Blood Vessel Segmentation in Fundus Images and Detection of Glaucoma using SVM

Glaucoma is an unending and irreversible eye infection in which the optic nerve is consistently hurt due to Intraocular pressure (IOP), inciting disintegrating in vision and individual fulfillment. Survey proposed by Glaucoma Research Foundation (GRF), a committed regional non-profit organization to finding a cure announced results of a national survey for glaucoma designed to assess the impact of glaucoma on patients. As a result of the survey total of 1,548 adults were suffered from glaucoma almost two-thirds (64 percent) of all patients say the disease impacts their lives on a daily basis. There is an existing method for identifying glaucoma which is based upon the ISNT ratio. The proposed system consists of image acquisition, image enhancement, image restoration, morphological processing and segmentation. Preprocessing of retinal image to separate the green channel and retinal image is enhanced. Blood vessel segmentation is done for detection of glaucoma using Support Vector Machine (SVM) algorithm. SVM algorithm is supervised learning algorithm which is mainly used in computer vision projects for artificial intelligence applications. By using this algorithm accuracy of detection of glaucoma is better than all the existing methods.