Automated Diabetic Retinopathy Detection using CS Based SVM Techniques
Sunil S S1, S. S Anusuya2
1Mr.Sunil S S, Computer Science and Engineering, MET’S School of Engineering, Thrissur,India.
2Dr.S Anusuya, Computer Science and Engineering,Saveetha School of Engineering, Chennai, India.
Manuscript received on 5 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 1843-1848 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4638098319/19©BEIESP | DOI: 10.35940/ijrte.C4638.098319
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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: Diabetes is one of the metabolic maladies where a patient has high glucose either brought about by body inability to create enough insulin or the cells inability to react to deliver insulin. This ceaseless ailment may prompt long haul inconveniences and death. It can cause high danger of kidney disappointment, nervous system harm, visual impairment and coronary illness. During the ongoing years there have been numerous examinations on programmed finding of diabetic retinopathy utilizing a few features and techniques. In this work at first the color fundus image can be utilized for processing, methods, for example, Median filtering, Morphological transformation, or Histogram equalization used to improve the nature of the image. Then to detect microaneurysms, blood vessels and optic disc using the techniques like morphological thresholding transformation, and the features are extracted from Grey level Co-occurrence Matrix (GLCM), Gabor Feature extraction and Linear Binary Pattern (LBD).At long last, for classify the various phases of diabetic retinopathy, SVM (support Vector Machine) Algorithm will be utilized, the outcomes are optimized by Cuckoo Search (CS) calculation.
Keywords: Cuckoo Search (CS), SVM (support Vector Machine), Gabor Feature Extraction, Linear Binary Pattern (LBD), GLCM, Median filtering.
Scope of the Article: Automated Software Design and Synthesis