Computer Vision-Based Method for Automatic Detection of Crop Rows in Potato Fields

  • Iván García-Santillán
  • Diego Peluffo-Ordoñez
  • Víctor Caranqui
  • Marco Pusdá
  • Fernando Garrido
  • Pedro Granda
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 721)

Abstract

This work presents an adaptation and validation of a method for automatic crop row detection from images captured in potato fields (Solanum tuberosum) for initial growth stages based on the micro-ROI concept. The crop row detection is a crucial aspect for autonomous guidance of agricultural vehicles and site-specific treatments application. The images were obtained using a color camera installed in the front of a tractor under perspective projection. There are some issues that can affect the quality of the images and the detection procedure, among them: uncontrolled illumination in outdoor agricultural environments, different plant densities, presence of weeds and gaps in the crop rows. The adapted approach was designed to address these adverse situations and it consists of three linked phases. The main contribution is the ability to detect straight and curved crop rows in potato crops. The performance was quantitatively compared against two existing methods, achieving acceptable results in terms of accuracy and processing time.

Keywords

Crop row detection Autonomous guidance Image segmentation Computer vision 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Iván García-Santillán
    • 1
  • Diego Peluffo-Ordoñez
    • 1
  • Víctor Caranqui
    • 1
  • Marco Pusdá
    • 1
  • Fernando Garrido
    • 1
  • Pedro Granda
    • 1
  1. 1.Department of Software Engineering, Faculty of Applied SciencesUniversidad Técnica del NorteIbarraEcuador

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