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Complementary texture and intensity gradient estimation and fusion for watershed segmentation

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Abstract

In this paper, we identify two current challenges associated with watershed segmentation algorithms which attempt to fuse the visual cues of texture and intensity. The first challenge is that most existing techniques use a competing gradient set which does not allow boundaries to be defined in terms of both visual cues. The second challenge is that these techniques fail to account for the spatial uncertainty inherent in texture gradients. We present a watershed segmentation algorithm which provides a suitable solution to both these challenges and minimises the spatial uncertainty in boundary localisation. This is achieved by a novel fusion algorithm which uses morphological dilation to integrate intensity and texture gradients. A quantitative and qualitative evaluation of results is provided demonstrating that our algorithm outperforms three existing watershed algorithms.

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Authors and Affiliations

  1. Department of Computer Science, National Centre for Geocomputation, National University of Ireland Maynooth, Kildare, Ireland

    Padraig Corcoran, Adam Winstanley & Peter Mooney

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  1. Padraig Corcoran
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  2. Adam Winstanley
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  3. Peter Mooney
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Correspondence to Padraig Corcoran.

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Corcoran, P., Winstanley, A. & Mooney, P. Complementary texture and intensity gradient estimation and fusion for watershed segmentation. Machine Vision and Applications 22, 1027–1045 (2011). https://doi.org/10.1007/s00138-010-0310-z

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  • DOI: https://doi.org/10.1007/s00138-010-0310-z

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