Title :
Map-Based Single-Frame Super-Resolution Image Reconstruction for License Plate Recognition
Author :
Li, Zhan ; Han, Guoqiang ; Xiao, Su ; Chen, Xiangji
Author_Institution :
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
In a car license plate recognition system, effective and robust image expansion methods will improve its performance and bring a lower error rate. Two MAP-based super-resolution image reconstruction approaches for single image with a prior image model described as Huber Markov random field are discussed and applied to such a system in this paper. A new spatial smoothness measurement based on a flexible convolution kernel is proposed. Parameters in these approaches are discussed. Improved definition of images and increased recognition rate is also shown through computer simulations.
Keywords :
Markov processes; image resolution; object recognition; traffic engineering computing; Huber Markov random field; MAP-based single frame super resolution image reconstruction; car license plate recognition system; intelligent transportation systems; maximum a posteriori probability; robust image expansion methods; Convolution; Error analysis; Image recognition; Image reconstruction; Image resolution; Kernel; Licenses; Markov random fields; Robustness; Spatial resolution;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5366989