Image Modeling

Image Modeling

1st Edition - September 28, 1981
This is the Latest Edition
  • Editor: Azriel Rosenfeld
  • eBook ISBN: 9781483275604

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Description

Image Modeling compiles papers presented at a workshop on image modeling in Rosemont, Illinois on August 6-7, 1979. This book discusses the mosaic models for textures, image segmentation as an estimation problem, and comparative analysis of line-drawing modeling schemes. The statistical models for the image restoration problem, use of Markov random fields as models of texture, and mathematical models of graphics are also elaborated. This text likewise covers the univariate and multivariate random field models for images, stochastic image models generated by random tessellations of the plane, and long crested wave models. Other topics include the Boolean model and random sets, structural basis for image description, and structure in co-occurrence matrices for texture analysis. This publication is useful to specialists and professionals working in the field of image processing.

Table of Contents


  • List of Contributors

    Preface

    Mosaic Models for Textures

    Image Segmentation as an Estimation Problem

    Toward a Structural Textural Analyzer Based on Statistical Methods

    Stochastic Boundary Estimation and Object Recognition

    Edge Detection in Textures

    Comparative Analysis of Line-Drawing Modeling Schemes

    Statistical Models for the Image Restoration Problem

    Syntactic Image Modeling Using Stochastic Tree Grammars

    Edge and Region Analysis for Digital Image Data

    The Use of Markov Random Fields as Models of Texture

    On the Noise in Images Produced by Computed Tomography

    Mathematical Models of Graphics

    Nonstationary Statistical Image Models (and Their Application to Image Data Compression)

    Markov Mesh Models

    Univariate and Multivariate Random Field Models for Images

    Image Models in Pattern Theory

    A Survey of Geometrical Probability in the Plane, with Emphasis on Stochastic Image Modeling

    Stochastic Image Models Generated by Random Tessellations of the Plane

    Long Crested Wave Models

    The Boolean Model and Random Sets

    Scene Modeling: A Structural Basis for Image Description

    Pictorial Feature Extraction and Recognition via Image Modeling

    Finding Structure in Co-Occurrence Matrices for Texture Analysis

Product details

  • No. of pages: 460
  • Language: English
  • Copyright: © Academic Press 1981
  • Published: September 28, 1981
  • Imprint: Academic Press
  • eBook ISBN: 9781483275604
  • About the Editor

    Azriel Rosenfeld

    The late Azriel Rosenfeld was a tenured research professor, a distinguished university professor, and the Founding Director of the Center for Automation Research at the University of Maryland in College Park, where he also held affiliate professorships in the departments of computer science, electrical engineering, and psychology. Dr. Rosenfeld was widely regarded as the leading researcher in the world in the field of computer image analysis. Over a period of nearly 40 years, he made fundamental and pioneering contributions to nearly every area of that field. He wrote the first textbook in the field, was founding editor of its first journal, and was co-chairman of its first international conference. He published over 30 books and over 600 book chapters and journal articles, and directed nearly 60 Ph.D. dissertations. Dr. Rosenfeld's research on digital image analysis—specifically on digital geometry and topology and the accurate measurement of statistical features of digital images in the 1960s and 1970s—formed the foundation for a generation of industrial vision inspection systems that have found widespread applications from the automotive to the electronics industry. He was a Fellow of the IEEE and the Washington Academy of Sciences; a Founding Fellow of the AAAI, the ACM, and the IAPR. Among his numerous awards and honors are the IEEE's Emanuel Piore Award, its Third Millennium Medal, and its Distinguished Service Award for Lifetime Achievement in Computer Vision and Pattern Recognition.

    Affiliations and Expertise

    University of Maryland, College Park, U.S.A.