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

Authors

  • Camilo Andrés Pulido-Rojas Universidad Militar Nueva Granada
  • Manuel Alejandro Molina-Villa Universidad Militar Nueva Granada
  • Leonardo Enrique Solaque-Guzmán Universidad Militar Nueva Granada

DOI:

https://doi.org/10.17533/udea.redin.n80a13

Keywords:

Weed detection, machine vision, weed removal, discriminate crop

Abstract


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, Universidad Militar Nueva Granada

Grupo de investigación GIDAM, Facultad de Ingeniería

Manuel Alejandro Molina-Villa, Universidad Militar Nueva Granada

Grupo de investigación GIDAM, Facultad de Ingeniería

Leonardo Enrique Solaque-Guzmán, Universidad Militar Nueva Granada

Grupo de investigación GIDAM, Facultad de Ingeniería

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Published

2016-09-15

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. https://doi.org/10.17533/udea.redin.n80a13

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