Author(s): M. Iyapparaja, P. Sivakumar

Email(s): iyapparaja85@gmail.com

DOI: 10.5958/0974-360X.2019.00011.8   

Address: M. Iyapparaja1*, P. Sivakumar2
1Associate Professor, School of Information Technology and Engineering, VIT University, Vellore, Tamilnadu, India.
2Associate Professor, CSE Department, Saudi Electronic University, Saudi Arabiya, Riyadh, Chennai, Tamil Nadu, India
*Corresponding Author

Published In:   Volume - 12,      Issue - 1,     Year - 2019


ABSTRACT:
Diabetic retinopathy (DR) is a serious eye infection which cause visual impairment. Henceforth, early discovery of DR is an absolute necessity. Exudates is the essential indication of Diabetics in retina. At the initial treatment of DR is conceivable in the event that we recognize Exudates at the most punctual arrange. The principle centralization of paper is to speak about strategies for productive discovery of Exudates. The first technique talks about Exudate discovery utilizing numerical morphology. The next procedure, proposes a half approach for detection of Exudates. These approach comprises of some phases pre-processing technique, grouping, and post processing. At the pre-processing stage, resizing the picture and morphological enlargement done. At grouping stage LindeBuzo-Grey is applied, k-implied calculation to recognize Exudates. In post preparing step, we expel every undesirable component segments in the picture to receive exact outcomes. The ideal outcomes will be got when the quantity of groups took is 8 in both of the grouping calculations.


Cite this article:
M. Iyapparaja, P. Sivakumar. Detecting Diabetic Retinopathy exudates in digital image processing Hybrid Methodology. Research J. Pharm. and Tech 2019; 12(1): 57-61. doi: 10.5958/0974-360X.2019.00011.8

Cite(Electronic):
M. Iyapparaja, P. Sivakumar. Detecting Diabetic Retinopathy exudates in digital image processing Hybrid Methodology. Research J. Pharm. and Tech 2019; 12(1): 57-61. doi: 10.5958/0974-360X.2019.00011.8   Available on: https://rjptonline.org/AbstractView.aspx?PID=2019-12-1-11


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

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