Resumen

PULIDO-ROJAS*, Camilo Andrés; MOLINA-VILLA, Manuel Alejandro  y  SOLAQUE-GUZMAN, Leonardo Enrique. Machine vision system for weed detection using image filtering in vegetables crops. Rev.fac.ing.univ. Antioquia [online]. 2016, n.80, pp.124-130. ISSN 0120-6230.  https://doi.org/10.17533/udea.redin.n80a13.

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.

Palabras clave : Weed detection; machine vision; weed removal; discriminate crop.

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