Detection of Pterygium Disease Using Forward Chaining and Viola Jones Algorithm

Abstract

Eyesight is one of the most important senses for human life. Because only with our eyes, we can see and know the situations and conditions that occur around us. If there are problems or disorders that happen in our eyes, then we will feel uncomfortable and there are several diseases that can reduce the quality of vision and can cause blindness. In this project the author will be make an application to detect Pterygium eye disease based on the early symptoms that have been felt by the patient and find out how severely the patient affected by Pterygium disease with different levels. The stages used to determine the level of Pterygium disease is by filling all the symptoms by the patient in the application using Forward Chaining method and using an image segmentation process with Viola Jones Algorithm. The results of using the Viola Jones algorithm that have been processed using this application have an accuracy rate of 76% by testing 50 images and the results of the images detected are 38 images, in addition there are some images that are not detected and there are some images that are not detected.