In the field of agriculture, image processing is a constantly evolving field of research and progress. Currently, several plant disease identification studies are underway. Identifying plant diseases can not only help farmers increase yields, but also promote a variety of agricultural practices. This paper proposes an algorithmic program for the diseases detection and categorization with the assistance of machine learning mechanisms and image recognition tools. First detect and record the contaminated area and then perform image pre-processing. Then collect the fragments, identify the infected area, and perform feature extraction on it. This article discusses the methods of using leaf photography to detect plant diseases. In addition, this article also introduces some feature segmentation and extraction algorithms for plant disease detection.