PRELIMINARY STUDY FOR THE IMPLEMENTATION OFAN IMAGE ANALYSIS ALGORITHM TO DETECT DAIRY COW PRESENCE AT THE FEED BARRIER

  • Simona M.C. Porto | siporto@unict.it Department of Agri-Food and Environmental Systems Management, Section: Building and Land Engineering, Italy.
  • Claudia Arcidiacono Department of Agri-Food and Environmental Systems Management, Section: Building and Land Engineering, Italy.
  • Giuseppe C. Guarnera University of Catania, Department of Mathematics and Informatics, Italy.
  • Giovanni Cascone Department of Agri-Food and Environmental Systems Management, Section: Building and Land Engineering, Italy.

Abstract

The objective of this study was to investigate the applicability of the Viola-Jones algorithm for continuous detection of the feeding behaviour of dairy cows housed in an open free-stall barn. A methodology was proposed in order to train, test and validate the classifier. A lower number of positive and negative images than those used by Viola and Jones were required during the training. The testing produced the following results: hit rate of about 97.85%, missed rate of about 2.15%, and false positive rate of about 0.67%. The validation was carried out by an accuracy assessment procedure which required the time-consuming work of an operator who labelled the true position of the cows within the barn and their behaviours. The accuracy assessment revealed that among the 715 frames about 90.63% contained only true positives, whereas about 9.37% were affected by underestimation, i.e., contained also one or two false negatives. False positives occurred only in 2.93% of the analyzed frames. Though a moderate mismatch between the testing and the validation performances was registered, the results obtained revealed the adequacy of the Viola-Jones algorithm for detecting the feeding behaviour of dairy cows housed in open free-stall barns. This, in turn, opens up opportunities for an automatic analysis of cow behaviour.

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Published
2012-06-22
Section
Original Articles
Keywords:
precision livestock farming, dairy farming, vision techniques, animal detection.
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How to Cite
Porto, S. M., Arcidiacono, C., Guarnera, G. C., & Cascone, G. (2012). PRELIMINARY STUDY FOR THE IMPLEMENTATION OFAN IMAGE ANALYSIS ALGORITHM TO DETECT DAIRY COW PRESENCE AT THE FEED BARRIER. Journal of Agricultural Engineering, 42(4), 17-24. https://doi.org/10.4081/jae.2011.4.17