Volume 6 Number 2 (Feb. 2011)
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JCP 2011 Vol.6(2): 246-253 ISSN: 1796-203X
doi: 10.4304/jcp.6.2.246-253

Vehicle License Plate Recognition Based on Text-line Construction and Multilevel RBF Neural Network

Baoming Shan
College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao, 266042, China

Abstract—License plate localization and character segmentation and recognition are the research hotspots of vehicle license plate recognition (VLPR) technology. A new method to VLPR is presented in this paper. In license plate localization section, Otsu binarization is operated to get the plate-candidates regions, and a text-line is constructed from the candidate regions. According to the text-line construction result and the characteristics of the license plate character arrangement, the license plate location will be determined. And then the locally optimal adaptive binarization is utilized to make more accurate license plate localization. After the license plate localization, the segment method of vertical projection information with prior knowledge is used to slit characters and the statistical features are extracted. Then the multilevel classification RBF neural network is used to recognize characters using the feature vector as input. The results show that this method can recognize characters precisely and improve the ability of license plate character recognition effectively.

Index Terms—License plate localization, License plate character recognition, Text-line construction, Multilevel classification RBF neural network

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Cite: Baoming Shan, "Vehicle License Plate Recognition Based on Text-line Construction and Multilevel RBF Neural Network," Journal of Computers vol. 6, no. 2, pp. 246-253, 2011.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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