A super-resolution method for recognition of license plate character using LBP and RBF

Author

Chen, Xiaoxuan ; Qi, Chun

Author_Institution

Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., Xi´´an, China

fYear

2011

fDate

18-21 Sept. 2011

Firstpage

1

Lastpage

5

Abstract

Character recognition is the key of three steps in license plate recognition. Although many methods have been proposed to deal with this problem, there is less work dealing with exploration of effective feature to represent license plate characters and recognize characters in low-resolution (LR) images. In this paper, we propose a method that uses the feature based on local binary pattern (LBP) to describe characters and uses radial basis function (RBF) to establish the relationship between features of HR and LR images. The experimental results show that the LBP feature is effective and our method has a good recognition performance.

Keywords

feature extraction; image resolution; optical character recognition; radial basis function networks; traffic engineering computing; HR images; LBP; RBF; feature exploration; license plate character recognition; local binary pattern; low-resolution images; radial basis function; super-resolution method; Character recognition; Feature extraction; Histograms; Image recognition; Image resolution; Licenses; Training; Character recognition; local binary pattern (LBP); radial basis function (RBF); super-resolution;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on

Conference_Location

Santander

ISSN

1551-2541

Print_ISBN

978-1-4577-1621-8

Electronic_ISBN

1551-2541

Type

conf

DOI

10.1109/MLSP.2011.6064550

Filename

6064550