Character Segmentation Method for a License Plate with Topological Transform
This paper propose the robust character segmentation method for license plate with topological transform such as twist,rotation. The first step of the proposed method is to find a candidate region for character and license plate. The character or license plate
must be appeared as closed loop in the edge image. In the case of
detecting candidate for character region, the evaluation of detected
region is using topological relationship between each character. When
this method decides license plate candidate region, character features
in the region with binarization are used. After binarization for the detected candidate region, each character region is decided again. In
this step, each character region is fitted more than previous step. In the
next step, the method checks other character regions with different
scale near the detected character regions, because most license plates
have license numbers with some meaningful characters around them.
The method uses perspective projection for geometrical normalization.
If there is topological distortion in the character region, the method
projects the region on a template which is defined as standard license
plate using perspective projection. In this step, the method is able to
separate each number region and small meaningful characters. The
evaluation results are tested with a number of test images.
[1] H. Bai, J. Zhu, C. Liu, "A fast license plate extraction method on complex
background," Intelligent Transportation Systems, Proceedings. 2003
IEEE, vol. 2, pp. 985-987.
[2] D. Zheng, Y. Zhao, and J. Wang, "An efficient method of license plate
location," Pattern Recognit. Lett., vol. 26, no. 15, pp.2431-2438, Nov.
2005.
[3] Jung-Wei Hsieh, Shin-Hao Yu, and Yung-Sheng Chen,
"Morphology-based license plate detection in images of differently illuminated and oriented cars," Journal of Electronic Imaging, Vol.11,
No. 4, pp. 507-516, 2002.
[4] X. Shi, W. Zhao, and Y. Shen, Automatic License Plate Recognition
System Based on Color Image Processing, vol. 3483, O. Gervasi et al., Ed.
New York: Springer-Verlag, 2005, pp. 1159-1168.
[5] G. Cao, J. Chen, and J. Jiang, "An adaptive approach to vehicle license
plate localization", in Proc. 29th Annu. Conf. IECON, 2003, pp.
1786-1791.
[6] Feng Wang, Lichun Man, Bangping Wang, Yijun Xiao, Wei Pan,
Xiaochun Lu, "Fuzzy-based algorithm for color recognition of license
plates," Pattern Recognition Letters, Vol. 29 , No. 7, pp. 1007-1020,
May. 2008.
[7] Wu Guo-ping, Cheng Shi, Ao Min-si, Lei Hui, "Slant Correction of
Vehicle License Plate Based on Feature Point and Principal Component
Analysis," International Conference on Computer Science and Software
Engineering, vol. 6, pp.487-490, 2008.
[8] Hsien-Chu WU, Chwei-Shyong TSAI, and Ching-Hao LAI, "A license
plate recognition system in E-Government," An International Journal
Information & Security, Vol. 15, No. 2, 2004, pp. 199-210.
[1] H. Bai, J. Zhu, C. Liu, "A fast license plate extraction method on complex
background," Intelligent Transportation Systems, Proceedings. 2003
IEEE, vol. 2, pp. 985-987.
[2] D. Zheng, Y. Zhao, and J. Wang, "An efficient method of license plate
location," Pattern Recognit. Lett., vol. 26, no. 15, pp.2431-2438, Nov.
2005.
[3] Jung-Wei Hsieh, Shin-Hao Yu, and Yung-Sheng Chen,
"Morphology-based license plate detection in images of differently illuminated and oriented cars," Journal of Electronic Imaging, Vol.11,
No. 4, pp. 507-516, 2002.
[4] X. Shi, W. Zhao, and Y. Shen, Automatic License Plate Recognition
System Based on Color Image Processing, vol. 3483, O. Gervasi et al., Ed.
New York: Springer-Verlag, 2005, pp. 1159-1168.
[5] G. Cao, J. Chen, and J. Jiang, "An adaptive approach to vehicle license
plate localization", in Proc. 29th Annu. Conf. IECON, 2003, pp.
1786-1791.
[6] Feng Wang, Lichun Man, Bangping Wang, Yijun Xiao, Wei Pan,
Xiaochun Lu, "Fuzzy-based algorithm for color recognition of license
plates," Pattern Recognition Letters, Vol. 29 , No. 7, pp. 1007-1020,
May. 2008.
[7] Wu Guo-ping, Cheng Shi, Ao Min-si, Lei Hui, "Slant Correction of
Vehicle License Plate Based on Feature Point and Principal Component
Analysis," International Conference on Computer Science and Software
Engineering, vol. 6, pp.487-490, 2008.
[8] Hsien-Chu WU, Chwei-Shyong TSAI, and Ching-Hao LAI, "A license
plate recognition system in E-Government," An International Journal
Information & Security, Vol. 15, No. 2, 2004, pp. 199-210.
@article{"International Journal of Information, Control and Computer Sciences:50865", author = "Jaedo Kim and Youngjoon Han and Hernsoo Hahn", title = "Character Segmentation Method for a License Plate with Topological Transform", abstract = "This paper propose the robust character segmentation method for license plate with topological transform such as twist,rotation. The first step of the proposed method is to find a candidate region for character and license plate. The character or license plate
must be appeared as closed loop in the edge image. In the case of
detecting candidate for character region, the evaluation of detected
region is using topological relationship between each character. When
this method decides license plate candidate region, character features
in the region with binarization are used. After binarization for the detected candidate region, each character region is decided again. In
this step, each character region is fitted more than previous step. In the
next step, the method checks other character regions with different
scale near the detected character regions, because most license plates
have license numbers with some meaningful characters around them.
The method uses perspective projection for geometrical normalization.
If there is topological distortion in the character region, the method
projects the region on a template which is defined as standard license
plate using perspective projection. In this step, the method is able to
separate each number region and small meaningful characters. The
evaluation results are tested with a number of test images.", keywords = "License Plate Detection, Character Segmentation, Perspective Projection, Topological Transform.", volume = "3", number = "8", pages = "1918-4", }