Fourier Vision: Segmentation and Velocity Measurement using the Fourier Transform / Edition 1

by David Vernon

Overview

Fourier Vision provides a new treatment of figure-ground segmentation in scenes comprising transparent, translucent, or opaque objects. Exploiting the relative motion between figure and ground, this technique deals explicitly with the separation of additive signals and makes no assumptions about the spatial or spectral content of the images, with segmentation being carried out phasor by phasor in the Fourier domain. It works with several camera configurations, such as camera motion and short-baseline binocular stereo, and performs best on images with small velocities/displacements, typically one to ten pixels per frame. The book also addresses the use of Fourier techniques to estimate stereo disparity and optical flow. Numerous examples are provided throughout.
Fourier Vision will be of value to researchers in image processing & computer vision and, especially, to those who have to deal with superimposed transparent or translucent objects. Researchers in application areas such as medical imaging and acoustic signal processing will also find this of interest.

Product Details

ISBN-13:	9780792374138
Publisher:	Springer US
Publication date:	06/30/2001
Series:	The Springer International Series in Engineering and Computer Science , #623
Edition description:	2001
Pages:	195
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1. Introduction.- 1. Computer Vision.- 2. Overview of the Fourier Vision Approach.- 3. Camera Configurations.- 4. Scope of the Book.- 2. Mathematical Preliminaries.- 1. The 2-D Fourier Transform.- 2. The Hough Transform.- 3. Monocular Vision — Segmentation in Additive Images.- 1. Overview.- 2. The Segmentation Problem.- 3. The Fourier Model of Segmentation.- 4. Application of the Technique.- 5. Conclusion.- 4. Monocular Vision — Segmentation in Occluding Images.- 1. Overview.- 2. Figure-Ground Segmentation of Occluding Translating Objects.- 3. Application of the Technique.- 4. Image Complexity.- 5. Outstanding Issues.- 6. A Sample of Motion/Stereo Segmentation Techniques.- 5. Articulated Binocular Vision.- 1. Motivation.- 2. Overview.- 3. Theoretical Framework.- 6. Fronto-Parallel Binocular Vision.- 1. Formulation of the Problem.- 2. The Computational Model.- 3. Application of the Technique.- 4. Caveat.- 7. Instantaneous Optical Flow.- 1. Motivation.- 2. Velocity from Phase Change.- 3. Examples.- 4. Discussion.- 5. Conclusions.- 6. Postscript: Other Approaches.- 8. Decoupled Optical Flow.- 1. The Problem of Non-Unique Multiple Local Velocities.- 2. Algorithm.- 3. Examples.- 4. Conclusion.- 9. Epilogue.- References.

Editorial Reviews

Fourier and Hough transforms are described in this text as an approach to deal with issues of separation of additive images and segmentation of figure-ground scenes. Vernon (National U. of Ireland, Maynooth) describes the math used in the process then discusses monocular and binocular vision and instantaneous and decoupled optical flow. The text will be of interest to those working with image processing and computer vision, especially when dealing with superimposed transparent or translucent objects. No assumptions are made about the spatial or spectral content of the images; segmentation is carried out phasor by phasor in the Fourier domain. Annotation c. Book News, Inc., Portland, OR (booknews.com)