Title :
Automatic character recognition for moving and stationary vehicles and containers in real-life images
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol.
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
Keywords :
image recognition; neural nets; optical character recognition; VECON; Vehicle and Container Number Recognition; automatic character recognition; border checkpoints; bus stations; car parks; container depots; container terminals; containers; image distortion; moving vehicles; real-life images; stationary vehicles; uneven lighting; Character recognition; Computer science; Containers; Fading; Image segmentation; Layout; Lighting; Paints; Robustness; Vehicle detection;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.833530