License Plate Character Segmentation and Recognition Based on RBF Neural Network

Author

Shan, Baoming

Author_Institution

Coll. of Autom. & Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao, China

Volume

2

fYear

2010

fDate

6-7 March 2010

Firstpage

86

Lastpage

89

Abstract

Character segmentation and recognition is the research hotspot of vehicle license plate recognition technology. A new method is presented in this paper. Based on the vehicle license location, the segment method of vertical projection information with prior knowledge is used to slit characters, and extract the statistical features. Then the RBF neural network is used to recognize characters with 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.

Keywords

character recognition; image recognition; image segmentation; radial basis function networks; RBF neural network; license plate character recognition; license plate character segmentation; prior knowledge; vehicle license location; vehicle license plate recognition; vertical projection information; Character recognition; Data mining; Educational technology; Feature extraction; Image recognition; Image segmentation; Intelligent transportation systems; Licenses; Neural networks; Vehicles; License plate character recognition; RBF neural network; feature extraction; vertical projection;

fLanguage

English

Publisher

ieee

Conference_Titel

Education Technology and Computer Science (ETCS), 2010 Second International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-6388-6

Electronic_ISBN

978-1-4244-6389-3

Type

conf

DOI

10.1109/ETCS.2010.464

Filename

5459969