A machine vision system using a laser radar applied to robotic fruit harvesting

A. R. Jiménez*, R. Ceres, Jose L Pons

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

This paper describes a new laser-based computer vision system used for automatic fruit recognition. Most relevant vision studies for fruit harvesting are reviewed. Our system is based on an infrared laser-range finder sensor generating range and reflectance images and it is designed to detect spherical objects in non-structured environments. A special image restoration technique is defined and applied to improve image quality. Image analysis algorithms integrate both range and reflectance information to generate four characteristic primitives evidencing the presence of spherical objects. This machine vision system, which generates the 3-D location, radio and surface reflectivity of each spherical object has been applied to the AGRIBOT orange fruit harvester robot. Test results indicate good correct detection rates, unlikely false alarms and a robust behavior.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE Workshop on Computer Vision Beyond the Visible Spectrum
Subtitle of host publicationMethods and Applications, CVBVS 1999
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages110-119
Number of pages10
ISBN (Electronic)0769500501, 9780769500508
DOIs
StatePublished - 1999
Event1st IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, CVBVS 1999 - Fort Collins, United States
Duration: Jun 21 1999Jun 22 1999

Publication series

NameProceedings - IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, CVBVS 1999

Conference

Conference1st IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications, CVBVS 1999
CountryUnited States
CityFort Collins
Period6/21/996/22/99

ASJC Scopus subject areas

  • Instrumentation
  • Computer Vision and Pattern Recognition
  • Signal Processing

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