Digital image processing methods for the identification of pigs posture during weight estimation

Ferdous, W. M. and Tscharke, M. and Saunders, C. and Lee, S.-H. and Banhazi, T. M. (2011) Digital image processing methods for the identification of pigs posture during weight estimation. In: 5th European Conference on Precision Livestock Farming (ECPLF 2011), 11-14 July 2011, Prague .

Abstract

Variations in the postures of pigs can contribute to significant amounts of error during automatic weight estimation of pigs using image analysis techniques. This is especially the case when the head of a pig is not maintained on the same straight line as the body of the animal. It was estimated that an additional 2.4% error is associated with sub-optimal posture of animals during weight estimation. To minimize weight estimation error as much as possible, the aim of this study was to identify the most suitable image analysis technique that can automatically select frames from video streams with optimum animal posture for accurate weight estimation. Four different techniques, namely reference line, length ratio, angular width and mid-line methods were investigated using images of pigs between 45 and 90 kg. All images were taken from above the animals at a height of 1680 mm. In this study, images of animals turning their heads more than 30 degrees from the body line either left or right were classified as suboptimal. Similarly, images were also classified as suboptimal if the angular placement of the pigs in the images were more than 30 degrees from the midline. Among the different methods, both the length ratio and angular width method were found to be most likely to identify images with suboptimal head position, while the midline method was the best at identifying pigs with a suboptimal body position. Thus overall the length ratio method appears to be the best to identify suboptimal images before further processing.


Statistics for USQ ePrint 20094
Statistics for this ePrint Item
Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Author version not held.
Depositing User: Dr Thomas Banhazi
Faculty / Department / School: Current - USQ Other
Date Deposited: 13 Mar 2012 00:16
Last Modified: 03 Jul 2013 00:53
Uncontrolled Keywords: Image analysis, posture, head turning, livestock, pig
Fields of Research (FOR2008): 09 Engineering > 0999 Other Engineering > 099901 Agricultural Engineering
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
URI: http://eprints.usq.edu.au/id/eprint/20094

Actions (login required)

View Item Archive Repository Staff Only