Scale-Space Theory in Computer Vision [electronic resource] : First International Conference, Scale-Space '97, Utrecht, The Netherlands, July 2 - 4, 1997, Proceedings /
Scale-Space'97Corporate Author
Scale-Space'97(1997 :Utrecht, Netherlands)
Scale-Space'97
Haar Romeny, Bart ter.editor.
Florack, Luc.editor.
Koenderink, Jan.editor.
Viergever, Max.editor.
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 2 invited papers and 13 poster presentations. This book is the first comprehensive documentation of the application of Scale-Space techniques in computer vision and, in the broader context, in image processing and pattern recognition.
Bibliographic Level Mode of Issuance: Monograph
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.
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 2 invited papers and 13 poster presentations. This book is the first comprehensive documentation of the application of Scale-Space techniques in computer vision and, in the broader context, in image processing and pattern recognition.
Optical data processing.
Signal processing.
Image processing.
Speech processing systems.
Pattern recognition.
Computer graphics.
Image Processing and Computer Vision.
Signal, Image and Speech Processing.
Pattern Recognition.
Computer Graphics.