Applied of color image processing system to detect plant disease using clustering algorithms

Abstract

In recent times, after the changing of weather conditions and the pollution of water resources and air, the green cover of the earth has got many infections and the agricultural crop started to suffer many diseases. These diseases are able to catch and decide the suitable medicine in many ways. Maybe one of the most important ways is to check the change of plants' leaves. Plant leave disease detection uses several methods like image processing and deep learning. All of these methods suffer from the high similarity of some diseases, the different sizes of leaves, and the colors of them. Which caused the lower accuracy of detecting the right disease. Neural network methods were used too, but needed a higher computation time and more computation power. All of above provides image processing techniques superior advantages over other techniques. Other techniques, such those employing KNN, MLP, and Gaussian classifiers, provide accuracy that is lower than that of SVM techniques when using applications.