30 September 2011 Automatic estimation of rock particulate size on conveyer belt using image analysis
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Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 82851E (2011) https://doi.org/10.1117/12.913415
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt
Abstract
Image segmentation is an important and difficult step for automatic rock particle size distribution estimation. In this paper, we propose a method for the segmentation rock images in a machine vision system using the Voronoi diagram. Typically, rock edge detection is achieved using the watershed transform. Marker-driven watershed segmentation extracts seeds indicating the presence of rocks at specific image locations. The marker locations are then set to be regional minima within the topological surface, which is normally the gradient or thresholds of the original input image. In contrast, our approach uses the generalized Voronoi diagram through Euclidian distance transform for the segmentation of the rock image after extracting the markers. In order to avoid the difficult step of segmentation, we also investigate an image-classification system for rock particulate size estimation using two-level wavelet decomposition. Experimental results show that using the Voronoi diagram is not only more robust than watershed for rock particulate size estimation but also less computationally complex. The Voronoi diagram and watershed methods are superior to the image classification method.
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Anthony Amankwah, Anthony Amankwah, Chris Aldrich, Chris Aldrich, } "Automatic estimation of rock particulate size on conveyer belt using image analysis", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82851E (30 September 2011); doi: 10.1117/12.913415; https://doi.org/10.1117/12.913415
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