Weight estimation using image analysis and statistical modelling: a preliminary study

Kollis, K. and Phang, C. S. and Banhazi, Thomas and Searle, Stephen J. (2007) Weight estimation using image analysis and statistical modelling: a preliminary study. Applied Engineering in Agriculture, 23 (1). pp. 91-96. ISSN 0883-8542

Abstract

The weighing of pigs on a farm is traditionally performed manually, making the process time-consuming and laborious. An automated weighing system could thus greatly improve the efficiency of the weighing process. Former studies have demonstrated that an animal's weight may be estimated via analysis of an image of that animal. A recent study conducted at the University of Adelaide aimed to implement an automatic weight estimation system for pigs, and use this system to confirm the results of previous studies while investigating new features, such as additional statistical modelling. A system was designed and implemented using off-the-shelf hardware. It was found that the system was able to estimate a pig's weight with an acceptable error.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to published version due to publisher copyright policy.
Depositing User: epEditor USQ
Faculty / Department / School: Current - USQ Other
Date Deposited: 17 May 2011 08:46
Last Modified: 03 Jul 2013 00:37
Uncontrolled Keywords: image processing; pigs; precision livestock farming; weight estimation
Fields of Research (FOR2008): 07 Agricultural and Veterinary Sciences > 0702 Animal Production > 070202 Animal Growth and Development
09 Engineering > 0999 Other Engineering > 099901 Agricultural Engineering
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective (SEO2008): B Economic Development > 91 Economic Framework > 9105 Measurement Standards and Calibration Services > 910501 Agricultural and Environmental Standards
URI: http://eprints.usq.edu.au/id/eprint/18904

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