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Sweet pepper maturity evaluation via multiple viewpoints color analyses
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel .ORCID iD: 0000-0002-8933-7229
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel . (MRO)ORCID iD: 0000-0003-4685-379x
Proefstation voor de Groenteteelt, Sint-Katelijne-Waver, Belgium .
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel .ORCID iD: 0000-0002-2071-7338
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2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Maturity evaluation is an important feature for selective robotic harvesting. This paper focuses on maturity evaluationderived by a color camera for a sweet pepper robotic harvester. Fruit visibility for sweet peppers is limited to 65% andmultiple viewpoints are necessary to detect more than 90% of the fruit. This paper aims to determine the number ofviewpoints required to determine the maturity level of a sweet pepper and the best single viewpoint. Different colorbased measures to estimate the maturity level of a pepper were evaluated. Two datasets were analyzed: images of 54yellow bell sweet peppers and 30 red peppers both harvested at the last fruit setting; all images were taken in uniformillumination conditions with white background. Each pepper was photographed from 5-6 viewpoints: one photo of thetop of the pepper, one photo of the bottom and 3-4 photos of the pepper sides. Each pepper was manually tagged by ahuman professional observer as ‘mature’ or ‘immature’. Image processing routines were implemented to extract colorlevel measures which included different hue features. Results indicates high correlation between the sides to the bottomview, the bottom view shows the best 0.86 correlation in the case of yellow peppers while the side view shows the best0.835 correlation in the case of red peppers (the bottom view yields 0.82 correlation).

Place, publisher, year, edition, pages
2016. p. 1-7
National Category
Agricultural Science
Identifiers
URN: urn:nbn:se:oru:diva-79410OAI: oai:DiVA.org:oru-79410DiVA, id: diva2:1388678
Conference
CIGR-AgEng Conference, Aarhus, Denmark, 26-29 June, 2016
Available from: 2020-01-27 Created: 2020-01-27 Last updated: 2020-01-28

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Kurtser, Polina

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Harel, BenKurtser, PolinaParmet, YisraelEdan, Yael
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CiteExportLink to record
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Citation style
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