Abstract
A multiscale morphological dilation-erosion smoothing operation and its associated scale-space expansion for multidimensional signals are proposed. Properties of this smoothing operation are developed and, in particular a scale-space monotonie property for signal extrema is demonstrated. Scale-space fingerprints from this approach have advantages over Gaussian scale-space fingerprints in that they are defined for negative values of the scale parameter; have monotonie properties in two and higher dimensions, do not cause features to be shifted by the smoothing, and allow efficient computation. The application of reduced multiscale dilation-erosion fingerprints to the surface matching of terrain is demonstrated.
| Original language | English |
|---|---|
| Pages (from-to) | 38-51 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Pattern Analysis and Machine Intelligence |
| Volume | 18 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1996 |
| Externally published | Yes |
Keywords
- Scale-space filtering, multiscale morphology, signal analysis, monotonie property, scale-space fingerprints
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