Fruit localization using artificial vision and shape analysis

Raphael Linker, Eliyahu Kelman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper details a procedure for identifying edges that may belong to three-dimensional convex objects of an approximate size, such as apples, from a much larger set of edges. The identification is achieved by analyzing a number of intensity profiles that originate at each edge and determining whether they have a shape that is suitable with a 3D convex object of the correct size. We show that contrarily to the prevailing opinion, the intensity or luminance functions of three-dimensional convex objects are not necessarily convex, which led us to developing models for describing such profiles. The simplest suitable model includes four parameters that can be easily estimated by a standard constrained least squares optimization procedure. The proposed procedure is applied to images of apple trees recorded in an orchard. The procedure correctly removes 77-100% of the edges not belonging to apples, with minimal loss of edges belonging to such objects.

Original languageEnglish
Title of host publicationAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2011, ASABE 2011
PublisherAmerican Society of Agricultural and Biological Engineers
Pages4244-4256
Number of pages13
ISBN (Print)9781618391568
StatePublished - 2011
EventAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2011 - Louisville, KY, United States
Duration: 7 Aug 201110 Aug 2011

Publication series

NameAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2011, ASABE 2011
Volume5

Conference

ConferenceAmerican Society of Agricultural and Biological Engineers Annual International Meeting 2011
Country/TerritoryUnited States
CityLouisville, KY
Period7/08/1110/08/11

Keywords

  • Contour extraction
  • Fruit detection
  • Shape recognition

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science

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