DocumentCode
2149029
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
fYear
2010
fDate
7-10 Aug. 2010
Firstpage
157
Lastpage
161
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Graphics, Imaging and Visualization (CGIV), 2010 Seventh International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-1-4244-7840-8
Type
conf
DOI
10.1109/CGIV.2010.32
Filename
5576211
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