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Sweet pepper maturity evaluation

Published online by Cambridge University Press:  01 June 2017

B. Harel ,
P. Kurtser ,
Y. Parmet  and
Y. Edan
B. Harel*
Affiliation:
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
P. Kurtser
Affiliation:
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
Y. Parmet
Affiliation:
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
Y. Edan
Affiliation:
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
*
†E-mail: [email protected]
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Abstract

This paper focuses on maturity evaluation derived by a color camera for a sweet pepper robotic harvester. Different color and morphological features for sweet pepper maturity were evaluated. Side view and bottom view of sweet paper were analyzed and compared for their ability to classify into 4 maturity classes. The goal of this study was to differentiate between the two center classes which are difficult to separate. Statistical analysis of 13 different features in reliance to the maturity classification and the views indicated the best features for classification. The results show that the features that can be used for classification between the two central classes from both bottom and side views are: Hue range, Equal2Real – the ratio between the equivalent equal sized circle perimeter to the shape perimeter and Area2Peri – the ratio between the area to the perimeter.

Keywords

Computer visionFruit maturityRobotic harvestingSweet peppersAgricultural robots
Type
Crop Sensors and Sensing
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 167 - 171
Copyright
© The Animal Consortium 2017 

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