Mobile Computational Vision System in the Identification of White Quinoa Quality

Percimil Lecca-Pino, Daniel Tafur-Vera, Michael Cabanillas-Carbonell, José Luis Herrera Salazar, Esteban Medina-Rafaile

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Quinoa is currently in high commercial demand due to its large benefits and vitamin components. The process of selecting this grain is mostly done manually, being prone to errors, because many times this work is subject to fatigue and to subjective criteria of those in charge, causing the quality to decrease due to not making an adequate selection subject to standards. For this reason, a study focused on determining the influence of the computer vision system for the identification of the quality of white quinoa, based on the standards and techniques for the development of a computer vision system through the phases of PDI.

Original languageEnglish
Pages (from-to)436-442
Number of pages7
JournalInternational Journal of Advanced Computer Science and Applications
Volume12
Issue number8
DOIs
StatePublished - 2021

Keywords

  • Computer vision system
  • digital image processing
  • quinoa quality

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