Automatic ore image segmentation using mean shift and watershed transform

Date
2011
Authors
Amankwah A.
Aldrich C.
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
In this paper, we present a novel method for segmenting ore images specifically for estimating the size distribution of ore material on conveyer belt. The segmentation system uses the mean shift and watershed algorithm. The mean shift algorithm is used to identify pixel clusters of particular modes of the probability density function of the image data. The pixel clusters are then used to generate markers for the watershed transform and shadow areas in ore image. Experimental results show that the proposed algorithm is not only faster than the standard methods but also more robust. © 2011 IEEE.
Description
Keywords
Mean Shift, Ore size distribution estimation, Watershed Transform, Conveyer belts, Image data, Mean shift, Mean shift algorithm, Novel methods, Ore material, Segmentation system, Standard method, Water-shed algorithm, Watershed Transform, Belt conveyors, Clustering algorithms, Landforms, Ores, Pixels, Probability density function, Size distribution, Watersheds, Image segmentation
Citation
Proceedings of 21st International Conference, Radioelektronika 2011
http://www.scopus.com/inward/record.url?eid=2-s2.0-79960738600&partnerID=40&md5=b69dfff3d404f7c646ce07ec9134da8a
URI
http://hdl.handle.net/10019.1/16703
Collections
Stellenbosch University - Scopus Publications