Banhazi, T. M. and Tscharke, M. and Ferdous, W. M. and Saunders, C. and Lee, S.-H. (2011) Improved image analysis based system to reliably predict the live weight of pigs on farm: preliminary results. Australian Journal of Multi-Disciplinary Engineering , 8 (2). pp. 107-119. ISSN 1448-8388
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A computer vision system was developed to automatically measure the live weight of pigs without human intervention. The system was trialled on both research and commercial farms to demonstrate the ability of the system to cope with different conditions and non-uniform lighting conditions. Early results demonstrate that the system can achieve sufficient practical accuracy. The results of the initial trials demonstrated that weight of the pigs can be predicted with an average error of 1.18 kg. Precision, reliability and repeatability are likely to be increased in future through improved weight prediction models, increased image resolution and algorithm enhancement.
|Item Type:||Article (Commonwealth Reporting Category C)|
|Additional Information:||Permanent restricted access to published version due to publisher copyright policy. © The Institution of Engineers Australia, 2011.|
|Uncontrolled Keywords:||image analysis; body composition; swine; pigs; weight; farm produce|
|Fields of Research (FOR2008):||08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision|
07 Agricultural and Veterinary Sciences > 0702 Animal Production > 070203 Animal Management
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
|Socio-Economic Objective (SEO2008):||B Ecomonic Development > 83 Animal Production and Animal Primary Products > 8303 Livestock Raising > 830308 Pigs|
|Deposited On:||13 Mar 2012 14:07|
|Last Modified:||07 Jun 2012 12:04|
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