Application of Support Vector Machine for Detecting Rice Diseases Using Shape and Color Texture Features

Abstract

For detecting rice disease early and accurately, we presented an application of image processing techniques andSupport Vector Machine (SVM) for detecting rice diseases.Rice disease spots were segmented and their shape and texture features were extracted. The SVM method was employed to classify rice bacterial leaf blight, rice sheath blight and rice blast. The results showed that SVM could effectively detect and classify these disease spots to an accuracy of 97.2%.