Viewpoint analysis for maturity classification of sweet peppers

Ben Harel, Rick van Essen, Yisrael Parmet, Yael Edan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The effect of camera viewpoint and fruit orientation on the performance of a sweet pepper maturity level classification algorithm was evaluated. Image datasets of sweet peppers harvested from a commercial greenhouse were collected using two different methods, resulting in 789 RGB—Red Green Blue (images acquired in a photocell) and 417 RGB-D—Red Green Blue-Depth (images acquired by a robotic arm in the laboratory), which are published as part of this paper. Maturity level classification was performed using a random forest algorithm. Classifications of maturity level from different camera viewpoints, using a combination of viewpoints, and different fruit orientations on the plant were evaluated and compared to manual classification. Results revealed that: (1) the bottom viewpoint is the best single viewpoint for maturity level classification accuracy; (2) information from two viewpoints increases the classification by 25 and 15 percent compared to a single viewpoint for red and yellow peppers, respectively, and (3) classification performance is highly dependent on the fruit’s orientation on the plant.

Original languageEnglish
Article number3783
Pages (from-to)1-22
Number of pages22
JournalSensors
Volume20
Issue number13
DOIs
StatePublished - 1 Jul 2020

Keywords

  • Camera position
  • Machine vision
  • Maturity classification
  • Sweet pepper
  • Viewpoint analysis

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