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RESEARCH ARTICLE
Contents Vol 46(7)

Using machine vision classification to control access of animals to water

N. A. Finch A C , P. J. Murray A C , M. T. Dunn B and J. Billingsley B
+ Author Affiliations
- Author Affiliations

A School of Animal Studies, The University of Queensland, Gatton, Qld 4343, Australia.

B Faculty of Engineering and Surveying, The University of Southern Queensland, Toowoomba, Qld 4350, Australia.

C Corresponding author. Email: naf@sas.uq.edu.au or peter.murray@.uq.edu.au

Australian Journal of Experimental Agriculture 46(7) 837-839 https://doi.org/10.1071/EA05325
Submitted: 5 December 2005  Accepted: 6 April 2006   Published: 8 June 2006

Abstract

Invasive vertebrate pests together with overabundant native species cause significant economic and environmental damage in the Australian rangelands. Access to artificial watering points, created for the pastoral industry, has been a major factor in the spread and survival of these pests. Existing methods of controlling watering points are mechanical and cannot discriminate between target species. This paper describes an intelligent system of controlling watering points based on machine vision technology. Initial test results clearly demonstrate proof of concept for machine vision in this application. These initial experiments were carried out as part of a 3-year project using machine vision software to manage all large vertebrates in the Australian rangelands. Concurrent work is testing the use of automated gates and innovative laneway and enclosure design. The system will have application in any habitat throughout the world where a resource is limited and can be enclosed for the management of livestock or wildlife.

Additional keywords: classification, livestock management, machine vision, vertebrate pests.


Acknowledgments

These experiments were carried out as part of a 3-year project, funded by the Commonwealth Department of Agriculture, Fisheries and Forestry (Natural Heritage Trust) using machine vision software to manage large vertebrates in the Australian rangelands.


References


Braysher M (1993) ‘Managing vertebrate pests: principles and strategies.’ (Australian Government Publishing Service: Canberra)

Cheffins R (1988) ‘Cattle trapping and self mustering.’ (Queensland Department of Primary Industries: Brisbane)

Choquenot D , McIlroy J , Korn T , Bomford M (1996) ‘Managing vertebrate pests: feral pigs.’ (Australian Government Publishing Service: Canberra)

Connelly P , Horrocks D , Pahl L , Waman K (2000) ‘Cost effective and multipurpose self-mustering enclosures for stock.’ (Department of Primary Industries: Brisbane)

Dunn M , Billingsley J , Finch N (2003) ‘Machine vision classification of animals. Mechatronics and machine vision 2003: future trends.’ (Research Studies Press Ltd: Baldock, UK)

Great Artesian Basin Consultative Council (2000) Strategic Management Plan. Available at http://www.gabcc.org.au/ (verified 19 April 2006)

Grigg G (2002) Conservation benefit from harvesting kangaroos: status report at the start of a new millennium. In ‘A zoological revolution. Using native fauna to assist in its own survival’. (Ed. D Lunney, C Dickman) pp. 53–76. (Royal Zoological Society of New South Wales: Mosman, NSW)

Parkes J , Henzell R , Pickles G , Bomford M (1996) ‘Managing vertebrate pests: feral goats.’ (Australian Government Publishing Service: Canberra)