Automatic License Plate Detection and Recognition for Jordanian Vehicles

摘要

Nowadays, automatic number plate recognition (ANPR) is very important especially in the era of smart cities and intelligent transport systems. Fully automated number plate detection and recognition system helps in reducing time, error, and cost for tracking of vehicles and for recording traffic violations. The main goal of this paper is to design a low cost fully automated number plate detection and recognition system targeting the Jordanian license plates. Several problems (e.g., cost, wasted efforts, manual intervention, and possible errors) were identified in the currently used Jordanian number plate recognition for recording traffic violations. We hope that the proposed system would mitigate such problems. The proposed system performs two main tasks. First, it automatically detects and recognizes the license plate number of a given Jordanian vehicle using a robust metric; the rectangularity measurement, and identifies the vehicle’s type (e.g., governmental, private, visitor, public, etc.). Second, it recognizes a selected number of trained classes for the make of the vehicle whenever applicable. The experimentation results and the performance evaluations compared to other ANPR approaches show that proposed system achieves the best performance among the tested systems with a plate detection accuracy of 95%, OCR recognition accuracy of 94.68%, make recognition accuracy of 86.84%, and an overall ANPR accuracy of 89% excluding the make results.