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

Romeo Granados, Juan; Pajares Martinsanz, Gonzalo; Montalvo Martínez, Martín; Guerrero Hernández, José Miguel; Guijarro Mata-García, María y 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.

Descripción

Título: Crop row detection in maize fields inspired on the human visual perception
Autor/es:
  • Romeo Granados, Juan
  • Pajares Martinsanz, Gonzalo
  • Montalvo Martínez, Martín
  • Guerrero Hernández, José Miguel
  • Guijarro Mata-García, María
  • Ribeiro Seijas, Ángela
Tipo de Documento: Artículo
Título de Revista/Publicación: The Scientific World Journal
Fecha: 2012
Volumen: 2012
Materias:
Escuela: Centro de Automática y Robótica (CAR) UPM-CSIC
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 21255
Identificador DC: http://oa.upm.es/21255/
Identificador OAI: oai:oa.upm.es:21255
Identificador DOI: 10.1100/2012/484390
URL Oficial: http://www.hindawi.com/journals/tswj/2012/484390/
Depositado por: Memoria Investigacion
Depositado el: 06 Nov 2013 20:17
Ultima Modificación: 24 Feb 2017 17:47
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