@article {10.3844/jcssp.2013.1341.1347,
article_type = {journal},
title = {LICENSE PLATE LOCALIZATION USING GABOR FILTERS AND NEURAL NETWORKS},
author = {Ktata, Sami and Benzarti, Faouzi and Amiri, Hamid},
volume = {9},
number = {10},
year = {2013},
month = {Sep},
pages = {1341-1347},
doi = {10.3844/jcssp.2013.1341.1347},
url = {https://thescipub.com/abstract/jcssp.2013.1341.1347},
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.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}