DocumentCode :
3746527
Title :
Image super-resolution via sparse coding for Chinese license plate recognition
Author :
Ni Hao;Liu Fanghua;Ruan Ruolin
Author_Institution :
School of Electronic and Information Engineering, Hubei University of Science and Technology, Xianning, China
fYear :
2015
Firstpage :
944
Lastpage :
948
Abstract :
Some plate recognition systems can not recognize the low-resolution license plate images correctly because the resolution of the input plate image is very low. The proposed method in this paper enhances the resolution of the Chinese license plate image via sparse coding. It employs dictionary learning to get the optimal overcomplete dictionary pairs and introduces the regularization terms to recover the high-resolution plate image. Experiments show that the plate image recovered by the proposed method can be well recognized. That is, the proposed single image super-resolution method in this paper can promote the plate recognition effectively.
Keywords :
"Dictionaries","Image reconstruction","Feature extraction","Training","Image edge detection","Image resolution"
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2015 8th International Congress on
Type :
conf
DOI :
10.1109/CISP.2015.7408014
Filename :
7408014
Link To Document :
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