A Robust Diverged Localization and Recognition of License Registration Characters
Localization and Recognition of License registration characters from the moving vehicle is a computationally complex task in the field of machine vision and is of substantial interest because of its diverse applications such as cross border security, law enforcement and various other intelligent transportation applications. Previous research used the plate specific details such as aspect ratio, character style, color or dimensions of the plate in the complex task of plate localization. In this paper, license registration character is localized by Enhanced Weight based density map (EWBDM) method, which is independent of such constraints. In connection with our previous method, this paper proposes a method that relaxes constraints in lighting conditions, different fonts of character occurred in the plate and plates with hand-drawn characters in various aspect quotients. The robustness of this method is well suited for applications where the appearance of plates seems to be varied widely. Experimental results show that this approach is suited for recognizing license plates in different external environments.
<p>[1] Yali Amit,Donald Geman, and Xiaodong Fan, “A Coarse-to-fine
strategy for multiclass shape detection”, IEEE Transaction on Pattern
Analysis and Machine Intelligence, Vol.26, No. 12. pp. 1606-1621,
2004.
[2] Park, S.H. Kim, K.I. Jung, and Kim H. J., “Locating Car License Plate
using Neural Networks”, IEE Electronics letters 35, pp.1475-1477,1999.
[3] Hegt J A, Haye R J, De La Khan N A, “High performance license plate
recognition system”, IEEE Proceedings of international conference of
systems, MAN, cybernetics, San Diego, CA, 1998, pp. 4357-4362.
[4] Eun Ruyng Lee, Pyeoung Kee Kim, Hang Oon Kim, “Automatic
Recognition of a car license plate using color image processing”, IEEE
Proceedings of ICISIP, 1994, pp. 149-152.
[5] M. J. Ahmed, M . Sarfraz, A. Zidouri, W.G. Al Khatib, “License Plate
Recognition System”, IEEE Proceedings of ICECS, 2003, (07803-8163-
7/03), pp. 898-901.
[6] Dong-Su Kim, Sung-Il Chien, “Automatic License Plate Extraction
Using Modified Generalized Symmetry Transform and Image Warping”,
IEEE Proceedings of ISIE, 2001, (0-7803-7090-2/01), pp. 2022-2027.
[7] Guangzhi Cao, Jiaqian Chen, Jingping Jiang, “An Adaptive Approach
to Vehicle License Plate Localization”, IEEE Proc. of IECON, Roanoke,
Virginia, USA, 2003, pp. 1786-1791.
[8] Gyu-Dong Lee, Kwang-Sub Kim, Dong-Seok Jeong, “Rough Edge
Detection of Low Contrast Images Using Consequential Local Variance
Maxima, IEEE Proceedings of Tencon, 1999, (0-7803-5739-6/99), pp.
734-737
[9] Hans A. Hegt, Ron J. De la Haye, Nadeem A. Khan, “A High
Performance License Plate Recognition System”, IEEE Proceedings,
1998, (0-7803-4778-1/98), pp. 4357-4362
[10] Paolo Comelli, Paolo Ferragina, Mario Notturno Granieri and Flavio
Stabille, “Optical Recognition of Motor Vehicle License Plate”, IEEE
Transactions on Vehicular Technology, Vol. 44, No.4, November 1995,
(0018-9545/95), pp. 790-799.
[11] Giovanni Adorni, Stefano Cagnoni, Marco Gori and Monica Mardonini,
Access Control System with Neuro-Fuzzy supervision, IEEE
Proceedings of Intelligent Transportation Systems Conference, 2001, (0-
7803-7194-1/01). pp.472 - 477
[12] Shyang-lih Chang , Li-Shien Chen, Yun-Chung Chung, and Sei-Wan
Chen, “Automatic License plate Recognition”, IEEE Transaction on
Intelligent Transportation Systems, Vol. 5 No. 1, pp. 42-53, 2004.
[13] Mei Yu and Yong Deak Kim, “An Approach to Korean License Plate
Recognition based on Vertical Edge matching”, IEEE Proceedings,
2000, (0-7803-6583-6/00), pp. 2975-2980.
[14] Takashi Naito, Toshihiko Tsukada, Keiichi Yamada, Kazuhiro Kozuka,
and Shin Yamamoto, “Robust License-Plate Recognition Method for
Passing Vehicles Under Outside Environment”, IEEE Transaction on
Vehicular Technology, Vol.49, No.6, pp. 2309-2319, 2000.
[15] R.Bremananth, A Chitra, Vivek Seetharaman Vidya Sudhan L Nathan,
“A Robust Video based License plate recognition”, IEEE Proc. of Inter.
Conf. On intelligent sensing and information processing, (IEEE-0-7803-
8840-2/05), 2005, pp.175-180.
[16] Park, S.H. Kim, K.I., Jung, K., Kim, H. J., “Locating Car License Plate
using Neural Networks”, IEE Electronics letters, 35, pp. 1475-1477,
1999.
[17] R. Bremananth, Prof. A. Chitra, Vivek seetharaman, Vidyasudhan, “A
New Methodology for License Plate Recognition System”, IETE Journal
of Research, Vol.51, No.4, pp. 279-286, 2005.</p>
<p>[1] Yali Amit,Donald Geman, and Xiaodong Fan, “A Coarse-to-fine
strategy for multiclass shape detection”, IEEE Transaction on Pattern
Analysis and Machine Intelligence, Vol.26, No. 12. pp. 1606-1621,
2004.
[2] Park, S.H. Kim, K.I. Jung, and Kim H. J., “Locating Car License Plate
using Neural Networks”, IEE Electronics letters 35, pp.1475-1477,1999.
[3] Hegt J A, Haye R J, De La Khan N A, “High performance license plate
recognition system”, IEEE Proceedings of international conference of
systems, MAN, cybernetics, San Diego, CA, 1998, pp. 4357-4362.
[4] Eun Ruyng Lee, Pyeoung Kee Kim, Hang Oon Kim, “Automatic
Recognition of a car license plate using color image processing”, IEEE
Proceedings of ICISIP, 1994, pp. 149-152.
[5] M. J. Ahmed, M . Sarfraz, A. Zidouri, W.G. Al Khatib, “License Plate
Recognition System”, IEEE Proceedings of ICECS, 2003, (07803-8163-
7/03), pp. 898-901.
[6] Dong-Su Kim, Sung-Il Chien, “Automatic License Plate Extraction
Using Modified Generalized Symmetry Transform and Image Warping”,
IEEE Proceedings of ISIE, 2001, (0-7803-7090-2/01), pp. 2022-2027.
[7] Guangzhi Cao, Jiaqian Chen, Jingping Jiang, “An Adaptive Approach
to Vehicle License Plate Localization”, IEEE Proc. of IECON, Roanoke,
Virginia, USA, 2003, pp. 1786-1791.
[8] Gyu-Dong Lee, Kwang-Sub Kim, Dong-Seok Jeong, “Rough Edge
Detection of Low Contrast Images Using Consequential Local Variance
Maxima, IEEE Proceedings of Tencon, 1999, (0-7803-5739-6/99), pp.
734-737
[9] Hans A. Hegt, Ron J. De la Haye, Nadeem A. Khan, “A High
Performance License Plate Recognition System”, IEEE Proceedings,
1998, (0-7803-4778-1/98), pp. 4357-4362
[10] Paolo Comelli, Paolo Ferragina, Mario Notturno Granieri and Flavio
Stabille, “Optical Recognition of Motor Vehicle License Plate”, IEEE
Transactions on Vehicular Technology, Vol. 44, No.4, November 1995,
(0018-9545/95), pp. 790-799.
[11] Giovanni Adorni, Stefano Cagnoni, Marco Gori and Monica Mardonini,
Access Control System with Neuro-Fuzzy supervision, IEEE
Proceedings of Intelligent Transportation Systems Conference, 2001, (0-
7803-7194-1/01). pp.472 - 477
[12] Shyang-lih Chang , Li-Shien Chen, Yun-Chung Chung, and Sei-Wan
Chen, “Automatic License plate Recognition”, IEEE Transaction on
Intelligent Transportation Systems, Vol. 5 No. 1, pp. 42-53, 2004.
[13] Mei Yu and Yong Deak Kim, “An Approach to Korean License Plate
Recognition based on Vertical Edge matching”, IEEE Proceedings,
2000, (0-7803-6583-6/00), pp. 2975-2980.
[14] Takashi Naito, Toshihiko Tsukada, Keiichi Yamada, Kazuhiro Kozuka,
and Shin Yamamoto, “Robust License-Plate Recognition Method for
Passing Vehicles Under Outside Environment”, IEEE Transaction on
Vehicular Technology, Vol.49, No.6, pp. 2309-2319, 2000.
[15] R.Bremananth, A Chitra, Vivek Seetharaman Vidya Sudhan L Nathan,
“A Robust Video based License plate recognition”, IEEE Proc. of Inter.
Conf. On intelligent sensing and information processing, (IEEE-0-7803-
8840-2/05), 2005, pp.175-180.
[16] Park, S.H. Kim, K.I., Jung, K., Kim, H. J., “Locating Car License Plate
using Neural Networks”, IEE Electronics letters, 35, pp. 1475-1477,
1999.
[17] R. Bremananth, Prof. A. Chitra, Vivek seetharaman, Vidyasudhan, “A
New Methodology for License Plate Recognition System”, IETE Journal
of Research, Vol.51, No.4, pp. 279-286, 2005.</p>
@article{"International Journal of Electrical, Electronic and Communication Sciences:65159", author = "M. Sankari and R. Bremananth and C.Meena", title = "A Robust Diverged Localization and Recognition of License Registration Characters", abstract = "Localization and Recognition of License registration characters from the moving vehicle is a computationally complex task in the field of machine vision and is of substantial interest because of its diverse applications such as cross border security, law enforcement and various other intelligent transportation applications. Previous research used the plate specific details such as aspect ratio, character style, color or dimensions of the plate in the complex task of plate localization. In this paper, license registration character is localized by Enhanced Weight based density map (EWBDM) method, which is independent of such constraints. In connection with our previous method, this paper proposes a method that relaxes constraints in lighting conditions, different fonts of character occurred in the plate and plates with hand-drawn characters in various aspect quotients. The robustness of this method is well suited for applications where the appearance of plates seems to be varied widely. Experimental results show that this approach is suited for recognizing license plates in different external environments.
", keywords = "Character segmentation, Connectivity checking, Edge detection, Image analysis, license plate localization, license
number recognition, Quality frame selection", volume = "6", number = "10", pages = "1225-8", }
