Map-Based Single-Frame Super-Resolution Image Reconstruction for License Plate Recognition

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-super resolution; image reconstruction; license plate recognition; maximum a posteriori probability

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