Riesz fractional based model for enhancing license plate detection and recognition

Raghunandan, K. S. and Shivakumara, P. and Jalab, Hamid A. and Ibrahim, Rabha W. and Hemantha Kumar, G. and Pal, Umapada and Lu, Tong (2018) Riesz fractional based model for enhancing license plate detection and recognition. IEEE Transactions on Circuits and Systems for Video Technology, 28 (9). pp. 2276-2288. ISSN 1558-2205

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Official URL: http://dx.doi.org/10.1109/TCSVT.2017.2713806

Abstract

One of the major causes of poor results in license plate recognition is low quality of images affected by multiple factors, such as severe illumination condition, complex background, different weather conditions, night light, and perspective distortions. In this paper, we propose a new mathematical model based on Riesz fractional operator for enhancing details of edge information in license plate images to improve the performances of text detection and recognition methods. The proposed model performs convolution operation of the Riesz fractional derivative over each input image by enhancing the edge strength in it. To test the performance of the proposed model, we conduct experiments on benchmark license plate image databases, namely, UCSD and ICDAR 2015-SR competition text image databases. Experimental results on enhancement show that the proposed model outperforms the existing baseline enhancement techniques in terms of quality measures. Furthermore, experimental results on text detection and recognition show that text detection and recognition rates are improved significantly after enhancement compared with before enhancement.

Item Type: Article
Uncontrolled Keywords: convolution;edge detection;image enhancement;image resolution;object recognition;text detection;traffic engineering computing;illumination condition;weather conditions;convolution operation;license plate detection;baseline enhancement techniques;multiple factors;license plate recognition;ICDAR 2015-SR competition text image databases;benchmark license plate image databases;edge strength;input image;Riesz fractional derivative;text detection;license plate images;edge information;Riesz fractional operator;mathematical model;perspective distortions;night light;complex background;Licenses;Text recognition;Image edge detection;Robustness;Image resolution;Lighting;Low quality images;enhancement model;Riesz fractional order derivative;license plate text detection;license plate recognition
Subjects: D Physical Science > Computer Science
Divisions: Department of > Computer Science
Depositing User: Manjula P Library Assistant
Date Deposited: 06 Jul 2019 11:32
Last Modified: 04 Jan 2020 10:57
URI: http://eprints.uni-mysore.ac.in/id/eprint/4848

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