Robust multi-scale extraction of blob features

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Abstract

This paper presents a method for detection of homogeneous regions in grey-scale images, representing them as blobs. In order to be fast, and not to favour one scale over others, the method uses a scale pyramid. In contrast to most multi-scale methods this one is non-linear, since it employs robust estimation rather than averaging to move through scale-space. This has the advantage that adjacent and partially overlapping clusters only affect each other's shape, not each other's values. It even allows blobs within blobs, to provide a pyramid blob structure of the image. © Springer-Verlag 2003.

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Forssén, P. E., & Granlund, G. (2003). Robust multi-scale extraction of blob features. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2749, 11–18. https://doi.org/10.1007/3-540-45103-x_3

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