template matching is used for recognition of plate characters. The
performance of the proposed algorithm has been tested on real
images. Based on the experimental results, we noted that our
algorithm shows superior performance in car license plate
recognition.
[1] D.G. Bailey, D. Irecki, B.K. Lim and L. Yang "Test bed for number
plate recognition applications", Proceedings of First IEEE International
Workshop on Electronic Design, Test and Applications ( DELTA-02 ),
IEEE Computer Society, 2002.
[2] R.A. Lotufo, A.D. Morgan, and AS. Johnson, 1990, "Automatic
Number-Plate Recognition," Proceedings of the IEE Colloquium on
Image analysis for Transport Applications, V01.035, pp.6/1-6/6,
February 16, 1990.
[3] A.S. Johnson, B.M. Bird, 1990, "Number-plateMatching for Automatic
Vehicle Identification," IEE Colloquium on Electronic Image and Image
Processing in Security and Forensic, Aprl, 1990.
[4] M.M.M. Fahmy, 1994, "Automatic Number-plate Recognition : Neural
Network Approach," Proceedings of VNIS-94 Vehicle Navigation and
Information System Conference, 3 1 Aug-2 Sept, 1994
[5] J.A.G. Nijhuis, M.H. Ter Brugge, K.A. Helmholt, J.P.W. Pluim, L.
Spaanenburg, R.S. Venema, M.A. Westenberg, 1995, "Car License Plate
Recognition with Neural Networks and Fuzzy Logic," IEEE
International Conference on Neural Networks,1995
[6] H.J. Choi, 1987, "A Study on the Extraction and Recognition of a Car
Number Plate by Image Processing," Journal of the Korea Institute of
Telematics and Electronics, Vo1.24, pp. 309-3 15,1987.
[7] H.S. Kim, et al., 1991, "Recognition of a Car Number Plate by a Neural
Network," Proceedings of the Korea Information Science Society Fall
Conference, Vol. 18, pp. 259-262, 1991
[8] E.R. Lee, P.K. Kim, and H.J. Kim, 1994, "Automatic Recognition of a
Car License Plate Using Color Image Processing," Proceedings of the
International Conference on Image Processing
[9] S.K. Kim, D.W. Kim, and H.J. Kim, 1996, "A Recognition of Vehicle
License Plate Using a Genetic Algorithm Based Segmentation,"
Proceedings of 3rd IEEE International Conference on Image Processing,
V01.2., pp. 661-664, 1996
[10] Tavsanoglu V, Saatci E. "Feature extraction for character recognition
using Gabor-type filters implemented by cellular neural networks,"
Proceedings of the 2000 6th IEEE International Workshop on Cellular
Neural Networks and their Applications, IEEE. 2000, pp.63-8.
Piscataway,NJ,USA.
[11] Yoshimura H, Etoh M, Kondo K, Yokoya N."Gray-scale character
recognition by Gabor jets projection," Proceedings 15th International
Conference on Pattern Recognition, ICPR-2000. IEEE Comput. Soc.
Part vol.2, 2000, pp.335-8 vol.2, Los Alamitos, CA,USA.
[12] Hontani, H., and Koga, T., (2001), "Character extraction method without
prior knowledge on size and information," Proceedings of the IEEE
International Vehicle Electronics Conference (IVEC-01), pp. 67-72.
[13] Park, S. H., Kim, K. I., Jung, K., and Kim, H. J., (1999), "Locating car
license plates using neural network," IEE Electronics Letters, vol.35, no.
17, pp. 1475-1477.
[14] H.J.Kim, D.W.Kim, S.K. Kim, J.V. Lee, J.K. Lee, 1997, "Automatic
Recognition of Car License Plates Using Color Image Processing,"
Engineering Design & Automation, 3(2), pp.215-225,1997
[15] M.Horowitz, "Efficient use of a picture correlator" J. Opt. Soc. Am,
vol.47, pp.327, 1957.
[1] D.G. Bailey, D. Irecki, B.K. Lim and L. Yang "Test bed for number
plate recognition applications", Proceedings of First IEEE International
Workshop on Electronic Design, Test and Applications ( DELTA-02 ),
IEEE Computer Society, 2002.
[2] R.A. Lotufo, A.D. Morgan, and AS. Johnson, 1990, "Automatic
Number-Plate Recognition," Proceedings of the IEE Colloquium on
Image analysis for Transport Applications, V01.035, pp.6/1-6/6,
February 16, 1990.
[3] A.S. Johnson, B.M. Bird, 1990, "Number-plateMatching for Automatic
Vehicle Identification," IEE Colloquium on Electronic Image and Image
Processing in Security and Forensic, Aprl, 1990.
[4] M.M.M. Fahmy, 1994, "Automatic Number-plate Recognition : Neural
Network Approach," Proceedings of VNIS-94 Vehicle Navigation and
Information System Conference, 3 1 Aug-2 Sept, 1994
[5] J.A.G. Nijhuis, M.H. Ter Brugge, K.A. Helmholt, J.P.W. Pluim, L.
Spaanenburg, R.S. Venema, M.A. Westenberg, 1995, "Car License Plate
Recognition with Neural Networks and Fuzzy Logic," IEEE
International Conference on Neural Networks,1995
[6] H.J. Choi, 1987, "A Study on the Extraction and Recognition of a Car
Number Plate by Image Processing," Journal of the Korea Institute of
Telematics and Electronics, Vo1.24, pp. 309-3 15,1987.
[7] H.S. Kim, et al., 1991, "Recognition of a Car Number Plate by a Neural
Network," Proceedings of the Korea Information Science Society Fall
Conference, Vol. 18, pp. 259-262, 1991
[8] E.R. Lee, P.K. Kim, and H.J. Kim, 1994, "Automatic Recognition of a
Car License Plate Using Color Image Processing," Proceedings of the
International Conference on Image Processing
[9] S.K. Kim, D.W. Kim, and H.J. Kim, 1996, "A Recognition of Vehicle
License Plate Using a Genetic Algorithm Based Segmentation,"
Proceedings of 3rd IEEE International Conference on Image Processing,
V01.2., pp. 661-664, 1996
[10] Tavsanoglu V, Saatci E. "Feature extraction for character recognition
using Gabor-type filters implemented by cellular neural networks,"
Proceedings of the 2000 6th IEEE International Workshop on Cellular
Neural Networks and their Applications, IEEE. 2000, pp.63-8.
Piscataway,NJ,USA.
[11] Yoshimura H, Etoh M, Kondo K, Yokoya N."Gray-scale character
recognition by Gabor jets projection," Proceedings 15th International
Conference on Pattern Recognition, ICPR-2000. IEEE Comput. Soc.
Part vol.2, 2000, pp.335-8 vol.2, Los Alamitos, CA,USA.
[12] Hontani, H., and Koga, T., (2001), "Character extraction method without
prior knowledge on size and information," Proceedings of the IEEE
International Vehicle Electronics Conference (IVEC-01), pp. 67-72.
[13] Park, S. H., Kim, K. I., Jung, K., and Kim, H. J., (1999), "Locating car
license plates using neural network," IEE Electronics Letters, vol.35, no.
17, pp. 1475-1477.
[14] H.J.Kim, D.W.Kim, S.K. Kim, J.V. Lee, J.K. Lee, 1997, "Automatic
Recognition of Car License Plates Using Color Image Processing,"
Engineering Design & Automation, 3(2), pp.215-225,1997
[15] M.Horowitz, "Efficient use of a picture correlator" J. Opt. Soc. Am,
vol.47, pp.327, 1957.
@article{"International Journal of Electrical, Electronic and Communication Sciences:53395", author = "Serkan Ozbay and Ergun Ercelebi", title = "Automatic Vehicle Identification by Plate Recognition", abstract = "Automatic Vehicle Identification (AVI) has many
applications in traffic systems (highway electronic toll collection, red
light violation enforcement, border and customs checkpoints, etc.).
License Plate Recognition is an effective form of AVI systems. In
this study, a smart and simple algorithm is presented for vehicle-s
license plate recognition system. The proposed algorithm consists of
three major parts: Extraction of plate region, segmentation of
characters and recognition of plate characters. For extracting the
plate region, edge detection algorithms and smearing algorithms are
used. In segmentation part, smearing algorithms, filtering and some
morphological algorithms are used. And finally statistical based
template matching is used for recognition of plate characters. The
performance of the proposed algorithm has been tested on real
images. Based on the experimental results, we noted that our
algorithm shows superior performance in car license plate
recognition.", keywords = "Character recognizer, license plate recognition, plate
region extraction, segmentation, smearing, template matching.", volume = "1", number = "9", pages = "1283-4", }
