Scale-space theory for computer vision : First International Conference, Scale-Space'97, Utrecht, The Netherlands, July 2 4, 1997 : proceedings
This book constitutes the refereed proceedings of the First International Conference on Scale-Space Theory for Computer Vision, Scale-Space '97, held in Utrecht, The Netherlands, in July 1997. The volume presents 21 revised full papers selected from a total of 41 submissions. Also included are...
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| Format: | Livre numérique |
| Sprache: | Anglais |
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Springer
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| Schriftenreihe: | Lecture notes in computer science
1252 |
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| Edition sous un autre format: | • Scale-space theory for computer vision, First International Conference, Scale-Space '97, Utrecht, The Netherlands, July 2-4, 1997, proceedings, Bart ter Haar Romeny ... [et al.], eds, 1997, New York, Springer, 1 vol. (IX-364 p.), Lecture notes in computer science, 3-540-63167-4 • Scale-Space Theory in Computer Vision, Texte imprimé, 9783662210130 |
Inhaltsangabe:
- A review of nonlinear diffusion filtering
- Scale space versus topographic map for natural images
- On generalized entropies and scale-space
- On the duality of scalar and density flows
- Invertible orientation bundles on 2D scalar images
- Generating stable structure using Scale-space analysis with non-uniform Gaussian kernels
- Generic events for the gradient squared with application to multi-scale segmentation
- Linear spatio-temporal scale-space
- On the handling of spatial and temporal scales in feature tracking
- Following feature lines across scale
- A multi-scale line filter with automatic scale selection based on the Hessian matrix for medical image segmentation
- Supervised diffusion parameter selection for filtering SPECT brain images
- Image loci are ridges in geometric spaces
- Multiscale measures in linear scale-space for characterizing cerebral functional activations in 3D PET difference images
- Scale space analysis by stabilized inverse diffusion equations
- Intrinsic scale space for images on surfaces: The geodesic curvature flow
- Multi-spectral probabilistic diffusion using bayesian classification
- From high energy physics to low level vision
- Dynamic scale-space theories
- Recursive separable schemes for nonlinear diffusion filters
- Level set methods and the stereo problem
- Reliable classification of chrysanthemum leaves through Curvature Scale Space
- Multi-scale contour segmentation
- Reconstruction of self-similar functions from scale-space
- Multi-scale detection of characteristic figure structures using principal curvatures of image gray-level profile
- A new framework for hierarchical segmentation using similarity analysis
- Robust anisotropic diffusion: Connections between robust statistics, line processing, and anisotropic diffusion
- Fast adaptive alternatives to nonlinear diffusion in image enhancement: Green's function approximators and nonlocal filters
- A scale-space approach to shape similarity
- Multi-scale active shape description
- Scale-space filters and their robustness
- Directional anisotropic diffusion applied to segmentation of vessels in 3D images
- 3D shape representation: Transforming polygons into voxels
- Extraction of a structure feature from three-dimensional objects by scale-space analysis
- Slowed anisotropic diffusion
- Thin nets extraction using a multi-scale approach.