Abstract
Image segmentation can be roughly presented as the grouping of individual image pixels into (meaningful/useful) partition of regions or objects. It is an important area common to a number of research fields such as image processing, computer vision and machine learning. Although a number of algorithms and approaches have been proposed, automated image segmentation continues to be a tantalizing and challenging problem. In this paper, we look at image segmentation as an inference problem and describe the Statistical Region Merging technique (Nock et al; 2004). We will further apply the technique in the segmentation of CT images.
Original language | English |
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Title of host publication | Proceedings of the 49th ANZIAM Conference Newcastle, New South Wales 3–7 February 2013 |
Editors | David Allingham, Roslyn Hickson, Bishnu Lamichhane, Mike Meylan |
Place of Publication | Newcastle, NSW |
Publisher | Australian Mathematical Society Australian and New Zealand Industrial and Applied Mathematics |
Pages | 73-74 |
Number of pages | 2 |
ISBN (Print) | 978-0-9873276-1-1 |
Publication status | Published - 3 Feb 2013 |
Event | ANZIAM Conference 2013 - Newcastle, Australia Duration: 3 Feb 2013 → 7 Feb 2013 Conference number: 49th |
Conference
Conference | ANZIAM Conference 2013 |
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Country/Territory | Australia |
City | Newcastle |
Period | 3/02/13 → 7/02/13 |