Recognition of Characters and Numbers in Vietnam License Plates based on Image Processing and Neural Network

Artificial neural network (ANN) have wide applicability in various applications in the life, one of them is apply to recognize characters and numbers, and we know that the Automatic License Plate Recognition (ALPR) is very important in the Intelligent Transportation System (ITS) and it is beginning in research and application in Vietnam. Usually, an ALPR system consists of three parts: 1) license plate location, 2) character segmentation, 3) characters & numbers recognition. In this paper, we proposed an improved method for the characters & numbers recognition part. And then, we apply to recognize characters & numbers of Vietnam License Plates (LP), which combined neural network and image processing technologies. In the training work, we used two networks and back-propagation (BP) algorithm for characters & numbers training with noises, separately, which the computing time and accuracy will be improved. In the using network work, we used the image processing technology for preprocessing to obtain high quality of characters & numbers before put in the trained network to improve accuracy of the system. We tested on 600 Vietnam LP images, which obtained from the actual systems, these images are very different background such as illumination, license angles, size and type, colors, light conditions in Vietnam environment. Our approach is more effective than some of the existing methods and satisfied for all types and color of Vietnam license plates and Vietnam environment.