Mathematical Morphology and its Applications to Image and Signal Processing

  • Petros Maragos
  • Ronald W. Schafer
  • Muhammad Akmal Butt

Part of the Computational Imaging and Vision book series (CIVI, volume 5)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Introduction

    1. Petros Maragos, Ronald W. Schafer, Muhammad Akmal Butt
      Pages 1-5
  3. Theory

    1. Pijush K. Ghosh, Henk J. A. M. Heijmans
      Pages 7-14
    2. Juliette Mattioli, Luc Doyen, Laurent Najman
      Pages 23-30
    3. Edmond Breen, Ronald Jones
      Pages 41-48
    4. Mohammed Charif-Chefchaouni, Dan Schonfeld
      Pages 49-56
    5. J. B. T. M. Roerdink
      Pages 57-64
    6. K. Sivakumar, J. Goutsias
      Pages 73-80
  4. Connectivity

    1. Jean Serra
      Pages 81-96
    2. P. Salembier, A. Oliveras
      Pages 97-110
  5. Filtering

    1. Henk J. A. M. Heijmans
      Pages 127-137
    2. Rein Van Den Boomgaard, Leo Dorst, Sherif Makram-Ebeid, John Schavemaker
      Pages 147-154
    3. Lúcio F. C. Pessoa, Petros Maragos
      Pages 155-162
    4. Dan Schonfeld
      Pages 163-170

About this book

Introduction

Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry.
MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies.
The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes:
  • Theory
  • Connectivity
  • Filtering
  • Nonlinear System Related to Morphology
  • Algorithms/Architectures
  • Granulometries, Texture
  • Segmentation
  • Image Sequence Analysis
  • Learning
  • Document Analysis
  • Applications

Keywords

Diffusion Erosion Interpolation LED Opening Region Growing filter image analysis image processing information mathematical morphology modeling signal processing

Editors and affiliations

  • Petros Maragos
    • 1
  • Ronald W. Schafer
    • 1
  • Muhammad Akmal Butt
    • 1
  1. 1.Georgia Institute of TechnologyUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4613-0469-2
  • Copyright Information Springer-Verlag US 1996
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-8063-4
  • Online ISBN 978-1-4613-0469-2
  • Series Print ISSN 1381-6446
  • About this book
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