Machine vision system for weed detection using image filtering in vegetables crops - Camilo Andrés Pulido-Rojas; Manuel Alejandro Molina-Villa; Leonardo Enrique Solaque-Guzmán (Revista Facultad de Ingeniería Universidad de Antioquia, 2016)
This work presents a machine vision system for weed detection in vegetable crops using outdoor images, avoiding lighting and sharpness problems during acquisition step. This development will be a module for a weed removal mobile robot with camera obscura (Latin for “dark room”) for lighting controlled conditions. The purpose of this paper is to develop a useful algorithm to discriminate weed, using image filtering to extract color and area features, then, a process to label each object in the scene is implemented, finally, a classification based on area is proposed, including sensitivity, specificity, positive and negative predicted values in order to evaluate algorithm performance.