Tscharke, M. J. and Banhazi, T. M. (2011) Growth recorded automatically and continuously by a machine vision system for finisher pigs. In: SEAg 2011: Diverse Challenges, Innovative Solutions, 28-30 Sep 2011, Gold Coast, Australia.
Conventional weighing methods in the livestock industries require direct contact with the animal. Due to this contact, conventional weighing methods are both physically demanding and hazardous for those involved. Alternatively the live weight of an animal can be estimated from its body dimensions using non-invasive methods. This paper presents the recent improvements in the ongoing development of a completely automatic, two dimensional computer vision system, designed to obtain critical dimensions of the body of pigs in order to estimate their live weight. Results from validation trials (comparing conventional livestock weighing results and the results generated by the vision-based system) are reported for pigs in their 'finisher' stage. Currently average group weights are predicted with ± 0.7 kg precision under commercial farm conditions. Recording the continuous live weight change of livestock (growth) is important as it can be used to measure the animal’s response to various factors such as the surrounding climate, housing environment and nutrition. Assessing the animal’s response to these conditions is essential in improving the efficiency and welfare of livestock in both research and commercial settings.
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|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Item Status:||Live Archive|
|Additional Information:||Publisher does not formally support archiving.|
|Faculty / Department / School:||Historic - Faculty of Engineering and Surveying - No Department|
|Date Deposited:||05 Mar 2012 02:06|
|Last Modified:||15 Jan 2014 05:45|
|Uncontrolled Keywords:||machine vision; livestock; pigs; allometry; computer vision; PLF; weight; image analysis; growth rate|
|Fields of Research :||07 Agricultural and Veterinary Sciences > 0702 Animal Production > 070203 Animal Management
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
09 Engineering > 0999 Other Engineering > 099901 Agricultural Engineering
|Socio-Economic Objective:||E Expanding Knowledge > 97 Expanding Knowledge > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences|
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