Machine vision system for weed detection using image filtering in vegetables crops


  • Camilo Andrés Pulido-Rojas Militar University of New Granada
  • Manuel Alejandro Molina-Villa Militar University of New Granada
  • Leonardo Enrique Solaque-Guzmán Militar University of New Granada



weed detection, machine vision, weed removal, discriminate crop


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.

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Author Biographies

Camilo Andrés Pulido-Rojas, Militar University of New Granada

GIDAM Research Group, Faculty of Engineering.

Manuel Alejandro Molina-Villa, Militar University of New Granada

GIDAM Research Group, Faculty of Engineering.

Leonardo Enrique Solaque-Guzmán, Militar University of New Granada

GIDAM Research Group, Faculty of Engineering.


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How to Cite

Pulido-Rojas, C. A., Molina-Villa, M. A., & Solaque-Guzmán, L. E. (2016). Machine vision system for weed detection using image filtering in vegetables crops. Revista Facultad De Ingeniería Universidad De Antioquia, (80), 124–130.

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