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Apple detection in natural tree canopies from multimodal images
Year:
2009
Authors :
Alchanatis, Victor
;
.
Volume :
Co-Authors:
Wachs, J.P., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Bet-Dagan, Israel, Dept. of Industrial Engineering, Ben-Gurion University of the Negev, Israel
Stern, H.I., Dept. of Industrial Engineering, Ben-Gurion University of the Negev, Israel
Burks, T., Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 110570, United States
Alchanatis, V., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Bet-Dagan, Israel
Facilitators :
From page:
293
To page:
301
(
Total pages:
9
)
Abstract:
In this work we develop a real time system that recognizes occluded green apples within a tree canopy using infra-red and color images in order to achieve automated harvesting. Infra-red provides clues regarding the physical structure and location of the apples based on their temperature (leaves accumulate less heat and radiate faster than apples), while color images provide evidence of circular shape. Initially the optimal registration parameters are obtained using maximization of mutual information. Haar features are then applied separately to color and infra-red images through a process called Boosting, to detect apples from the background. A contribution reported in this work, is the voting scheme added to the output of the RGB Haar detector which reduces false alarms without affecting the recognition rate. The resulting classifiers alone can partially recognize the on-trees apples however when combined together the recognition accuracy is increased.
Note:
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More details
DOI :
Article number:
Affiliations:
Database:
Scopus
Publication Type:
Conference paper
;
.
Language:
English
Editors' remarks:
ID:
29248
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:45
Scientific Publication
Apple detection in natural tree canopies from multimodal images
Wachs, J.P., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Bet-Dagan, Israel, Dept. of Industrial Engineering, Ben-Gurion University of the Negev, Israel
Stern, H.I., Dept. of Industrial Engineering, Ben-Gurion University of the Negev, Israel
Burks, T., Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 110570, United States
Alchanatis, V., Institute of Agricultural Engineering, Agricultural Research Organization, Volcani Center, Bet-Dagan, Israel
Apple detection in natural tree canopies from multimodal images
In this work we develop a real time system that recognizes occluded green apples within a tree canopy using infra-red and color images in order to achieve automated harvesting. Infra-red provides clues regarding the physical structure and location of the apples based on their temperature (leaves accumulate less heat and radiate faster than apples), while color images provide evidence of circular shape. Initially the optimal registration parameters are obtained using maximization of mutual information. Haar features are then applied separately to color and infra-red images through a process called Boosting, to detect apples from the background. A contribution reported in this work, is the voting scheme added to the output of the RGB Haar detector which reduces false alarms without affecting the recognition rate. The resulting classifiers alone can partially recognize the on-trees apples however when combined together the recognition accuracy is increased.
Scientific Publication
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