Glaucoma Detection using the Thermal Image Processing

Abstract

Diabetes has become a common disease nowadays. The count says at least one person in a house is suffering from diabetes. Diabetes gives rise to various diseases that can damage various organs of the body including the eyes, kidneys, gums, etc. Diabetes is one of the common causes where vision is lost amongst people and blindness occurs among working-age adults. Among all the eye diseases, type of glaucoma is an invisible type of disease that can damage the optic nerve, which carries all the information transmitted by the eye to the brain and can cause complete blindness. This disease can be detected by invasive and non-invasive methods. Thermography is the tool that can be used to avoid this damage non-invasively. Thermal images of the patients and normal people were taken with the help of the thermal camera. With the help of thermal images and image processing, the features were extracted using four properties of GLCM. Based on these properties classification is done which resultsin differentiating the normal and abnormal patients. The SVM classifier has achieved a maximum accuracy of 95%. This paper reveals different invasive methods which are used to detect and test glaucoma and the use of non-invasive method i.e., thermography over the invasive methods.