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Genetic Algorithm for Retinal Image Analysis

Novel Aspects of Digital Imaging Applications
© 2011 by IJCA Journal
ISBN: 978-93-80865-47-9
Year of Publication: 2011
Jestin V.K.
D.Jude Hemanth

Jestin V.K., J.Anitha and D.Jude Hemanth. Genetic Algorithm for Retinal Image Analysis. IJCA Special Issue on Novel Aspects of Digital Imaging Applications (DIA) (1):48–52, 2011. Full text available. BibTeX

	author = {Jestin V.K. and J.Anitha and D.Jude Hemanth},
	title = {Genetic Algorithm for Retinal Image Analysis},
	journal = {IJCA Special Issue on Novel Aspects of Digital Imaging Applications (DIA)},
	year = {2011},
	number = {1},
	pages = {48--52},
	note = {Full text available}


Diabetic Retinopathy is one of the leading causes of blindness. Hard exudates have been found to be one of the most prevalent earliest clinical signs of retinopathy. Thus, identification and classification of hard exudates from retinal images is clinically significant. For this purpose the images from the hospitals were taken as reference. In this work, Genetic Algorithm (GA) for best feature selection from retinal images is proposed. The features that improve the classification accuracy are selected by Genetic Algorithm and termed as optimized feature set. The others that degrade the performance are rejected at the end of specified generation (in this case 100 generations).


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