Conference Paper

Health examination based on iris images.

DOI: 10.1109/ICMLC.2010.5580885 Conference: International Conference on Machine Learning and Cybernetics, ICMLC 2010, Qingdao, China, July 11-14, 2010, Proceedings
Source: DBLP

ABSTRACT This study combined iridology with image processing technique to conducts iris disease examination. Iridology is not to determine disease, but to reflect degeneration of organic functions, toxin precipitation and various unhealthy situations caused by mental or other factors. Iris test technique applies simple and non-invasive healthy examination method, helps the people prevent disease, and regularly follows up self-health conditions to achieve real-time prevention and treatment. The system consists of four modules: eye image capture, image preprocessing, texture feature extraction and symptomatic analysis. Following the input of eye image, the required iris part is acquired from eye images by using image preprocessing module. The texture feature extraction module utilizes 2-D Gabor filter to extract texture feature. The symptomatic analysis module uses fuzzy theory to evaluate severity of organ symptoms.

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    ABSTRACT: 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.
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