Classification of Abnormalities in the Heart Through Iris Eye Images Using Fuzzy C-Means as a Feature Capture and Classification Using Support Vector Machine
Iridology is the diagnosis of an iris that represents signs such as the color and structure of the iris so that information about one’s health is obtained. This research is about computerized iridology by a system used in detecting heart conditions that are designed with steps such as pre-process conversion of RGB images to Grayscale, noise removal using a median filter, trimming, grouping using Fuzzy C-Means (FCM), detection edge using the Canny method and followed by the extraction feature using the Gray Level Co-occurrence Matrix (GLCM), and classification using the Support Vector Machine (SVM). The iris sample of the patient is normal and abnormal. Data iris of patients who have heart abnormalities as many as 20 images. The results of the detection of cardiac abnormalities through this iris image have an accuracy rate of 75%.
Prodi Matematika, Fakultas Sains dan Teknologi, Universitas Islam Negeri Sunan Ampel Surabaya