FCM based iris image analysis for tissue imbalance stage identification

The iris of human eye is globally identified as the better solution for biometric systems with its unique 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. 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, iris signs and the corresponding 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 due to problems in lung organ, using Image Processing techniques such as Circular Hough Transform, Fuzzy C-Means clustering and Gray level analysis. The efficiency of the proposed system is analyzed for its correctness with iridologist report.