Foundations of Image Understanding

  • Larry S. Davis

Table of contents

  1. Front Matter
    Pages i-xv
  2. Azriel Rosenfeld
    Pages 1-32
  3. T. Yung Kong
    Pages 73-93
  4. John N. Mordeson
    Pages 95-125
  5. Akira Nakamura
    Pages 127-155
  6. Angela Y. Wu
    Pages 157-180
  7. Hanan Samet
    Pages 181-217
  8. Maneesh K. Singh, Narendra Ahuja
    Pages 241-288
  9. Steven W. Zucker
    Pages 289-321
  10. Cornelia Fermüller, Yiannis Aloimonos
    Pages 409-445
  11. Yael Pritch, Moshe Ben-Ezra, Shmuel Peleg
    Pages 447-467
  12. Back Matter
    Pages 491-492

About this book

Introduction

Computer systems that analyze images are critical to a wide variety of applications such as visual inspections systems for various manufacturing processes, remote sensing of the environment from space-borne imaging platforms, and automatic diagnosis from X-rays and other medical imaging sources. Professor Azriel Rosenfeld, the founder of the field of digital image analysis, made fundamental contributions to a wide variety of problems in image processing, pattern recognition and computer vision. Professor Rosenfeld's previous students, postdoctoral scientists, and colleagues illustrate in Foundations of Image Understanding how current research has been influenced by his work as the leading researcher in the area of image analysis for over two decades.
Each chapter of Foundations of Image Understanding is written by one of the world's leading experts in his area of specialization, examining digital geometry and topology (early research which laid the foundations for many industrial machine vision systems), edge detection and segmentation (fundamental to systems that analyze complex images of our three-dimensional world), multi-resolution and variable resolution representations for images and maps, parallel algorithms and systems for image analysis, and the importance of human psychophysical studies of vision to the design of computer vision systems. Professor Rosenfeld's chapter briefly discusses topics not covered in the contributed chapters, providing a personal, historical perspective on the development of the field of image understanding.
Foundations of Image Understanding is an excellent source of basic material for both graduate students entering the field and established researchers who require a compact source for many of the foundational topics in image analysis.

Keywords

Computer Vision Stereo algorithms computer image analysis image processing machine vision modeling statistics topology

Editors and affiliations

  • Larry S. Davis
    • 1
  1. 1.University of MarylandUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-1529-6
  • Copyright Information Kluwer Academic Publishers 2001
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-5599-1
  • Online ISBN 978-1-4615-1529-6
  • Series Print ISSN 0893-3405
  • About this book