Farsi License Plate Detection and Recognition Based on Characters Features

In this paper a license plate detection and recognition system for iranian private cars is implemented. the proposed license plate localization algorithm is based on region elements analysis which works properly independent 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 may exist in the image. the proposed method extracts edges and then determines the candidate regions by applying window movement. the region elements analysis includes binarization, character analysis, character continuity analysis and character parallelism analysis. after detecting license plates, we estimate the rotation angle and try to compensate it. in order to identify a detected plate, every character should be recognized. for this purpose, we present 25 features and use them as the input to an artificial neural network classifier. the experimental results show that our proposed method achieves appropriate performance for both detection and recognition of the iranian license plates.