Novel License Plate Detection Method for Complex Scenes

In this paper, a novel license plate detection method is proposed. There are three key steps in our method, i.e. image preprocessing, license plate detection and license plate confirmation. First, the noises are removed and the diversities of license plate forms are unified through image preprocessing. And then, the license plates are detected roughly by using the cascade AdaBoost classifier. Finally, the gradient images are binarized, and the connected component analysis will be adopted to remove some false plates. Meanwhile, the offline trained Support Vector Machine (SVM) classifier is adopted to confirm the license plate candidates in further. The promising results of the proposed method is verified by experiments on a challenging database.