Abstract
This paper shows a potential use of scale space for statistical validation of watershed regions of a greyscale image. The watershed segmentation has difficulty in distinguishing valid watershed regions associated with real structures of the image from invalid random regions due to background noise. In this paper, a hierarchy of watershed regions is established by following merging process of the regions in a Gaussian scale space. The distribution of annihilation scales (lives) of the regional minima is investigated to statistically judge the regions as being valid or not. Recursive validation using the hierarchy prevents oversegmentation due to the randomness.
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Sakai, T., Imiya, A. (2009). Validation of Watershed Regions by Scale-Space Statistics. In: Tai, XC., Mørken, K., Lysaker, M., Lie, KA. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2009. Lecture Notes in Computer Science, vol 5567. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02256-2_15
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DOI: https://doi.org/10.1007/978-3-642-02256-2_15
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