Open Access Open Access  Restricted Access Subscription or Fee Access

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

K. Sivasankar


The study of the iris for medical purposes is called
iridology and it is the science of analyzing the delicate structures of the iris of the eye. In iridology point of view the iris has very close relationship with every organ in the body. Iris analysis is having many advantages for iridologists in order to detect symptom in patient's iris. Iridology is a novel 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. Many consider iridolgy a “fringe” practice and it is a pseudoscience, but it has enormous
potential when practiced correctly. So this project is proposing a real time approach to analyze human iris for Pulmonary Diseases using Image Processing techniques and proposed to measure correctness of iridology experimentally through comparative study with Clinical Testing. The comparative study is based on Iridology Chart developed by Dr. Bernard Jensen. The pulmonary diseases are the problems in lungs area which is in position at 9.0 to 10.0 in right iris and 2.0 to 3.0 in left iris based on Jensen Chart.


Iridology, Pulmonary Diseases, Water Flow Method, Circular Hough Transform, Jensen Chart.

Full Text:



Preliminary Study on Iris Recognition System: Tissues of Body Organs

in Iridology by Zuraini Othman, Anton Satria Prabuwono , 2010 IEEE

EMBS Conference.

Early Detection on the Condition of Pancreas Organ as the Cause of

Diabetes Mellitus by Real Time Iris Image Processing - Adhi Dharma

Wibawa, Mauridhi Hery Purnomo, 2006 IEEE.

Health Examination Based On Iris Images, Cheng-liang Lai , Chien-lun

Chiu -2010.

Using Iris Recognition Algorithm, Detecting Cholesterol Presence - R.

A. Ramlee, S.Ranjit , 2009.

Design of an Iris-Based Medical Diagnosis System - Adrian Lodin,

Sorina Demea, 2009 IEEE.

Daugman J "Gabor wavelets and statistical pattern recognition." The

Handbook of Brain Theory and Neural Networks, 2nd ed., MIT Press

(M. )

S. J. K. Pedersen, “Circular Hough Transform”, Aalborg University,

Vision, Graphics and Interactive Systems, November 2007 Arbib,

editor), 2002.

Daugman, J.G.: High Confidential Visual Recognition by Test of

Statistical Independence. IEEE Transactions on Pattern Analysis and

Machine Intelligence 15, 1148–1161 (1993)

L. Ma and N. Li : Texture Feature Extraction and Classification for Iris

Diagnosis Lecture Note in Com. Sc, Medical Biometric. Springer-Verlag

Berlin Heidelberg 2007

Colton, J., Colton, S.: Iridology, 10–25 (1991).

The Science and Practice of Iridology – Bernard Jensen. Volume I.

image segmentation based on water flow analogy, Xin Liu , thesis for

the degree of doctor of Philosophy, May 2009.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.