Abstract
Individual identification in pigs is a key point for management. Many behaviors such as resting, activity, feeding and drinking are better to be monitored individually. The purpose of this work was to investigate feasibility of an automated method to identify marked pigs in a pen in experimental conditions and for behavior-related research by using image processing.
First, ellipse fitting algorithms were employed to localize pigs. Second, individual pigs could be identified by their respective paint pattern using pattern recognition techniques. In total, pigs could be identified with an average accuracy of 89.4%. It was also shown that behaviors such as resting can be monitored using the presented technique.
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References
Prakash, A., Stigler, M.: FAO Statistical Yearbook. Food and Agriculture Organization of the United Nations (2012), http://faostat.fao.org/
Harris, P.J., Schaare, P.N., Cook, C.J., Henderson, J.D.: An ambulatory physiological monitor for animal welfare studies. Computers and Electronics in Agriculture 32(3), 181–194 (2001)
Prola, L., Perona, G., Tursi, M., Mussa, P.P.: Use of injectable transponders for the identification and traceability of pigs. Italian Journal of Animal Science 9(2), 183–186 (2010)
Hernandez-Jover, M., Schembri, N., Toribio, J., Holyoake, P.: Biosecurity risks associated with current identification practices of producers trading live pigs at livestock sales. Animal 2(11), 1692–1699 (2008)
Leslie, E., Hernandez-Jover, M., Newman, R., Holyoake, P.: Assessment of acute pain experienced by piglets from ear tagging, ear notching and intraperitoneal injectable transponders. Applied Animal Behaviour Science 127(3-4), 86–95 (2010)
Perner, P.: Motion Tracking of Animals for Behavior Analysis. In: Arcelli, C., Cordella, L.P., Sanniti di Baja, G. (eds.) IWVF 2001. LNCS, vol. 2059, pp. 779–786. Springer, Heidelberg (2001)
Zhang, D., Lu, G.: Review of shape representation and description techniques. Pattern Recognition 37(1), 1–19 (2004)
Zhang, D.: Image Retrieval Based on Shape. PhD Thesis, Faculty of Information Technology, Monash University (2002)
Zhang, Y., Wu, L.: A Rotation Invariant Image Descriptor based on Radon Transform. International Journal of Digital Content Technology and its Applications 5(4), 209–217 (2011)
Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation, rotation, and scale-invariant image registration. IEEE Transactions on Image Processing 5(8), 1266–1271 (1996)
Sherrier, R.H., Johnson, G.: Regionally Adaptive Histogram Equalization of the Chest. IEEE Transactions on Medical Imaging 6(1), 1–7 (1987)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)
Zhang, G., Jayas, D.S., White, N.D.G.: Separation of Touching Grain Kernels in an Image by Ellipse Fitting Algorithm. Biosystems Engineering 92(2), 135–142 (2005)
Kunttu, I., Lepistö, L., Rauhamaa, J., Visa, A.: Color fourier descriptor for defect image retrieval. In: Roli, F., Vitulano, S. (eds.) ICIAP 2005. LNCS, vol. 3617, pp. 415–422. Springer, Heidelberg (2005)
Pradhan, R., Kumar, S., Agarwal, R., Pradhan, M.P., Ghose, M.K.: Contour Line Tracing Algorithm for Digital Topographic Maps. International Journal of Image Processing (IJIP) 4(2), 156–163 (2010)
Casanovas, C.: Basic needs of the growing pig (2009), http://www.pig333.com/management/basic-needs-of-the-growing-pig_1640/
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Kashiha, M.A. et al. (2013). Automatic Identification of Marked Pigs in a Pen Using Image Pattern Recognition. In: Sanches, J.M., Micó, L., Cardoso, J.S. (eds) Pattern Recognition and Image Analysis. IbPRIA 2013. Lecture Notes in Computer Science, vol 7887. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38628-2_24
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DOI: https://doi.org/10.1007/978-3-642-38628-2_24
Publisher Name: Springer, Berlin, Heidelberg
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