RETINAL IMAGE SEGMENTATION ANALYSIS TO DETECT GLAUCOMA AND EXUDATE USING SVM CLASSIFIER
Author’s Name : Subhasree D | Suganthi B | Kannan R
Volume 05 Issue 02 Year 2018 ISSN No: 2349-252X Page no: 18-21
In this paper the diabetic retinopathy is analysed from an image using exudate and glaucoma secretion in the retina. An Edge analyzing from the scanned image to change the value in the image intensity usually associated with a discontinuity in either the image intensity. Edge detection is a problem of fundamental importance in object extraction as it reduces image data and detects the object which is required. Edges identify object boundaries and are detected through changes in grey level above a particular threshold. A Diabetic retinopathy is a very recent method of finding the level of acid secretion in the eye while the persons are having diabetics in their body. The edge detection is mainly applicable in case of data transmission; in that case the detected edge data reduce the amount of data to be transmitted. The experimental results show that our method achieves 91% in sensitivity and 92% in positive prediction value (PPV), which both outperforms the state of the art methods significantly.
Retinopathy, Diabetics, Android, SVM Classifier, Digital Image Processing
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