Automatic Monitoring of Pig Activity Using Image Analysis

Mohammad Amin Kashiha, Claudia Bahr, Sanne Ott, Christel Moons, Theo Niewold, Frank Tuyttens, Daniel Berckmans

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureC1: Artikels in proceedings van wetenschappelijke congressen, die niet inbegrepen zijn in A1, A2, A3 of P1peer review

    Uittreksel

    The purpose of this study is to investigate the feasibility and validity
    of an automated image processing method to detect the activity status of pigs.
    Top-view video images were captured for forty piglets, housed ten per pen.
    Each pen was monitored by a top-view CCD camera. The image analysis
    protocol to automatically quantify activity consisted of several steps. First, in
    order to localise the pigs, ellipse fitting algorithms were employed.
    Subsequently, activity was calculated by subtracting image background and
    comparing binarised images. To validate the results, they were compared to
    labelled behavioural data ('active' versus 'inactive'). This is the first study to
    show that activity status of pigs in a group can be determined using image
    analysis with an accuracy of 89.8 %. Since activity status is known to be
    associated with issues such as lameness, careful monitoring can give an
    accurate indication of the health and welfare of pigs.
    Oorspronkelijke taalEngels
    TitelAdvanced Concepts for Intelligent Vision Systems : Proceedings of the 15th International Conference
    EditorsJacques Blanc-Talon, Andrzej Kasinski, Wilfried Philips, Dan Popescu, Paul Scheunders
    Aantal pagina’s9
    UitgeverijSpringer
    Publicatiedatum2013
    Pagina's555-563
    ISBN van geprinte versie978-3-319-02894-1
    ISBN van elektronische versie978-3-319-02895-8
    PublicatiestatusGepubliceerd - 2013
    EvenementAdvanced Concepts for Intelligent Vision Systems - Poznan, Polen
    Duur: 28-okt-201331-okt-2013

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