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Application of ANN techniques to automated identification of bovine livestock

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1607))

Abstract

In this work a classification system is presented that, taking lateral images of cattle as inputs, is able to identify the animals and classify them by breed into previously learnt classes. The system consists of two fundamental parts. In the first one, a deformable-model-based preprocessing of the image is made, in which the contour of the animal in the photograph is sought, extracted, and normalized. Next, a neural classifier is presented that, supplemented with a decision-maker at its output, makes the distribution into classes. In the last part, the results obtained in a real application of this methodology are presented.

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José Mira Juan V. Sánchez-Andrés

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© 1999 Springer-Verlag Berlin Heidelberg

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Velasco, H.M.G., Aligué, F.J.L., Orellana, C.J.G., Macías, M.M., Sotoca, M.I.A. (1999). Application of ANN techniques to automated identification of bovine livestock. In: Mira, J., Sánchez-Andrés, J.V. (eds) Engineering Applications of Bio-Inspired Artificial Neural Networks. IWANN 1999. Lecture Notes in Computer Science, vol 1607. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0100509

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  • DOI: https://doi.org/10.1007/BFb0100509

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66068-2

  • Online ISBN: 978-3-540-48772-2

  • eBook Packages: Springer Book Archive

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