Field testing of vision based macadamia yield monitoring

Dunn, Mark and Billingsley, John ORCID: https://orcid.org/0000-0002-7198-5594 and Bell, David (2005) Field testing of vision based macadamia yield monitoring. In: 12th Annual Conference on Mechatronics and Machine Vision in Practice, 29 Nov - 1 Dec 2005, Manila, Phillipines.

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Abstract

[Abstract]: Algorithms for visually identifying macadamia nuts in real time have been previously reported in (Dunn and Billingsley, 2003). This paper describes field trials on that system, with the additional tasks of integrating GPS and visual tree location. It describes a full working prototype harvester equipped with three cameras counting nuts, one camera mounted transversely logging in-field position by identifying individual trees, a ground speed radar and a Differential GPS receiver. With this system, individual nuts are identified and logged to a position in the field accurate to the nearest 10cm. This allows full yield mapping of the orchard to the individual tree level.

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Item Type:	Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed:	Yes
Item Status:	Live Archive
Additional Information:	Author retains copyright. Full conference proceedings held in disk format in USQ Library at call no. AV 629.89 Con.
Faculty/School / Institute/Centre:	Historic - Faculty of Engineering and Surveying - No Department (Up to 30 Jun 2013)
Faculty/School / Institute/Centre:	Historic - Faculty of Engineering and Surveying - No Department (Up to 30 Jun 2013)
Date Deposited:	11 Oct 2007 00:58
Last Modified:	02 Jul 2013 22:42
Uncontrolled Keywords:	machine vision, data fusion, localisation
Fields of Research (2008):	08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision 09 Engineering > 0906 Electrical and Electronic Engineering > 090602 Control Systems, Robotics and Automation 09 Engineering > 0910 Manufacturing Engineering > 091007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)
URI:	http://eprints.usq.edu.au/id/eprint/2156

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