The present research concentrated on spontaneous recognition approach for image exploration on rice leaves in a variety of usual conditions for advance investigation. The condition plays a crucial role in regulating and eradicating of features in image processing. Some of the dangers, nevertheless, continue to be inaccurate at forecasting inflammation. The anticipated algorithm concentrates on a precise challenge to predict the inflammation from the early warning in order to counteract such hazards. In rice crops, microbial leaf blight and brown spot are the two most common bacterial and fungal inflammations; they lead to harvest loss and worse grain quality. An automatic detection approach for pinpointing the precise inflammation in rice leaves under various natural conditions has been proposed after analyzing several hybrid image analysis and regulation algorithm techniques. Using image data, this structure can categorize the proportion of diseased and vigorous rice plants. With a large agricultural farm, this approach can simplify our task of identifying diseased plants. I'm optimistic that it will expedite the process of classifying our work.