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Scale-Space Theory in Computer Vision

Overview of attention for book
Cover of 'Scale-Space Theory in Computer Vision'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 37 A review of nonlinear diffusion filtering
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    Chapter 38 Scale space versus topographic map for natural images
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    Chapter 39 On generalized entropies and scale-space
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    Chapter 40 On the duality of scalar and density flows
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    Chapter 41 Invertible orientation bundles on 2D scalar images
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    Chapter 42 Generating stable structure using Scale-space analysis with non-uniform Gaussian kernels
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    Chapter 43 Generic events for the gradient squared with application to multi-scale segmentation
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    Chapter 44 Linear spatio-temporal scale-space
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    Chapter 45 On the handling of spatial and temporal scales in feature tracking
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    Chapter 46 Following feature lines across scale
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    Chapter 47 A multi-scale line filter with automatic scale selection based on the Hessian matrix for medical image segmentation
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    Chapter 48 Supervised diffusion parameter selection for filtering SPECT brain images
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    Chapter 49 Image loci are ridges in geometric spaces
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    Chapter 50 Multiscale measures in linear scale-space for characterizing cerebral functional activations in 3D PET difference images
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    Chapter 51 Scale space analysis by stabilized inverse diffusion equations
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    Chapter 52 Intrinsic scale space for images on surfaces: The geodesic curvature flow
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    Chapter 53 Multi-spectral probabilistic diffusion using bayesian classification
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    Chapter 54 From high energy physics to low level vision
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    Chapter 55 Dynamic scale-space theories
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    Chapter 56 Recursive separable schemes for nonlinear diffusion filters
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    Chapter 57 Level set methods and the stereo problem
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    Chapter 58 Reliable classification of chrysanthemum leaves through Curvature Scale Space
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    Chapter 59 Multi-scale contour segmentation
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    Chapter 60 Reconstruction of self-similar functions from scale-space
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    Chapter 61 Multi-scale detection of characteristic figure structures using principal curvatures of image gray-level profile
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    Chapter 62 A new framework for hierarchical segmentation using similarity analysis
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    Chapter 63 Robust anisotropic diffusion: Connections between robust statistics, line processing, and anisotropic diffusion
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    Chapter 64 Fast adaptive alternatives to nonlinear diffusion in image enhancement: Green's function approximators and nonlocal filters
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    Chapter 65 A scale-space approach to shape similarity
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    Chapter 66 Multi-scale active shape description
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    Chapter 67 Scale-space filters and their robustness
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    Chapter 68 Directional anisotropic diffusion applied to segmentation of vessels in 3D images
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    Chapter 69 3D shape representation: Transforming polygons into voxels
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    Chapter 70 Extraction of a structure feature from three-dimensional objects by scale-space analysis
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    Chapter 71 Slowed anisotropic diffusion
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    Chapter 72 Thin nets extraction using a multi-scale approach
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Mentioned by

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Title
Scale-Space Theory in Computer Vision
Published by
Lecture notes in computer science, January 1997
DOI 10.1007/3-540-63167-4
ISBNs
978-3-54-063167-5, 978-3-54-069196-9
Authors

Bart Haar Romeny, Luc Florack, Jan Koenderink, Max Viergever

Editors

Haar Romeny, Bart, Florack, Luc, Koenderink, Jan, Viergever, Max

Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 June 2017.
All research outputs
#7,459,393
of 22,805,349 outputs
Outputs from Lecture notes in computer science
#2,487
of 8,126 outputs
Outputs of similar age
#19,769
of 91,561 outputs
Outputs of similar age from Lecture notes in computer science
#9
of 20 outputs
Altmetric has tracked 22,805,349 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% of its peers.
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We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.