Parallel License Plate Location based on Multiagent System

Abstract

Automatic license plate recognition is a necessary step in intelligent traffic systems. Many methods are reported for License Plate Recognition (LPR) implementation until now. Real time LPR plays a major role in automatic monitoring of traffic rules and maintaining law enforcement on public roads. The automatic identification of vehicles by the contents of their license plates plays an important role in private transportation system applications. However there are a lot of systems in universal markets, but research and development are still continuing, and advanced solutions are reported. In this paper initially, image processing concepts of LPR and multiagent systems are introduced. Then, based on the expressed concepts, a multiagent model for License Plate Location proposed. The proposed model uses three agents i.e., Accurate Gabor, Speedy Multiple Interlacing (MI) and Judgment agents. The accurate-gabor agent utilizes gabor filter. Speedy-MI agent uses the Multiple Interlacing approach in parallel, then those images that the speedy-MI agent has not been able to detect, is delegated to the accuracy-gabor agent by the judgment agent. The proposed system implemented and tested on 200 images. The results show that the overall accuracy has been improved, and tends to the accuracy of 100%, due to the cooperation of accuracy-gabor, Speedy-MI and judgment agents.