Iris Diagnosis – A Quantitative Non-Invasive Tool for Diabetes Detection

Conference: McGraw-Hill International Conference on Signal, Image Processing Communication and Automation
Author(s): Mithun B S, R Sneha, Vinay Raj K, Basavaraj Hiremath, B. Ragavendrasamy Year: 2017
Grenze ID: 02.MH-ICSIPCA.2017.1.85 Page: 545-551

Abstract

Iris Diagnosis is a novel approach to assess various pathological conditions based on the Iris patterns. Iris Image\nanalysis is a non-invasive technique for determining the health condition of an individual. Correct and timely diagnosis is\ncritical, yet is the absolute requirement of medical science. In general, current approaches fail to diagnose various diseases\ncorrectly. An attempt is being made in the current research to explore the possibility of diagnosing diabetes from the\nrepresentations of the Iris. Initially the images of eye are captured using Iridoscope and a database is created with their\nclinical history. Various algorithms are developed to assess the quality of the Iris image, and then segmentation and feature\nextraction techniques such as GLCM and DCT are applied. Feature extraction plays a vital role in assessment of the\nindividual to be diabetic or not. In order to assess the presently proposed approach, 30 patient data were acquired for which\nthe present approach was able to detect diabetic or not with an accuracy of 83%.

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MH-ICSIPCA - 2017