Real Time Non-Invasive Iris Image Analysis for Pulmonary Disease Identification and Corrective Measure of Iridology

Abstract

The iris of human eye is globally identified as the better solution for biometric systems with its uniqueness feature and complex pattern. In other side the iris has the significance to reflect the changes in human body with the varying health condition. This study of the iris for medical purposes is called iridology. A primary theory of Iridology is that the iris is constructed in layers that represent the four stages of tissue activity, namely acute changes, sub-acute changes, chronic changes and degenerative changes. By noting which layer has the defect, the iridologist can suggest what the nature of the problem is. Iridology is a novel, cost-effective and non-invasive approach of medical analysis because there are no touching, no damage to human body. The Iridologists have to measure color of iris, its density, open and closed lesion, sign on iris image and the location of body organ in iris image as stated in iridology chart. This paper is proposing a real time approach to analyze human iris specifically for Pulmonary Diseases using existing better Image Processing techniques such as Circular Hough Transform, Gabor Wavelet and proposed Water Flow Segmentation model and finally to measure correctness of iridology experimentally through comparative study with Clinical Testing.