An Effective Screening System to Detect Diabetic Retinopathy by using Dehazing Technique
L. Saravanan1, K. Senthil Kumar2, Nami Susan Kurian3, A. Balaji4
1L.Saravanan, Assistant Professor, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India. Email:
2K.Senthil Kumar, Associate Professor, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India. Email:
3Nami Susan Kurian, Assistant Professor, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India. Email:
4Balaji.A, Assistant Professor, Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Chennai, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 3746-3749 | Volume-8 Issue-5, January 2020. | Retrieval Number: D4297118419/2020©BEIESP | DOI: 10.35940/ijrte.D4297.018520
Open Access | Ethics and Policies | Cite | Mendeley
© 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 Diabetic Retinopathy (DR) is playing a crucial role in clinical data analysis to diagnose abnormality in retina. Many situations the early stage of patient is not aware of any symptoms until it is too late for effective treatment. The abnormality in the blood vessels of diabetics, a way will be paved for prompt diagnosis of DR. In this work, we proposed the Dehazing method of fundus image to detect and classify the disease condition based on changes in blood vessels using thresholding segmentation technique using mean square error (MSE). Then formulate the area of extracted blood vessels in the subsequent analysis to classify accurately.
Keywords: Retinopathy Classification, Median Filter, Dehazing, Thresholding, Segmentation and Mean Square Error.
Scope of the Article: Classification.