Classification of Rice Leaf Diseases Based onMorphological Changes

Abstract

Rice is widely cultivated economical crop in the world. During cultivation the earliest and accurate diagnosis of the rice plant diseases able to reduce the damage, resulting environment protection and better return. In the work, an automated system has been developed to classify the leaf brown spot and the leaf blast diseases of rice plant based on the morphological changes of the plants caused by the diseases. Radial distribution of the hue from the center to the boundary of the spot images has been used as features to classify the diseases by Bayes' and SVM Classifier. The system has been validated using 1000 test spot images of infected rice leaves collected from the field, gives 79.5% and 68.1% accuracies for Bayes' and SVM Classifier based system respectively. blast and the brown spot diseases based on the morphological changes caused by the diseases. The accuracy of the proposed system is compared with the existing classifier, which shows comparable results. The paper, is organized in four Section II describes the process of image acquisition and feature extraction. Section III describes the classification process. Section IV represents results and discussion and the paper is concluded in section V.