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Single image super resolution for license plate

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4 Author(s)
Yanbing Xue ; Key Lab. of Comput. Vision & Syst., Tianjin Univ. of Technol., Tianjin, China ; Wenhui Deng ; Dongsheng Zhou ; Hua Zhang

A single image super resolution algorithm for license plate preprocessing is proposed in this paper. The image to be enhanced is modeled as a Markov Random Field and is estimated from the input low resolution image by image patch pairs. From the input image and the training set, observation function and compatibility function can be calculated. Then Bayesian Belief Propagation is used to select the most probable high resolution patches candidate in the MRF model. The experiment shows that using this method can get better license plate with more information for further recognition.

Published in:
Natural Computation (ICNC), 2010 Sixth International Conference on  (Volume:2 )

Date of Conference: 10-12 Aug. 2010

Page(s):
586 - 588
Print ISBN:
978-1-4244-5958-2
INSPEC Accession Number:
11554878
Conference Location :
Yantai, Shandong
Digital Object Identifier :
10.1109/ICNC.2010.5583108
Product Type:
Conference Publications

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