An image-based decision support methodology for weed management

Abstract

The use of images in precision farming needs efficient knowledge extraction techniques, allowing the identification of relevant information for management purposes. Focusing on weed management, a weed recognition algorithm is here proposed to verify the existence of undesirable weeds. The aim of this paper is to develop a decision support methodology based on weed recognition, detecting the undesired weed from aerial images and building an image-based viewpoint. Following this viewpoint, the user can make management decisions by evaluating the current conditions of the field and selecting the appropriate technology for treating weeds.