Discrete region competition for unknown numbers of connected regions
We present a discrete, unsupervised multi-region competition algorithm for image segmentation over different energy functionals. The number of regions present in an image does not need to be known a priori, nor their photometric properties. The algorithm jointly estimates the number of regions, thei...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 21(2012), 8 vom: 21. Aug., Seite 3531-45 |
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| Weitere Verfasser: | , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2012
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Zusammenfassung: | We present a discrete, unsupervised multi-region competition algorithm for image segmentation over different energy functionals. The number of regions present in an image does not need to be known a priori, nor their photometric properties. The algorithm jointly estimates the number of regions, their photometries, and their contours. The required regularization is provided by defining a region as a connected set of pixels. The evolving contours in the image are represented by computational particles that move as driven by an energy-minimization algorithm. We present an efficient discrete algorithm that allows minimizing a range of well-known energy functionals under the topological constraint of regions being connected components. The presented framework and algorithms are implemented in the open-source Insight Toolkit (ITK) image-processing library |
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| Beschreibung: | Date Completed 07.04.2014 Date Revised 06.09.2013 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1941-0042 |
| DOI: | 10.1109/TIP.2012.2192129 |