Overview

We perceive objects in the world as having structures at both coarse and fine scales. A tree, for instance, may appear as having a roughly round or cylindrical shape when seen from a distance, even though it is built up from a large number of branches. At a closer look, individual leaves become visible, and we can observe that they in turn have texture at an even finer scale. The fact that objects in the world appear in different ways, depending upon the scale of observation, has important implications when analyzing measured data, such as images, with automatic methods. Scale-Space Theory in Computer Vision describes a formal framework, called scale-space representation, for handling the notion of scale in image data. It gives an introduction to the general foundations of the theory and shows how it applies to essential problems in computer vision such as computation of image features and cues to surface shape. The subjects range from mathematical underpinning to practical computational techniques. The power of the methodology is illustrated by a rich set of examples.

Full Product Details

Author:   Tony Lindeberg
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   Softcover reprint of hardcover 1st ed. 1994
Volume:   256
Dimensions:   Width: 15.50cm , Height: 2.20cm , Length: 23.50cm
Weight:   0.676kg
ISBN:  

9781441951397

ISBN 10:   1441951393
Pages:   424
Publication Date:   02 December 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock  
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

1 Introduction and overview.- 2 Linear scale-space and related multi-scale representations.- 3 Scale-space for 1-D discrete signals.- 4 Scale-space for N-D discrete signals.- 5 Discrete derivative approximations with scale-space properties.- 6 Feature detection in scale-space.- 7 The scale-space primal sketch.- 8 Behaviour of image structures in scale-space: Deep structure.- 9 Algorithm for computing the scale-space primal sketch.- 10 Detecting salient blob-like image structures and their scales.- 11 Guiding early visual processing with qualitative scale and region information.- 12 Summary and discussion.- 13 Scale selection for differential operators.- 14 Direct computation of shape cues by scale-space operations.- 15 Non-uniform smoothing.- A Technical details.- A.1 Implementing scale-space smoothing.- A.2 Polynomials satisfying the diffusion equation.

Reviews

' This approach will certainly turn out to be part of the foundations of the theory and practice of machine vision ... the author has no doubt performed an excellent service to many in the field of both artificial and biological vision. ' Jan Koenderink

` This approach will certainly turn out to be part of the foundations of the theory and practice of machine vision ... the author has no doubt performed an excellent service to many in the field of both artificial and biological vision. ' Jan Koenderink

' This approach will certainly turn out to be part of the foundations of the theory and practice of machine vision ... the author has no doubt performed an excellent service to many in the field of both artificial and biological vision. ' Jan Koenderink

' This approach will certainly turn out to be part of the foundations of the theory and practice of machine vision ... the author has no doubt performed an excellent service to many in the field of both artificial and biological vision. ' Jan Koenderink

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