Deteksi Penyakit Brown Eye Spot pada Daun Kopi Menggunakan Metode Euclidean Distance dan Hough Transform

Abstract

For utilization, image processing, leaf images taken from the coffee garden, both types of coffee, and its disease can be known at once. The Euclidean distance method is used to distinguish between robusta coffee and Arabica coffee to find out the type of coffee. There are so many diseases in coffee, but the disease used in this research is brown eyespot. The disease is detected using a Hough transform method because it can be used to identify a circle, which is a symptom of the disease. The purpose of the research is to analyze the effectiveness of the methods used. The first method is to measure the accuracy level of euclidean distance to distinguish between arabica leaf and robusta leaf. The second method is to analyze the level of accuracy to detect brown eyespot disease in leaves used using hough transform. Experiment attempts to 7 arabica leaves and four robustas leave using Matlab R2017a. The result of using the euclidean distance method has no error to distinguish the leaves, the seven arabica leaves detected as arabica leaves, and the four robusta leaves recognized as robusta leaves. In the second method to detect brown eyespot disease to the leaves used, the result of accuracy to arabica leaves is 55%, and robusta leaves are 50%.