Title :
Simplified Local Binary Pattern Descriptor for Character Recognition of Vehicle License Plate
Author :
Liu, Lixia ; Zhang, Honggang ; Feng, Aiping ; Wan, Xinxin ; Guo, Jun
Author_Institution :
Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
Local Binary Pattern (LBP) is a powerful texture descriptor for its tolerance against illumination changes and its computational simplicity. The basic LBP encodes 256 feature patterns in a 3×3 neighborhood, but not all the patterns are effective for classification. In this paper, we propose a simplified LBP(S-LBP) which produces optimal patterns by using the best coding principle for classification. Meanwhile, we combine S-LBP and Mahalonobis distance in solving the practical problem of character recognition in Chinese license plate. Experimental results demonstrate the effectiveness of our method for vehicle license recognition comparing with other popular methods.
Keywords :
character recognition; image classification; image coding; image texture; Chinese license plate; Mahalonobis distance; character recognition; coding principle; computational simplicity; local binary pattern descriptor; simplified-local binary pattern; texture descriptor; vehicle license plate; Character recognition; Feature extraction; Histograms; Licenses; Pixel; Vehicles; Entropy; S-LBP; character recognition; low-resolution;
Conference_Titel :
Computer Graphics, Imaging and Visualization (CGIV), 2010 Seventh International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-7840-8
DOI :
10.1109/CGIV.2010.32