A License Plate Recognition System Based on HSV Space in Natural Lighting

Abstract:

Article Preview

In recent years, with the development of modern traffic demand, the automobile license plate recognition technology has obtained more and more attentions. In this paper, the license plate in the vehicle image is located by extracting the color feature in HSV color space. And after binarizing the license plate image, the vertical scanning procedure is used to segment the license plate characters, and the template matching procedure are used to recognize the characters according to the similar degrees. Experimental results show that the system designed in this paper can effectively recognize the license plate in natural lighting, with the accuracy up to 95% for the Chinese characters, 90.4% for the numbers, 84.4% for the letters, and the time consumption being second level.

Info:

Periodical:

Edited by:

Liangzhong Jiang

Pages:

421-426

Citation:

Z. B. Zhang et al., "A License Plate Recognition System Based on HSV Space in Natural Lighting", Advanced Materials Research, Vol. 590, pp. 421-426, 2012

Online since:

November 2012

Export:

Price:

$41.00

[1] Nanning Zheng, Xining Zhang andYing Zai. Automatic recognition system of running vehicle license plate, J. Joural of Xi'an Jiaotong University. 25(1991) 45-53.

[2] Kaushik Deb, Kang-Hyun Jo. HIS Color based Vehicle License Plate Detection, International Conference on Control Automation and System. (2008) 687-691.

DOI: https://doi.org/10.1109/iccas.2008.4694589

[3] J. Guo, P.F. Shi. Color And Texture Analysis Based Vehicle License Plate Location, J. Image and Graphics, 7(2002) 472-476.

[4] B. Hongliang, L. Changping. A hybrid license plate extraction method based on edge statistics and morphology, 17th International Conference on Pattern Recognition. (2004) 831-834.

DOI: https://doi.org/10.1109/icpr.2004.1334387

[5] Rongbao Chen, Yunfei Luo. An Improved License Plate Location Method Based On Edge Detection, International Conference on Applied Physics and Industrial Engineering. (2012).

DOI: https://doi.org/10.1016/j.phpro.2012.02.201

[6] Baofeng Zhang, Liye Cao, Junchao Zhu. Research on the segmentation of license plate characters, ESEP. (2011) 9-10.

DOI: https://doi.org/10.1016/j.egypro.2011.12.508

[7] Jianbin Jiao, QixiangYe, Qingming Huang. A configurable method for multi-style license plate recognition, J. Pattern Recognition. 42 (2009) 358-369.

DOI: https://doi.org/10.1016/j.patcog.2008.08.016

[8] Nicolás Fernando Gazcón, Carlos Iván Chesnvar, Silvia Mabel Castro. Automatic vehicle identification for Argentinean license plates using intelligent template matching, Pattern Recognition Letters. 33 (2012) 1066-1074.

DOI: https://doi.org/10.1016/j.patrec.2012.02.004