Abstract
This paper discusses the problem of selecting appropriate scales for region detection prior to feature localization. We argue that an approach in morphological opening-closing scale-space is better than one in Gaussian scale-space. The proposed operator is based on a new shape decomposition method called morphological band-pass filter that decomposes an image into structures of different size and different curvature polarity. Local appropriate scale is then defined as the scale that maximizes the response of the band-pass filter at each point. This operator gives constant scale values in a region of constant width, and its zero-crossings coincide with local maxima of the gradient magnitudes. Its usefulness is demonstrated by some examples.
Cite
CITATION STYLE
Köthe, U. (1996). Local appropriate scale in morphological scale-space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1064, pp. 219–228). Springer Verlag. https://doi.org/10.1007/bfb0015538
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