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    Real-time hyperspectral processing for automatic nonferrous material sorting

    Identifiers
    URI: http://hdl.handle.net/11556/195
    ISSN: 1017-9909
    DOI: 10.1117/1.JEI.21.1.013018
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    Author/s
    Picon, Artzai; Ghita, Ovidiu; Bereciartua, Arantza; Echazarra, Jone; Whelan, PF; [et al.]
    Date
    2012
    Keywords
    TEXTURE ANALYSIS
    Scrap Identification
    Abstract
    The application of hyperspectral sensors in the development of machine vision solutions has become increasingly popular as the spectral characteristics of the imaged materials are better modeled in the hyperspectral domain than in the standard trichromatic red, green, blue data. While there is no doubt that the availability of detailed spectral information is opportune as it opens the possibility to construct robust image descriptors, it also raises a substantial challenge when this high-dimensional data is used in the development of real-time machine vision systems. To alleviate the computational demand, often decorrelation techniques are commonly applied prior to feature extraction. While this approach has reduced to some extent the size of the spectral descriptor, data decorrelation alone proved insufficient in attaining real-time classification. This fact is particularly apparent when pixel-wise image descriptors are not sufficiently robust to model the spectral characteristics of ...
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