Title :
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
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;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
Conference_Location :
Santander
Print_ISBN :
978-1-4577-1621-8
Electronic_ISBN :
1551-2541
DOI :
10.1109/MLSP.2011.6064550