Jiang, Xiaoyi; Marti, Cyril; Irniger, Christophe; Bunke, Horst (2006). Distance measures for image segmentation evaluation. EURASIP journal on applied signal processing, 2006(1), pp. 1-11. Akron, Ohio: Hindawi Publ. 10.1155/ASP/2006/35909
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The task considered in this paper is performance evaluation of region segmentation algorithms in the ground-truth-based paradigm. Given a machine segmentation and a ground-truth segmentation, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in image processing. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
08 Faculty of Science > Institute of Computer Science (INF) |
UniBE Contributor: |
Bunke, Horst |
ISSN: |
1110-8657 |
Publisher: |
Hindawi Publ. |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 14:45 |
Last Modified: |
05 Dec 2022 14:13 |
Publisher DOI: |
10.1155/ASP/2006/35909 |
Web of Science ID: |
000242074700001 |
BORIS DOI: |
10.7892/boris.18488 |
URI: |
https://boris.unibe.ch/id/eprint/18488 (FactScience: 634) |
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