Paddy Plant Disease Detection Using Image Processing

Abstract

Rice is the most significant human food crop and almost every Malaysian consume it daily. However, paddy plant diseases have significantly caused damage to the crop, reduced the rice production and threatening the food security in Malaysia. The traditional way of identifying the disease is inspecting it manually using naked eyes, which produce inaccurate results and it is time-consuming. Hence, development of image processing algorithm is vital to assist the farmers in detecting the diseases on paddy plant. In this paper, the Random Forest classifier is proposed to classify the three common paddy plant diseases which are rice blast, brown spot and narrow brown spot disease. The proposed method effectively detects and classify paddy plant disease with an overall accuracy of 93%.