Automatic Eye Screening Method Based on a Multi -Anatomical Retinal System Segmentation with the Help of Morphology & Fuzzy Logic
Tulasi vitta1, Shaik saheb basha2
1Tulasi Vitta, Department of ECE, G. Pulla Reddy Engineering College,(Autonomous), Kurnool, A.P. India
2Dr. Shaik Saheb Basha, Professor, Department of ECE, G. Pulla Reddy Engineering College, Kurnool, A.P. India
Manuscript received on 02 July 2019 | Revised Manuscript received on 07 July 2019 | Manuscript published on 30 August 2019 | PP: 724-729 | Volume-8 Issue-10, August 2019 | Retrieval Number: J88800881019/2019©BEIESP | DOI: 10.35940/ijitee.j8880.0881019
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© 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: Eye examination is used to determine Retinal problems at an early stage. Retina screening can be used to detect various hidden retinal problems including pre-diabetes and diabetes. The doctors will depend on segmentation results of retinal structures to determine the abnormalities in the eye. A novel algorithm for instant identification and segmentation of the optic disk (OD) and detection of exudates in human retinal images is described in this document. The proposed technique uses segmentation methodology for automatically detecting of these structures. This methodology uses morphology theories and fuzzy techniques to detect the structures even in pathological images. The performance is evaluated using two datasets that is DRISHI-GS (optic disc) and DIARETD1 (exudates). Present methods have accuracy and efficiency is less, but in the proposed new novel method i.e morphology based fuzzy logic, we achieved an accuracy 92.91% and PPV (positive predictive value) is 89.54% in optic disc. specificity and F-score also trained with help of subjected method 99% and 93.17% in exudate.
Keywords: Retinal structures, optic disc, exudates, morphological theory, fuzzy logic, fuzzy c-means, convex hull transform.
Scope of the Article: Fuzzy Logics