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     Research Journal of Applied Sciences, Engineering and Technology


Support Vector Machine Based Pades Approximant for Diabetic Retinal Eye Detection

1S. Vijayalakshmi and 2P. Sivaprakasam
1Karpagam University, Coimbatore-641659, India
2Department of Computer Science, Sri Vasavi College, Erode 638316, India
Research Journal of Applied Sciences, Engineering and Technology  2014  20:4206-4210
http://dx.doi.org/10.19026/rjaset.7.790  |  © The Author(s) 2014
Received: October 09, 2013  |  Accepted: November 18, 2013  |  Published: May 20, 2014

Abstract

Diabetic Retina (DR), a problem of formation of blood clot must be diagnosed at an early stage for laser therapy. A number of automated diagnosis methods based on image segmentation of fundus image is present which can diagnose DR at late mild proliferative stage. Proposed work is aimed to detect DR at early mild proliferative stage. Method uses feature extraction of fundus image using 2D Gabor filtering and pre-classification for feature vector extraction using Pades approximation. The Padesvector are then again classified using SVM by forming a dual of convex quadratic type minimization problem for linearly separable hyper plane. The performance of the proposed work is tested with set of images taken from fundus camera.

Keywords:

Diabetic Retina (DR), lagrangians multiplier, pades approximation, Support Vector Machines (SVM),


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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