Abstract
Mornitoring cow behavior and performance plays an important role in dairy health and welfare management systems. Due to the increased number of elderly farm workers, the demands for automatic cow monitoring system become a key role. Moreover, the image based technology for a mornitoring system is a promising technique because it is relatively low cost and easy to install. In this aspect, the fundamental and important work to be done is to make an identification of individual cows with high accuracy. Thus in this paper, a simple and effective method for cow identification is introduced by using a modified background subtraction method and histogram based decision process. Specifically, the painted-marks are placed on all black-haired cows and video images are taken. Then the marked region is extracted by using the proposed background subtraction method and histogram based features. Finally, the identification process is performed and some experimental results are shown by using self-collected database taken in the University dairy farm.
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© 2016 Springer International Publishing Switzerland
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Sumi, K., Kobayashi, I., Zin, T.T. (2016). Cow Identification by Using Shape Information of Pointed Pattern. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. GEC 2015. Advances in Intelligent Systems and Computing, vol 388. Springer, Cham. https://doi.org/10.1007/978-3-319-23207-2_27
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DOI: https://doi.org/10.1007/978-3-319-23207-2_27
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-319-23207-2
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