Abstract
In this work the relation between scale-space image segmentation and selection of the localization scale is examined first, and a scale selection approach is consequently proposed in the segmentation context. Considering the segmentation part, gradient watersheds are applied to the non-linear scale-space domain followed by a grouping operation. A report on localization scale selection techniques is carried out next. Furthermore a scale selection method that originates from the evolution of the probability distribution of a region uniformity measure through the generated scales is proposed. The introduced algorithm is finally compared to a previously published approach that is also introduced into the segmentation context to indicate its efficacy.
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Makrogiannis, S., Bourbakis, N. (2005). Localization Scale Selection for Scale-Space Segmentation. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_1
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DOI: https://doi.org/10.1007/11559573_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
Online ISBN: 978-3-540-31938-2
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