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Proceedings Paper

Automatic vehicle license plate recognition with color component texture detection and template matching
Author(s): Jianjun Gao; Erik Blasch; Khanh Pham; Genshe Chen; Dan Shen; Zhonghai Wang
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Paper Abstract

Automatic vehicle license plate recognition (LPR) is important for intelligent traffic surveillance systems. This paper suggests a vehicle license plate algorithm, color component texture detection and template matching (CCTD-TM). CCTD-TM has advantages of ease of implementation and highly efficient in calculation. We suggest a novel algorithm of color component texture for license plate localization. This algorithm takes advantage of the feature of fixed color texture of plate base and character. The image preprocessing and character recognition by template matching parts are included in the LPR algorithm. The preliminary results demonstrate an average detection rate over 96.5% and an average recognition rate over 89.9% on hundreds of vehicle images tested in the experiments.

Paper Details

Date Published: 21 May 2013
PDF: 6 pages
Proc. SPIE 8739, Sensors and Systems for Space Applications VI, 87390Z (21 May 2013); doi: 10.1117/12.2014595
Show Author Affiliations
Jianjun Gao, Intelligent Fusion Technology, Inc. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Genshe Chen, Intelligent Fusion Technology, Inc. (United States)
Dan Shen, Intelligent Fusion Technology, Inc. (United States)
Zhonghai Wang, Intelligent Fusion Technology, Inc. (United States)


Published in SPIE Proceedings Vol. 8739:
Sensors and Systems for Space Applications VI
Khanh D. Pham; Joseph L. Cox; Richard T. Howard; Genshe Chen, Editor(s)

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