Recognition of Car License Plate by Using Dynamical Thresholding Method and Enhanced Neural Networks

In this paper, for the implementation of the recognition system of car license plates, the region extraction algorithm based on the contour tracking and the new enhanced neural networks learning algorithm are proposed, which extracts the areas of car license plate and the character areas from the car images and recognizes the car license numbers from the extracted areas. And a candidate area was selected, whose density rate was corresponding to the properties of the car license plate obtained in the condition of the car license plate. The contour tracking algorithm extracted the feature areas covering the areas of characters from the car license plate. As well, the enhanced neural networks learning algorithm, combining the modified ART1 and supervised learning algorithm, recognized the car license numbers from the feature areas.