Title :
Single image super resolution for license plate
Author :
Xue, Yanbing ; Deng, Wenhui ; Zhou, Dongsheng ; Zhang, Hua
Abstract :
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.
Keywords :
Bayes methods; Markov processes; character recognition; image resolution; Bayesian belief propagation; MRF model; Markov random field; compatibility function; image patch pair; license plate preprocessing; low resolution image; observation function; single image super resolution; Image reconstruction; Image resolution; Licenses; Markov random fields; Signal processing algorithms; Signal resolution; Training; Belief propagation; Llicense Plate; MRF; Super resolution; component;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5583108
