License Plate Character Recognition using Riesz Fractional and Convolutional Neural Network
Challa Chaitanya Chowdary1, Udaya Kiran2
1Challa Chaitanya Chowdary, Student, KKR&KSR Institute of Technology & Sciences, Vinjanampadu Village, Andhra Pradesh, India.
2Udaya Kiran, KKR&KSR Institute of Technology & Sciences, Vinjanampadu Village, Andhra Pradesh, India.
Manuscript received on 10 July 2019 | Revised Manuscript received on 22 July 2019 | Manuscript Published on 23 August 2019 | PP: 1432-1436 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I33050789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3305.0789S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Character recognition, convolutional neural network, license plate recognition.
Scope of the Article: Image Processing and Pattern Recognition