Recognition Of Powdery Mildew Disease For Betelvine Plants Using Digital Image Processing

Abstract

The fresh leaves of betel vine are generally known as paan in India, which are inspired by about 20-30 million people in the country. It is cultivated in India about 75,000 hectares with an annual production worth about Rs. 1000 millions. Betelvine plants may have various disease infected in the entire plantation without any early indications of the diseases. The aim of this paper is to recognize powdery mildew disease in the betelvine plants using digital image processing and pattern recognition techniques. The digital images of the betelvine leaves at various stages of the disease are collected from different plants using a high resolution digital camera and it is stored with JPEG format. The image analyses of the leaves are done using the image processing toolbox in MATLAB which provides the standard patterns of the digital images. Using RGB encoding technique the red, green and blue components of the preprocessed image were separated, which forms the pattern to be compared. These patterns and images of various healthy betelvine leaves at different stages in various days are collected and stored in the system. The mean and median values for all sample leaves are computed and calculated values are stored in the system. The mean and median values of test leaves are computed and compared with the stored values. As the result of this comparison, it is identified whether test leaves are affected by powdery mildew disease or not. Finally this analysis helps to recognize the powdery mildew disease can be identified before it spreads to entire crop.