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Improving fruit detection for robotic fruit harvesting
Year:
2009
Source of publication :
Acta Horticulturae
Authors :
Alchanatis, Victor
;
.
Volume :
824
Co-Authors:
Bulanon, D.M., Agricultural and Biological Engineering Department, University of Florida/IFAS, Gainesville, FL, United States
Burks, T.F., Agricultural and Biological Engineering Department, University of Florida/IFAS, Gainesville, FL, United States
Alchanatis, V., ARO-Volcani Center, Bet Dagan, Israel
Facilitators :
From page:
329
To page:
336
(
Total pages:
8
)
Abstract:
One of the challenges of developing a fruit-harvesting robot is fruit detection. Fruit detection in an unstructured environment with variable lighting conditions greatly affecting the robot's harvesting efficiency. This paper presents the enhancement of robotic citrus harvesting by improving fruit recognition and fruit visibility. To detect the fruit, an image processing approach was developed that is robust to outdoor variable illumination and has the ability to detect fruits in cluster and partially occluded fruit. The fruit portion was enhanced by the red chromaticity coefficient and a circle detection method enabled the individual fruits to be classified. To improve fruit visibility, the fruit detection algorithm was combined with a multiple viewing technique that would acquire multiple views of a portion of a tree canopy from different viewing angles. Results showed that by acquiring multiple views, fruit visibility improved from 50% to about 90%. The outcome of this study will be useful for targeting fruits for robotic fruit harvesting.
Note:
Related Files :
Citrus
Image processing
Machine vision
Robotic harvesting
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More details
DOI :
Article number:
Affiliations:
Database:
Scopus
Publication Type:
Conference paper
;
.
Language:
English
Editors' remarks:
ID:
29643
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:48
Scientific Publication
Improving fruit detection for robotic fruit harvesting
824
Bulanon, D.M., Agricultural and Biological Engineering Department, University of Florida/IFAS, Gainesville, FL, United States
Burks, T.F., Agricultural and Biological Engineering Department, University of Florida/IFAS, Gainesville, FL, United States
Alchanatis, V., ARO-Volcani Center, Bet Dagan, Israel
Improving fruit detection for robotic fruit harvesting
One of the challenges of developing a fruit-harvesting robot is fruit detection. Fruit detection in an unstructured environment with variable lighting conditions greatly affecting the robot's harvesting efficiency. This paper presents the enhancement of robotic citrus harvesting by improving fruit recognition and fruit visibility. To detect the fruit, an image processing approach was developed that is robust to outdoor variable illumination and has the ability to detect fruits in cluster and partially occluded fruit. The fruit portion was enhanced by the red chromaticity coefficient and a circle detection method enabled the individual fruits to be classified. To improve fruit visibility, the fruit detection algorithm was combined with a multiple viewing technique that would acquire multiple views of a portion of a tree canopy from different viewing angles. Results showed that by acquiring multiple views, fruit visibility improved from 50% to about 90%. The outcome of this study will be useful for targeting fruits for robotic fruit harvesting.
Scientific Publication
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