Non-invasive Dry Eye detection using Fuzzy c-means Clustering Algorithm

Abstract

The background includes the study area of the dry eye taken from 75 patients to analyze eye-related disease. This method suggested as earlier detection of eye detection and tries to diagnose the problem. Early detection of eye problem helps the patient to have a clear line of sight distance through fuzzy c means clustering algorithm.The tear film must be detected at an early stage to protect the person from death. The tear film should be a monitor at the initial stage and diagnose by the unique technique, whether it may be the invasive or non-invasive method of dry detection. The invasive approach is the time-consuming process, and many disadvantages in this method arise in tear film detection. The non- invasive technique is not said to be a slow process. So the author proposed the novel approach of tear film detection by fuzzy c means clustering algorithm. The sample of eye images are taken and processed with fuzzy c means clustering algorithm and finds the intensity in both the eye. The accuracy analysis carried by fuzzy c indicates a clustering algorithm of 82% in its efficiency.