Alzheimer Detection using Image Processing and Iridology

Abstract

Iridology is in particular the systemic diagnosis of human conditions by observing iris changes. Alzheimer's disease is one of the main reasons for death in developed nations, research has become interested in understanding its cause, and in the prediction of disease by monitoring the iris. This paper aims to show that there are alternative methods to detect certain neuronal disorders, specifically Alzheimer's. To detect Alzheimer's, there is a requirement of the pattern associated with the iris of the eye through the digital processing of images in such a way that certain related to the alternative diagnosis can be issued. In this paper, an algorithm has been developed using Rubber Sheet Normalization and SVM classification techniques to classify Alzheimer's and non-Alzheimer iris images.