Journal of Computer Science

LICENSE PLATE LOCALIZATION USING GABOR FILTERS AND NEURAL NETWORKS

Sami Ktata, Faouzi Benzarti and Hamid Amiri

DOI : 10.3844/jcssp.2013.1341.1347

Journal of Computer Science

Volume 9, Issue 10

Pages 1341-1347

Abstract

Vehicle License Plate Detection (LPD) is an important step for the vehicle plate recognition which can be used in the intelligent transport systems. Many methods have been proposed for the detection of license plates based on: Mathematical morphology, Discrete Wavelet Transform, Hough Transform and others. In general, an LPR system includes four main parts: Vehicle image acquisition, license plate detection, character segmentation and character recognition. In this study, we present a robust method for extracting and detecting license plates, from simple images of Tunisian vehicles, based on Gabor filters and neural networks. The proposed method is designed to perform recognition of any kind of license plates under any environmental conditions.

Copyright

© 2013 Sami Ktata, Faouzi Benzarti and Hamid Amiri. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.