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- W2125895360 abstract "In an ordinary 2D image the critical points and the isophotes through the saddle points provide sufficient information for classifying the image into distinct regions belonging to the extrema (i.e. a collection of bright and dark blobs), together with their nesting due to the saddle isophotes. For scale space images, obtained by convolution of the image with a Gaussian filter at a continuous range of widths for the Gaussian, things are more complicated. Here only scale space saddle points occur. They are related to spatial saddle points and spatial extrema and can thus provide a scale space based segmentation and hierarchy. However, a spatial extremum can be related to multiple scale space saddles. The key to solve this ambiguity is the investigation of both the scale space saddles and the iso-intensity manifolds (the extension of isophotes in scale space) through them. I will describe the different situations that one can encounter in this investigation, which scale space saddles are relevant, give examples and show the difference between selecting the relevant and the non-relevant (“void”) scale space saddles." @default.
- W2125895360 created "2016-06-24" @default.
- W2125895360 creator A5046597105 @default.
- W2125895360 date "2003-01-01" @default.
- W2125895360 modified "2023-09-23" @default.
- W2125895360 title "On Manifolds in Gaussian Scale Space" @default.
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- W2125895360 doi "https://doi.org/10.1007/3-540-44935-3_1" @default.
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