Beef identification in industrial slaughterhouses using machine vision techniques
Abstract
Accurate individual animal identification provides the producers with useful information to take management decisions about an individual animal or about the complete herd. This identification task is also important to ensure the integrity of the food chain. Consequently, many consumers are turning their attention to issues of quality in animal food production methods. This work describes an implemented solution for individual beef identification, taking in the time from cattle shipment arrival at the slaughterhouse until the animals are slaughtered and cut up. Our beef identification approach is image-based and the pursued goals are the correct automatic extraction and matching between some numeric information extracted from the beef ear-tag and the corresponding one from the Bovine Identification Document (BID). The achieved correct identification results by our method are near 90%, by considering the practical working conditions of slaughterhouses (i.e. problems with dirt and bad illumination conditions). Moreover, the presence of multiple machinery in industrial slaughterhouses make it difficult the use of Radio Frequency Identification (RFID) beef tags due to the high risks of interferences between RFID and the other technologies in the workplace. The solution presented is hardware/software since it includes a specialized hardware system that was also developed. Our approach considers the current EU legislation for beef traceability and it reduces the economic cost of individual beef identification with respect to RFID transponders. The system implemented has been in use satisfactorily for more than three years in one of the largest industrial slaughterhouses in Spain.Downloads
References
Ahrendt P, Gregersen T, Karstoft H, 2011. Development of a real-time computer vision system for tracking loose-housed pigs. Comput Electron Agric 76(2): 169-174. http://dx.doi.org/10.1016/j.compag.2011.01.011
Allen A, Golden B, Taylor M, Patterson D, Henriksen D, Skuce R, 2008. Evaluation of retinal imaging technology for the biometric identification of bovine animals in Northern Ireland. Livest Sci 116(1-3): 42-52. http://dx.doi.org/10.1016/j.livsci.2007.08.018
Bowling MB, Pendell DL, Morris DL, Yoon Y, Katoh K, Belk KE, Smith G.C, 2008. Identification and traceability of cattle in selected countries outside of North America. Prof Anim Sci 24: 287-294.
Dalvit C, De Marchi M, Cassandro M, 2007. Genetic traceability of livestock products: A review. Meat Sci 77(4): 437-449. http://dx.doi.org/10.1016/j.meatsci.2007.05.027 PMid:22061927
EC, 1997. Council Regulation (EC) No 820/97 of 21 April 1997 establishing a system for the identification and registration of bovine animals and regarding the labelling of beef and beef products. Available in http://eur-lex.europa.eu/smartapi/cgi/sga_doc?smartapi!celexapi!prod!CELEXnumdoc&numdoc=31997R0820&model=guichett&lg=en [1 October 2013].
EC, 2000. Regulation (EC) No. 1760/2000 of the European Parliament and of the Council of 17 July 2000 establishing a system for the identification and registration of bovine animals and regarding the labelling of beef and beef products and repealing Council Regulation (EC) No 820/97. Available in http://eur-lex.europa.eu/smartapi/cgi/sga_doc?smartapi!celexapi!prod!CELEXnumdoc&lg=EN&numdoc=32000R1760&model=guichett [1 October 2013].
EC, 2011. Working paper for amendment of Regulation (EC) No. 1760/2000, electronic identification of bovine animals and deleting the provisions on voluntary beef labelling. Available in http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=SEC:2011:1008:FIN:EN:PDF [1 October 2013].
Evans J, Van Eenennaam A, 2005. Livestock identification. Emerging management systems in animal identification. Fact Sheet #5. University of California Corporative Extension. Available in: http://animalscience.ucdavis.edu/animalID/ [1 March 2013].
Fowler M, Scott K, 2003. UML distilled: a brief guide to the standard object modeling language, 3rd Ed. Addison-Wesley, Reading, USA. 220 pp.
Gonzalez RC, Woods RE, 2008. Digital image processing, 3rd Ed. Prentice Hall. Upper Saddle River, USA. 954 pp.
ICAR, 2009. A synthesis of ICAR guidelines on animal identification. International Committee for Animal Recording. Animal Identification Sub-Committee. Available in: http://www.icar.org/Documents/Animal_Identification_applications/Extract%20Animal%20Identification.pdf [1 March 2013].
IPSA, 2003. Traceability of cattle using radio frequency identification. Investigación y Programas, S.A. Working Document, Madrid, 15 pp. [In Spanish].
IPSA, 2011. Atril: Software for document capture, management and transformation. Investigación y Programas, S.A. Available in: http://www.ipsa.es/en/cloud-paper/atril, Madrid [1 March 2013].
Keilthy L, 2008. Measuring automatic number plate recognition (ANPR) system performance. Parking Trend Int. Available in: http://www.videopeoplecounter.com/brochures/Measuring%20ANPR%20System%20Performance.pdf [1 March 2013].
Marchant J, 2002. Secure animal identification and source verification. Whitepaper, Optibrand Ltd., Ft. Collins, CO, USA.
McKean, JD, 2001. The importance of traceability for public health and and consumer protection. Rev Sci Tech Off Int Epizoot 20(2): 363-371.
Rossig W, 1999. Animal identification: Introduction and history. Comput Electron Agr 24(1-2): 1-4. http://dx.doi.org/10.1016/S0168-1699(99)00033-2
Schroeder TC, Tonsor GT, 2012. International cattle ID and traceability: Competitive implications for the US. Food Policy 37(1): 31–40. http://dx.doi.org/10.1016/j.foodpol.2011.10.005
Scottish Government, 2008. Effect of acoustic/mechanical interference on radio frequency identity (RFID) systems used to identify animals electronically. Available in: http://www.scotland.gov.uk/Publications/2008/07/24102700/0[1 March 2013].
Shanahan C, Kernan B, Ayalew G., McDonnell K, Butler F, Ward S, 2009. A framework for beef traceability from farm to slaughter using global standards: An Irish perspective. Comput Electron Agr 66(1): 62-69. http://dx.doi.org/10.1016/j.compag.2008.12.002
Simeone P, Marrocco C, Tortorella F, 2011. Shaping the error-reject curve of error correcting output coding systems. Proc 16 Int Conf on Image Analysis and Processing, Ravenna (Italy), Sep 14-16, pp: 118-127.
Trier OD, Jain AK, Taxt T, 1996. Feature extraction methods for character recognition: A survey. Pattern Recogn 29(4): 641–662. http://dx.doi.org/10.1016/0031-3203(95)00118-2
Tse D, Viswanath P, 2005. Fundamentals of wireless communication. Cambridge Univ Press, UK. 564 pp. http://dx.doi.org/10.1017/CBO9780511807213
Voulodimos AS, Patrikakis CZ, Sideridis AB, Ntafis VA, Xylouri EM, 2010. A complete farm management system based on animal identification using RIFD technology. Comput Electron Agr 70(2): 380-388. http://dx.doi.org/10.1016/j.compag.2009.07.009
© CSIC. Manuscripts published in both the printed and online versions of this Journal are the property of Consejo Superior de Investigaciones Científicas, and quoting this source is a requirement for any partial or full reproduction.
All contents of this electronic edition, except where otherwise noted, are distributed under a “Creative Commons Attribution 4.0 International” (CC BY 4.0) License. You may read here the basic information and the legal text of the license. The indication of the CC BY 4.0 License must be expressly stated in this way when necessary.
Self-archiving in repositories, personal webpages or similar, of any version other than the published by the Editor, is not allowed.
