Crop row detection in maize fields inspired on the human visual perception

Romeo Granados, Juan and Pajares Martinsanz, Gonzalo and Montalvo Martínez, Martín and Guerrero Hernández, José Miguel and Guijarro Mata-García, María and Ribeiro Seijas, Ángela (2012). Crop row detection in maize fields inspired on the human visual perception. "The Scientific World Journal", v. 2012 ; pp. 484390-484398. ISSN 1537-744X. https://doi.org/10.1100/2012/484390.

Description

Title: Crop row detection in maize fields inspired on the human visual perception
Author/s:
  • Romeo Granados, Juan
  • Pajares Martinsanz, Gonzalo
  • Montalvo Martínez, Martín
  • Guerrero Hernández, José Miguel
  • Guijarro Mata-García, María
  • Ribeiro Seijas, Ángela
Item Type: Article
Título de Revista/Publicación: The Scientific World Journal
Date: 2012
ISSN: 1537-744X
Volume: 2012
Subjects:
Faculty: Centro de Automática y Robótica (CAR) UPM-CSIC
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection.

More information

Item ID: 21255
DC Identifier: http://oa.upm.es/21255/
OAI Identifier: oai:oa.upm.es:21255
DOI: 10.1100/2012/484390
Official URL: http://www.hindawi.com/journals/tswj/2012/484390/
Deposited by: Memoria Investigacion
Deposited on: 06 Nov 2013 20:17
Last Modified: 24 Feb 2017 17:47
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