Soft Computing and Image Processing for Detection and Analysis of Plant Infections

Abstract

We provide a comprehensive evaluation of methods for detecting plant diseases in images taken under normal lighting conditions. The aim of these methods is to use digital image processing to identify plant diseases, rank their severity, and classify them into different categories. Disease symptoms could appear everywhere on a plant, but researchers here focused on the parts of the plant that could be seen by the human eye, such the leaves and stems. This was done for two reasons: (a) to keep the essay at a manageable length, and (b) to provide a more in-depth explanation of the subtleties involved in dealing with roots, seeds, and fruits. Taking these factors into account was crucial to making this decision. There are three broad classes into which the consensus standards fall: detection, severity measurement, and classification. The algorithm's preliminary technical response serves as a basis for subsequent breakdown of each class. Experts in the fields of vegetable pathology and pattern recognition may find this study's comprehensive overview to be useful.