Machine vision-based motion estimation of flotation froth using mutual information

The motion estimation of froths in the flotation of minerals is difficult due to the effects of bubble deformation, bursting and merging making it difficult for the traditional machine vision methods to estimate the froth velocity. In this paper, we propose a new method for the motion estimation of...

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Main Authors: Amankwah, A., Aldrich, Chris
Format: Conference Paper
Published: 2011
Online Access:http://hdl.handle.net/20.500.11937/22072
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author Amankwah, A.
Aldrich, Chris
author_facet Amankwah, A.
Aldrich, Chris
author_sort Amankwah, A.
building Curtin Institutional Repository
collection Online Access
description The motion estimation of froths in the flotation of minerals is difficult due to the effects of bubble deformation, bursting and merging making it difficult for the traditional machine vision methods to estimate the froth velocity. In this paper, we propose a new method for the motion estimation of flotation froth using mutual information with a bin size of two (MI2) as the block matching metric. Experimental results show that the proposed motion estimation technique improves the motion estimation accuracy in terms of peak signal-to-noise ratio of the reconstructed frame. The computational cost of the proposed method is almost the same as the standard machine vision methods used for the motion estimation of flotation froth.
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format Conference Paper
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institution Curtin University Malaysia
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last_indexed 2025-11-14T07:42:04Z
publishDate 2011
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spelling curtin-20.500.11937-220722017-09-13T13:53:07Z Machine vision-based motion estimation of flotation froth using mutual information Amankwah, A. Aldrich, Chris The motion estimation of froths in the flotation of minerals is difficult due to the effects of bubble deformation, bursting and merging making it difficult for the traditional machine vision methods to estimate the froth velocity. In this paper, we propose a new method for the motion estimation of flotation froth using mutual information with a bin size of two (MI2) as the block matching metric. Experimental results show that the proposed motion estimation technique improves the motion estimation accuracy in terms of peak signal-to-noise ratio of the reconstructed frame. The computational cost of the proposed method is almost the same as the standard machine vision methods used for the motion estimation of flotation froth. 2011 Conference Paper http://hdl.handle.net/20.500.11937/22072 10.2316/P.2011.752-060 restricted
spellingShingle Amankwah, A.
Aldrich, Chris
Machine vision-based motion estimation of flotation froth using mutual information
title Machine vision-based motion estimation of flotation froth using mutual information
title_full Machine vision-based motion estimation of flotation froth using mutual information
title_fullStr Machine vision-based motion estimation of flotation froth using mutual information
title_full_unstemmed Machine vision-based motion estimation of flotation froth using mutual information
title_short Machine vision-based motion estimation of flotation froth using mutual information
title_sort machine vision-based motion estimation of flotation froth using mutual information
url http://hdl.handle.net/20.500.11937/22072