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    Estimation of particulate fines on conveyor belts by use of wavelets and morphological image processing

    Access Status
    Fulltext not available
    Authors
    Amankwah, A.
    Aldrich, Chris
    Date
    2011
    Type
    Journal Article
    
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    Citation
    Amankwah, A. and Aldrich, C. 2011. Estimation of particulate fines on conveyor belts by use of wavelets and morphological image processing. International Journal of Machine Learning and Computing. 1 (2): pp. 132-137.
    Source Title
    International Journal of Machine Learning and Computing
    ISSN
    2010-3700
    URI
    http://hdl.handle.net/20.500.11937/46851
    Collection
    • Curtin Research Publications
    Abstract

    Estimation of the amount of fines in images of mineral particles using standard segmentation approaches is difficult. In this paper, an approach based on multivariate image analysis is presented for estimation of the amount of fines in particles on conveyor belts. The approach is based on two-level wavelet decomposition and morphological image operations, followed by feature extraction from gray level co-occurrence matrices. These features could be used with a simple k nearest neighbour model to estimate the proportion of fines in particulate images. Experimental results with coal and iron ore particles show that the performance of the method can yield better results than those achievable with standard methods.

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