Estimation of particulate fines on conveyor belts by use of wavelets and morphological image processing
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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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Estimating size fraction categories of coal particles on conveyor belts using image texture modeling methodsJemwa, G.; Aldrich, Chris (2012)Motivation: Physical properties of coal such as particle size distribution have a large influence on the stability and operational behavior of fluidized bed reactors and metallurgical furnaces. In particular, the presence ...
Estimation of particulate fines on conveyor belts by use of wavelets and morphological image processingAmankwah, A.; Aldrich, Chris (2011)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 ...
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