A complete system for vehicle plate localization, segmentation and recognition in real life scene.

Abstract

There are many applications of plate identification in pattern recognition and machine vision. These applications range from complex security systems to commons areas and from parking admission to urban traffic control. Car license plate recognition (CLPR) has complex characteristics due to diverse effects as fog, rain, shadows, irregular illumination conditions, partial occlusion, variable distances, cars' velocity, scene's angle on frame, plate rotation and conservation, number of vehicles in the scene and other. These factors make plate recognition much more complex and difficult than the traditional pattern or optical character recognition (OCR) systems. The main objective of this work is to show a system that solves the practical problem of car identification for real scenes. All steps of the process, from image scene acquisition to optical character recognition are considered to achieve an automatic identification of plates. It can be used with all type of country rules or plates design and adapted to each situation. The system is computationally very efficient and it is suitable for others related image recognition applications.