A review: Vision systems application on yield mapping

Shirin Ghatrehsamani, Yiannis Amptazidis

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations


This paper surveys the innovative work of vision systems for natural product mapping and confinement for mechanical reaping as well as harvest load estimation of claim to fame tree crops including apples, pears, and citrus. Variable lighting condition, impediments, and bunching are a portion of the essential issues should have been tended to for exact recognition and confinement of organic product in plantation environment. To address these issues, different strategies have been examined utilizing diverse sorts of sensors and their blends and with various picture preparing procedures. This paper abridges different methods and their focal points and burdens in recognizing organic product in plant or tree coverings. The paper additionally compresses the sensors and frameworks created and utilized by scientists to restrict organic product and the potential and constraints of those frameworks. At last, real difficulties for the effective utilization of machine vision framework for mechanical natural product collecting and harvest stack estimation, and potential future bearings for innovative work are talked about.

Original languageEnglish (US)
StatePublished - 2019
Event2019 ASABE Annual International Meeting - Boston, United States
Duration: Jul 7 2019Jul 10 2019


Conference2019 ASABE Annual International Meeting
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Agronomy and Crop Science
  • Bioengineering


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