Open AccessLicense Plate Character Recognition using Riesz Fractional and Convolutional Neural Network
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i3305.0789s319
Subject(s) - license , character (mathematics) , identification (biology) , character recognition , convolutional neural network , artificial intelligence , convolution (computer science) , computer science , pattern recognition (psychology) , artificial neural network , computer vision , speech recognition , image (mathematics) , mathematics , geometry , botany , biology , operating system
Automatic license plate recognition system is mostly used for identification of vehicles. This system is used in traffic monitoring, parking management and identification of theft vehicles. As in India the license plate regulations are not strictly followed, it is often difficult to identify the plate with different font type and character size. One more major problem in license plate recognition is low quality of images which affected via severe illumination condition. In this paper, a Riesz fractional mathematical model is proposed for enhancing the edges, which results in improving the performance of text recognition. The text in the license plate is recognized using the convolution neural network and the results showed better accuracy.