Automatic character recognition for moving and stationary vehicles and containers in real-life images

Abstract

Many methods have been proposed for character recognition but they are often subjected to substantial constraints, due to unexpected difficulties encountered in real-life images. A real-life image may be complex for a variety of reasons. Rust, mud, peeling paint, or fading color may distort the images of the characters; uneven lighting may make them difficult to discern. This paper presents the VECON (Vehicle and Container Number Recognition) system, which takes into account a wide range of real-life considerations and aims at offering applicable solutions to some industries. After being tested under outdoor environment and 24-hour operations, the proposed methods proved to have accuracy higher than 95%. The system was commercially employed in car parks, bus stations, border checkpoints, container terminals and container depots.