Image Processing Based Detection of Fungal Diseases in Plants

This paper presents a study on the image processing techniques used to identify and classify fungal disease symptoms affected on different agriculture/horticulture crops. Computers have been used to mechanization, automation, and to develop decision support system for taking strategic decision on the agricultural production and protection research. The plant disease diagnosis is limited by the human visual capabilities because most of the first symptoms are microscopic. As plant health monitoring is still carried out by humans due to the visual nature of the plant monitoring task, computer vision techniques seem to be well adapted. One of the areas considered here is the processing of images of disease affected agriculture/horticulture crops. The quantity and quality of plant products gets reduced by plant diseases. The goal is to detect, to identify, and to accurately quantify the first symptoms of diseases. Plant diseases are caused by bacteria, fungi, virus, nematodes, etc., of which fungi is the main disease causing organism. Focus has been done on the early detection of fungal disease based on the symptoms.