A New Machine Learning Approach to Deblurring License Plate Using K-Means Clustering Method

Abstract: Vehicle license plate recognition (LPR) is one of the important fields in Intelligent Transportation Systems (ITS). LPR systems aim to locate, segment and recognize the license plate from captured car image. Despite the great progress of LPR system in the last decade, there are still many problems to solve to reach a robust LPR system adapted to different environment and condition. The current license plate recognition systems will not effectively work well for blurred plate image. In this paper, to overcome the blurring problem a new machine learning approach to Deblurring License Plate using the K-Means clustering method have proposed. Experimental results demonstrate the effectiveness of the K-Means clustering as a feature selection method for license plate images.

Sanaz Aliyan and Ali Broumandnia. “A New Machine Learning Approach to Deblurring License Plate Using K-Means Clustering Method”. International Journal of Advanced Research in Artificial Intelligence (IJARAI) 1.2 (2012). http://dx.doi.org/10.14569/IJARAI.2012.010202

@article{Aliyan2012,
title = {A New Machine Learning Approach to Deblurring License Plate Using K-Means Clustering Method},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2012.010202},
url = {http://dx.doi.org/10.14569/IJARAI.2012.010202},
year = {2012},
publisher = {The Science and Information Organization},
volume = {1},
number = {2},
author = {Sanaz Aliyan and Ali Broumandnia}
}