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Application of Neural Networks to Morphological Assessment in Bovine Livestock

  • Horacio M. González-Velasco
  • Carlos J. García-Orellana
  • Miguel Macías-Macías
  • Ramón Gallardo-Caballero
  • Antonio García-Manso
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 363)

Abstract

In conservation and improvement programs of bovine livestock, an important parameter is morphological assessment, which consist of scoring an animal attending to its morphology, and is always performed by highly-qualified staff.

We present in this paper a system designed to help in morphological assessment, providing a score based on a lateral image of the cow. The system consist of two main parts. First, a feature extractor stage is used to reduce the information of the cow in the image to a set of parameters (describing the shape of the profile of the cow). For this stage, a model of the object is constructed by means of point distribution models (PDM), and later that model is used in the searching process within each image, that is carried out using genetic algorithms (GAs). Second, the parameters obtained are used in the following stage, where a multilayer perceptron is trained in order to provide the desired assessment, using the scores given by experts for selected cows.

The system has been tested with 124 images corresponding to 44 individuals of a special rustic breed, with very promising results, taking into account that the information contained in only one view of the cow is not complete.

Keywords

Genetic Algorithm Mean Square Error Global Score Multilayer Perceptron Lateral Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© International Federation for Information Processing 2011

Authors and Affiliations

  • Horacio M. González-Velasco
    • 1
  • Carlos J. García-Orellana
    • 1
  • Miguel Macías-Macías
    • 1
  • Ramón Gallardo-Caballero
    • 1
  • Antonio García-Manso
    • 1
  1. 1.CAPI Research Group Politechnic SchoolUniversity of ExtremaduraCáceresSpain

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