PLANT DISEASE DETECTION TECHNIQUETOOL- A THEORETICAL APPROACH

Images form important data and information in biological sciences. Plant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products. Automatic detection of plant diseases is an essential research topic as it may prove benefits in monitoring fields of crops, and thus automatically detect the symptoms of diseases. This paper presents a method for identify plant disease based on color, edge detection and histogram matching. Farmers are suffering from the problem rising from various types of plant traits/diseases. Sometimes plant’s doctors & Farmers are also unable to recognize the disease that results in lack of identification of right type of disease and this leads to crop spoil if not taken care of at right time. The most significant part of research on plant disease to identify the disease based on CBIR (content based image retrieval) that is mainly concerned with the accurate detection of diseased plant. This research describes effective; sample technique for identify plant disease. The method used in this research is divided into two major phases. First phase concerns with training of healthy sample and diseased sample. Second phase concerns with the training of test sample and generates result based on the edge detection and histogram matching