Overview

A tutorial in multi-scale methods for computer vision and image processing. It builds on the cross-fertilization between human visual perception and multi-scale computer vision (""scale-space"") theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a high-level language for symbolic and numerical manipulations. The book presents a new and effective approach to quickly mastering the mathematics of computer vision and image analysis. The typically short code is given for every topic discussed, and invites the reader to spend many hours ""playing"" with computer vision. The book is intended for undergraduate and graduate students, and all with an interest in computer vision, medical imaging and human visual perception.

Full Product Details

Author:   Bart M. Haar Romeny
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2003 ed.
Volume:   27
Dimensions:   Width: 15.50cm , Height: 2.60cm , Length: 23.50cm
Weight:   1.890kg
ISBN:  

9781402015038

ISBN 10:   1402015038
Pages:   466
Publication Date:   30 September 2003
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Apertures and the notion of scale.- Foundations of scale-space.- The Gaussian kernel.- Gaussian derivatives.- Multi-scale derivatives: implementations.- Differential structure of images.- Natural limits on observations.- Differentiation and regularization.- The front-end visual system — the retina.- A scale-space model for the retinal sampling.- The front-end visual system — LGN and cortex.- The front-end visual system — cortical columns.- Deep structure I. watershed segmentation.- Deep structure II. catastrophe theory.- Deep structure III. topological numbers.- Deblurring Gaussian blur.- Multi-scale optic flow.- Color differential structure.- Steerable kernels.- Scale-time.- Geometry-driven diffusion.- Epilog.

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