Early Detection Of Glaucoma Using SVM

Journal of Multi Disciplinary Engineering Technologies, Vol. 14, Issue 1

Paper Title: Early Detection Of Glaucoma Using SVM

Authors: M.Senthil Vadivu, Padmanabhan Rohineesh Dharan, Uthraa R Y, Sathish Kumar V, Anbuselvan D

Corresponding Author Email: rohinish.s99@gmail.com

Abstract: Glaucoma is the retinal disorder which is leading cause for blindness. Glaucoma is classified into two types namely open angle glaucoma and closed angle glaucoma. Earlier detection of glaucoma will prevent the vision loss. Parameters involved in assessing glaucoma are intra ocular pressure (IOP), visual field and cup- to-disc ratio (CDR). Glaucoma causes an increase in CDR value, thus affecting the peripheral vision loss. With the help of Image Processing techniques, CDR values can be estimated. These CDR values can be used to detect the presence of Glaucoma. There are a number of common image processing techniques involved such as pre-processing, feature extraction and classification. The classifier used below is Support Vector Machine (SVM) because the process is simple and accuracy is so high, performance is very good.

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