Recognition System for Libyan Vehicle License Plate

Abstract

Automatic license plate recognition system plays an essential role in real life applications, especially those related to security and traffic managements. It essentially extracts and recognizes number plate information from videos or captured images of the targeted vehicle. Vehicle license plates differ from one country to another and because of this the effectiveness of implementing any particular method or system varies based on the plate type. In this study, we present an automatic detection, segmentation and recognition system for Libyan vehicle license plates. The main challenge in this work is our determination to use images of real vehicle plates in Libya, and the majority of these plates are not in a good condition because of poor vehicle maintenance. Three different approaches were used in the proposed system as follows:(1) Projection histogram based approach is used to locate the authorized plate license; (2) Connected component analysis based approach is used to segment the plate characters; (3) The template matching based approach is used to recognise the extracted characters. The proposed system was tested on 200 vehicle images varying in illumination conditions and backgrounds. The detection accuracy of the implemented system was 87%, the segmentation accuracy was 90% and the recognition accuracy was 86%. CCS CONCEPTS • Computing methodologies • Artificial intelligence • Computer vision • Computer vision problems • Object recognition