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Glaucoma Detection in Retinal Images using Automatic Thresholding and Marker – Controlled Watershed Transformation
Manikandan T1, Satheesh Kumar S2, Joshua Kumaresan S3, Shobana Priya M S4, Priyanka R5

1Manikandan T, Professor, Department of ECE, Rajalakshmi Engineering College, Chennai (Tamil Nadu), India.

2Satheesh Kumar S, Assistant Professor, Department of ECE, Sri Krishna College of Engineering and Technology, Coimbatore (Tamil Nadu), India.

3Joshua Kumaresan S, Associate Professor, Department of ECE, R.M.K Engineering College, Chennai (Tamil Nadu), India.

4Shobana Priya M S, Assistant Professor, Department of ECE, Saveetha School of Engineering, Chennai (Tamil Nadu), India.

5Priyanka R, Assistant Professor, Department of ECE, Saveetha School of Engineering, Chennai (Tamil Nadu), India.

Manuscript received on 23 November 2019 | Revised Manuscript received on 04 December 2019 | Manuscript Published on 14 December 2019 | PP: 210-213 | Volume-9 Issue-1S November 2019 | Retrieval Number: A10431191S19/2019©BEIESP | DOI: 10.35940/ijitee.A1043.1191S19

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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: The eye is an organ in human, responsible for the vision. However, it gets affected by the diseases. Glaucoma is a one such eye disease. It develops in the eye due to the increase in intra-ocular pressure. If glaucoma is not treated in its initial stage, leads for permanent vision loss. This work is aimed to develop a computer aided diagnosis system for glaucoma detection in fundus retinal images. In this paper, we presented a method to automatically outline the optic disc in a retinal image by automatic thresholding technique. The optic cup is segmented based on marker-controlled automatic watershed transformation. The optic cup to disc ratio (OCDR) is calculated, to show the presence of glaucoma. The proposed work is assessed with 15 normal retinal images and 15 retinal images with glaucoma, retrospectively collected from the Annai Eye Clinic, Chennai. To validate the system performance, obtained results were compared with the ophthalmologist results (taken as the gold standard). The experimental results show that, the proposed work is potential for the glaucoma detection.

Keywords: Fundus Retinal Image, Optic Cup, Optic Disc, Thresholding and Watershed Transformation.
Scope of the Article: Image Security