Scale-Space Theory in Computer Vision

First International Conference, Scale-Space '97, Utrecht, The Netherlands, July 2 - 4, 1997, Proceedings

By: Bart ter Haar Romeny (Editor), Luc Florack (Editor), Jan Koenderink (Editor)

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Paperback | 18 June 1997

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384 Pages

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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.

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Non-Fiction Computing & I.T.Computer Science Image Processing Artificial Intelligence Computer Vision Mathematics Geometry Graphical & Digital Media Applications Digital Signal Processing (DSP)Engineering & Technology Electronics & Communications Engineering

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A review of nonlinear diffusion filtering	p. 3
Scale-space versus topographic map for natural images	p. 29
On generalized entropies and scale-space	p. 53
On the duality of scalar and density flows	p. 65
Invertible orientation bundles on 2D scalar images	p. 77
Generating stable structure using scale-space analysis with non-uniform Gaussian kernels	p. 89
Generic events for the gradient squared with application to multi-scale segmentation	p. 101
Linear spatio-temporal scale-space	p. 113
On the handling of spatial and temporal scales in feature tracking	p. 128
Following feature lines across scale	p. 140
A multi-scale line filter with automatic scale selection based on the Hessian matrix for medical image segmentation	p. 152
Supervised diffusion parameter selection for filtering SPECT brain images	p. 164
Image loci are ridges in geometric spaces	p. 176
Multiscale measures in linear scale-space for characterizing cerebral functional activations in 3D PET difference images	p. 188
Scale space analysis by stabilized inverse diffusion equations	p. 200
Intrinsic scale space for images on surfaces: The geodesic curvature flow	p. 212
Multi-spectral probabilistic diffusion using Bayesian classification	p. 224
From high energy physics to low level vision	p. 236
Dynamic scale-space theories	p. 248
Recursive separable schemes for nonlinear diffusion filters	p. 260
Level set methods and the stereo problem	p. 272
Reliable classification of chrysanthemum leaves through curvature scale space	p. 284
Multi-scale contour segmentation	p. 296
Reconstruction of self-semilar functions from scale-space	p. 311
Multi-scale detection of characteristic figure structures using principal curvatures of image gray-level profile	p. 315
A new framework for hierarchical segmentation using similarity analysis	p. 319
Robust anisotropic diffusion: connections between robust statistics, line processing, and anisotropic diffusion	p. 323
Fast adaptive alternatives to nonlinear diffusion in image enhancement: Green's function approximators and nonlocal filters	p. 327
A scale-space approach to shape similarity	p. 333
Multi-scale active shape description	p. 337
Scale-space filters and their robustness	p. 341
Directional anisotropic diffusion applied to segmentation of vessels in 3D images	p. 345
3D shape representation: transforming polygons into voxels	p. 349
Extraction of a structure feature from three-dimensional objects by scale-space analysis	p. 353
Slowed anisotropic diffusion	p. 357
Thin nets extraction using a multi-scale approach	p. 361
Author Index	p. 365
Table of Contents provided by Blackwell. All Rights Reserved.

Scale-Space Theory in Computer Vision

First International Conference, Scale-Space '97, Utrecht, The Netherlands, July 2 - 4, 1997, Proceedings

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