Machine vision for animal identification

Dunn, Mark (2007) Machine vision for animal identification. Technical Report. University of Southern Queensland , Toowoomba, Australia. [Report]

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Abstract

In the Great Artesian Basin there has been a program of capping bores and piping water to control points. Access to water can therefore be controlled for feral and native animals as well as farmed livestock. While National Livestock Identification Scheme (NLIS) tags are becoming common, the use of machine vision to identify animals based on their shape
allows control of water access for species not commonly tagged.


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Item Type: Report (Technical Report)
Item Status: Live Archive
Additional Information: USQ publication.
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: 19 Sep 2013 00:10
Last Modified: 19 Sep 2013 00:10
Uncontrolled Keywords: water supplies; identifying animals; tagged animals; feral; native species; Australia; outdoor cameras
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0702 Animal Production > 070203 Animal Management
09 Engineering > 0906 Electrical and Electronic Engineering > 090605 Photodetectors, Optical Sensors and Solar Cells
07 Agricultural and Veterinary Sciences > 0799 Other Agricultural and Veterinary Sciences > 079901 Agricultural Hydrology (Drainage, Flooding, Irrigation, Quality, etc.)
Fields of Research (2020): 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3003 Animal production > 300302 Animal management
40 ENGINEERING > 4009 Electronics, sensors and digital hardware > 400999 Electronics, sensors and digital hardware not elsewhere classified
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300201 Agricultural hydrology
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
URI: http://eprints.usq.edu.au/id/eprint/23350

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