Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJARAI.2012.010202
Article Published in International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 1 Issue 2, 2012.
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