Applied method of license plate binarization based on histogram analysis

The binarization of license plate image is one of the key techniques of car license plate recognition (CLPR) system and its results influence the accuracy of the segmentation of characters and their identification directly. In this paper, by analyzing the limitations of Otsu's method and Bernsen's method, a practical method of license plate binarization based on histogram analysis is proposed. In this method, the feature that the percentage of the character area is always less than that of background is presented to distinguish the style of plate. Then a global thresholding method, Doyle's method, is used to threshold the plate image. By counting over 8,000 pieces of plate images, the accuracy is nearly 99%. Only those pictures which are badly polluted or with very low resolution cannot be binarized correctly. The experimental and field-tested results show that our method has higher accuracy, higher speed and better binarization effect. The method has been applied in our CLPR system successfully.