Character extraction of license plates from video

Author

Cui, Yuntao ; Huang, Qian

Author_Institution

Siemens Corp. Res. Inc., Princeton, NJ, USA

fYear

1997

fDate

17-19 Jun 1997

Firstpage

502

Lastpage

507

Abstract

In this paper, we present a new approach to extract characters on a license plate of a moving vehicle given a sequence of perspective distortion corrected license plate images. We model the extraction of characters as a Markov random field (MRF). With the MRF modeling, the extraction of characters is formulated as the problem of maximizing the a posteriori probability based on given prior and observations. A genetic algorithm with local greedy mutation operator is employed to optimize the objective function. Experiments and comparison study were conducted. It is shown that our approach provides better performance than other single frame methods

Keywords

Markov processes; character recognition; computer vision; feature extraction; genetic algorithms; probability; road traffic; traffic control; traffic engineering computing; Markov random field; a posteriori probability; character extraction; genetic algorithm; license plates from video; local greedy mutation operator; moving vehicle; perspective distortion corrected license plate images; Computer vision; Data mining; Educational institutions; Genetic algorithms; Genetic mutations; Image resolution; Licenses; Markov random fields; Pixel; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on

Conference_Location

San Juan

ISSN

1063-6919

Print_ISBN

0-8186-7822-4

Type

conf

DOI

10.1109/CVPR.1997.609372

Filename

609372