International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Since Year 2012 | Open Access | Double Blind Reviewed

ISSN: 2319-7064




Downloads: 121

Research Paper | Computer Science & Engineering | India | Volume 6 Issue 7, July 2017


Red Lesion Detection Using Hough Transform and KNN Classifier for Diabetic Retinopathy Screening

Fayiza K T | Sherin Jabbar


Abstract: Diabetic retinopathy is a major cause of blindness in the world. It will take more time to identify the clinical features such as microaneurysms, hemorrhages, exudates and cottonwool spots through manual inspection of fundus images. A computer assisted diagnosis system can help to reduce the burden on the ophthalmologist and rapidly identify the most severe cases. An efficient approach for red lesion detection in fundus image is proposed. The fundus image is preprocessed and Hough transform is used to identify the regions having red lesions. A KNN classifier is used to train the features which classifies the images according to their probability of being normal or with disease.


Keywords: Diabetic retinopathy, Microaneurysm, Hemorrhages, Thresholding, Hough Transform, KNN classifier, Automatic detection


Edition: Volume 6 Issue 7, July 2017,


Pages: 473 - 478


How to Cite this Article?

Fayiza K T, Sherin Jabbar, "Red Lesion Detection Using Hough Transform and KNN Classifier for Diabetic Retinopathy Screening", International Journal of Science and Research (IJSR), Volume 6 Issue 7, July 2017, pp. 473-478, https://www.ijsr.net/get_abstract.php?paper_id=ART20174218

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