A Pyramid Framework for Early Vision

Multiresolutional Computer Vision

  • Jean-Michel Jolion
  • Azriel Rosenfeld

Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 251)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Jean-Michel Jolion, Azriel Rosenfeld
    Pages 1-5
  3. Jean-Michel Jolion, Azriel Rosenfeld
    Pages 6-61
  4. Jean-Michel Jolion, Azriel Rosenfeld
    Pages 62-169
  5. Jean-Michel Jolion, Azriel Rosenfeld
    Pages 170-186
  6. Back Matter
    Pages 187-218

About this book

Introduction

Biological visual systems employ massively parallel processing to perform real-world visual tasks in real time. A key to this remarkable performance seems to be that biological systems construct representations of their visual image data at multiple scales. A Pyramid Framework for Early Vision describes a multiscale, or `pyramid', approach to vision, including its theoretical foundations, a set of pyramid-based modules for image processing, object detection, texture discrimination, contour detection and processing, feature detection and description, and motion detection and tracking. It also shows how these modules can be implemented very efficiently on hypercube-connected processor networks.
A Pyramid Framework for Early Vision is intended for both students of vision and vision system designers; it provides a general approach to vision systems design as well as a set of robust, efficient vision modules.

Keywords

DEX Processing Rack Tracking architecture boundary element method design form network networks object parallel processing presentation set time

Editors and affiliations

  • Jean-Michel Jolion
    • 1
  • Azriel Rosenfeld
    • 2
  1. 1.University Claude BernardLyon 1France
  2. 2.University of MarylandCollege ParkUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-2792-3
  • Copyright Information Kluwer Academic Publishers 1994
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6207-4
  • Online ISBN 978-1-4615-2792-3
  • Series Print ISSN 0893-3405
  • About this book