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Proceedings Paper

Discriminating poultry feeds by image analysis for the purpose of avoiding importunate poultry behaviors
Author(s): Rabie Hachemi; Nicolas Loménie; Nicole Vincent
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Paper Abstract

The feed manufacturers can control the composition of feed in relation to their feed value. But, in practice, an important issue is still pending: the poultries can reject a batch of feed with optimal nutritional characteristics. This rejection is often accompanied by undesirable and incomprehensible reactions (e.g. pecks in multiple directions) leading to negative consequences for the animal as well as the poultry breeder and the firm. Zootechnical studies are dealing with two main research areas: modeling the poultry feeding behavior and linking it with the poultry perception, especially vision. Currently, a study is undertaken to define the poultry feeding behavior and to point out feeds corresponding to different reactions. As for the perception, visual aspects of feed seem to be involved. While the objective of the study is to make it possible to control the visual quality of feed according to animal behavior, the goal of the present work is to discriminate between feeds of different firms based on visual features extracted from feed images. This discrimination by visual features could be linked with the poultry feeding behaviour and be an effective foundation for the control of the feed acceptability by visual aspects. In this paper, we assess the relevance of color and texture features and we show how these features are involved in the discrimination process between feed images.

Paper Details

Date Published: 3 February 2009
PDF: 8 pages
Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 725106 (3 February 2009); doi: 10.1117/12.806006
Show Author Affiliations
Rabie Hachemi, Univ. Paris Descartes (France)
Nicolas Loménie, Univ. Paris Descartes (France)
Nicole Vincent, Univ. Paris Descartes (France)

Published in SPIE Proceedings Vol. 7251:
Image Processing: Machine Vision Applications II
Kurt S. Niel; David Fofi, Editor(s)

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