A fast hierarchical approach to image segmentation
In this paper, we propose a hierarchical approach to image segmentation based on the use of a graph regularisation algorithm. The initial segmentation map is obtained using the normalized cut segmentation algorithm. We then refine the segmentation results by iteratively propagating the class-labels...
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Published in | 2008 19th International Conference on Pattern Recognition pp. 1 - 4 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.12.2008
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Subjects | |
Online Access | Get full text |
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Summary: | In this paper, we propose a hierarchical approach to image segmentation based on the use of a graph regularisation algorithm. The initial segmentation map is obtained using the normalized cut segmentation algorithm. We then refine the segmentation results by iteratively propagating the class-labels from coarse-to-fine sampling levels. Image segmentation at each intermediate level is recast as a constrained graph regularisation problem that can be solved efficiently. The multi-level nature of our method achieves low computational cost and robustness to noise corruption. We provide experimental results on the Berkeley Image Database and show the efficacy of our method for segmentation of high resolution images. |
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ISBN: | 9781424421749 1424421748 |
ISSN: | 1051-4651 2831-7475 |
DOI: | 10.1109/ICPR.2008.4761590 |