Farsi License Plate Detection based on Element Analysis and Characters Recognition

In this paper, a safe and powerful method is presented which can detect and identify Farsi license plate irrespective of distance (how far a vehicle is), rotation (angle between camera and vehicle), and contrast (being dirty, reflected, or deformed). In addition, more than one car can be existed in an image. The proposed method extracts edges and then determines the candidate regions by using adaptive image enhancement and applying window movement. Finally by region elements analysis, the license plates are detected. The region elements analysis is working according to the plate geometric structure, continuity and parallelism. After detecting license plates, we estimate rotation angle and try to compensate it. In order to identify a detected plate, every character should be recognized. For this purpose, we present 53 features and use them as input to artificial neural network classifier.