MULTIREGION GRAPH CUT IMAGE SEGMENTATION

Mohamed Ben Salah, Ismail Ben Ayed, Amar Mitiche

2008

Abstract

The purpose of our study is two-fold: (1) investigate an image segmentation method which combines parametric modeling of the image data and graph cut combinatorial optimization and, (2) use a prior which allows the number of labels/regions to decrease when the number of regions is not known and the algorithm initialized with a larger number. Experimental verification shows that the method results in good segmentations and runs faster than conventional graph cut methods.

References

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Paper Citation


in Harvard Style

Ben Salah M., Ben Ayed I. and Mitiche A. (2008). MULTIREGION GRAPH CUT IMAGE SEGMENTATION . In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 535-538. DOI: 10.5220/0001081605350538


in Bibtex Style

@conference{visapp08,
author={Mohamed Ben Salah and Ismail Ben Ayed and Amar Mitiche},
title={MULTIREGION GRAPH CUT IMAGE SEGMENTATION},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={535-538},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001081605350538},
isbn={978-989-8111-21-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - MULTIREGION GRAPH CUT IMAGE SEGMENTATION
SN - 978-989-8111-21-0
AU - Ben Salah M.
AU - Ben Ayed I.
AU - Mitiche A.
PY - 2008
SP - 535
EP - 538
DO - 10.5220/0001081605350538