A Machine Vision Based Detection & Classification of Neovascularisation in Retinal Blood Vessels
S.Sudha1, A.Srinivasan2, S.Karthik3, S.Hari Krishnan4, S.Prakash5
1S.Sudha, Department of ECE School of EEE, SRC SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
2A.Srinivasan, Department of ECE School of EEE, SRC SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
3S.Karthik,, Department of ECE School of EEE, SRC SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
4S.Hari Krishnan, Department of ECE School of EEE, SRC SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
5S.Prakash, Department of ECE School of EEE, SRC SASTRA Deemed University, Kumbakonam, Tamilnadu, India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 1468-1471 | Volume-8 Issue-10, August 2019 | Retrieval Number: : : J10170881019/19©BEIESP| DOI: 10.35940/ijitee.A1017.0881019
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diabetic Retinopathy is an eye disease which is caused by excessive sugar level in blood. Insufficient secretion of insulin hormone is the ground for evolution of diabetes. It affects most of the important organs in our body. There are two types of DR: Non Proliferative Diabetic Retinopathy and Proliferative Diabetic Retinopathy. In this proposed system techniques are introduced to detect and classify neovascularisation. Input fundus image is preprocessed by median filtering and further new vessels are segmented by using Fuzzy c-means clustering algorithm. After segmentation SIFT features are extracted and are used to train support vector machine (SVM) classifier. This automated system has been tested for 70 fundus images and accuracy of 96% is achieved.
Keywords: Diabetic Retinopathy (DR); Median Filtering (MF); Fuzzy C-Means Clustering algorithm (FCM); Support vector machine (SVM) classifier; Neovascularisation (NV)
Scope of the Article: Classification