Abstract: Recently, one of the active research areas in agriculture productivity and quality of a crop.During the past decades, dramatic improvement of agriculture which plays a vital role in improving economic status have been achieved in all over the world considerably. The innovative technology approachis being advocated, particularly farmers in less favorable. The main concept of the work helps to improve productivity and sustainable agriculture using low external inputs, and also less harmful to nature recourses. The goal of this research is to develop an image recognition system that can recognize thewheat disease. To automate these activities, like texture. Color and shape, disease recognition system is feasible. The work concentrated on Triticum Aestivum (Wheat) disease detection by digital image processing. This is the novel approach of disease detection in wheat instead of many different disease detection techniques have been proposed for the wheat crops. The obtained image can be processed by using LabVIEW. The results are analyzed also evaluated through classification techniques. The results, which we have achieved, are more useful and they prove to be helpful for formers during the cultivation of wheat, a major food crop in the world.
Keywords: Color, texture, shape, Threshold image, LabVIEW, Digital image processing and precision agriculture