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  • Illumination independent object recognition

    Author(s)
    Lovell, Nathan
    Griffith University Author(s)
    Lovell, Nathan H.
    Year published
    2006
    Metadata
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    Abstract
    Object recognition under uncontrolled illumination conditions remains one of hardest problems in machine vision. Under known lighting parameters, it is a simple task to calculate a transformation that maps sensed values to the expected colors in objects (and minimize the problems of reflections and/or texture). However, RoboCup aims to develop vision systems for natural lighting conditions in which the conditions are not only unknown but also dynamic. This makes fixed color-based image segmentation infeasible. We present a method for color determination under varying illumination conditions that succeeds in tracking the ...
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    Object recognition under uncontrolled illumination conditions remains one of hardest problems in machine vision. Under known lighting parameters, it is a simple task to calculate a transformation that maps sensed values to the expected colors in objects (and minimize the problems of reflections and/or texture). However, RoboCup aims to develop vision systems for natural lighting conditions in which the conditions are not only unknown but also dynamic. This makes fixed color-based image segmentation infeasible. We present a method for color determination under varying illumination conditions that succeeds in tracking the objects of interest in the RoboCup legged league.
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    Journal Title
    Lecture Notes in Computer science
    Volume
    40
    Issue
    20
    DOI
    https://doi.org/10.1007/11780519_34
    Subject
    Multi-Disciplinary
    Publication URI
    http://hdl.handle.net/10072/27331
    Collection
    • Journal articles

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