International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 91 - Issue 16 |
Published: April 2014 |
Authors: A. Elbalaoui, M. Fakir, A. Merbouha |
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A. Elbalaoui, M. Fakir, A. Merbouha . Segmentation and Detection of Diabetic Retinopathy Exudates. International Journal of Computer Applications. 91, 16 (April 2014), 7-13. DOI=10.5120/15963-5155
@article{ 10.5120/15963-5155, author = { A. Elbalaoui,M. Fakir,A. Merbouha }, title = { Segmentation and Detection of Diabetic Retinopathy Exudates }, journal = { International Journal of Computer Applications }, year = { 2014 }, volume = { 91 }, number = { 16 }, pages = { 7-13 }, doi = { 10.5120/15963-5155 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2014 %A A. Elbalaoui %A M. Fakir %A A. Merbouha %T Segmentation and Detection of Diabetic Retinopathy Exudates%T %J International Journal of Computer Applications %V 91 %N 16 %P 7-13 %R 10.5120/15963-5155 %I Foundation of Computer Science (FCS), NY, USA
Diabetic retinopathy, the most common diabetic eye disease, occurs when blood vessels in the retina change. Sometimes these vessels swell and leak fluid or even close off completely. In other cases, abnormal new blood vessels grow on the surface of the retina. Early detection can potentially reduce the risk of blindness. This paper presents an automated method for the detection of exudates in retinal color fundus images with high accuracy, First, the image is converted to HSI model, after preprocessing possible regions containing exudate, the segmented image without Optic Disc (OD) using algorithm Graph cuts, Invariant moments Hu in extraction feature vector are then classified as exudates and non-exudates using a Neural Network Classifier. All tests are applied on database DIARETDB1.