Efficient Farsi license plate recognition

This paper presents a practical Farsi license plate recognition system that can process images at high accuracy rates for real-time applications. This system is designed to exhibit the requirements of performance, computational speed, for vehicle surveillance applications, such as stolen car detection systems and traffic monitoring. These requirements are satisfied by adopting a hierarchy serial framework. The proposed system is composed of five main cascading parts for motion detection, plate location, character segmentation, character recognition, and postprocessing. In each part many candidates are selected and some of them are rejected from desired candidates list and other forward to next step. This strategy saves computational load and increase implementation velocity. Experimental results show that the proposed system can provide over 94% accuracy with a resolution of 576*768 pixels on a 3 GHz Intel Pentium 4 and 1 GB RAM personal computer.