Color-Clustering and Neural Network Based License Plate Type Identification

License plate recognition is the key of the intelligent transport monitoring system and the rate of license plate type identification is one of the important technical specifications in this recognition system. This paper proposed a new method based on clustering and neural network to identify the license plate type. The experimental results of more than 500 images acquired under different conditions show that the method is more accurate and robust to noises and illumination variations, and the rate of identification is above 99%.