Image Modeling
eBook - PDF

Image Modeling

  1. 460 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Image Modeling

Book details
Table of contents
Citations

About This Book

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.

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Information

Publisher
Academic Press
Year
2014
ISBN
9781483275604
Topic
Computer Science
Subtopic
Computer Vision & Pattern Recognition
Index
Computer Science

Table of contents

  1. Front Cover
  2. Image Modeling
  3. Copyright Page
  4. Table of Contents
  5. List of Contributors
  6. Preface
  7. Chapter 1. Mosaic Models for Textures
  8. Chapter 2. Image Segmentation as an Estimation Problem
  9. Chapter 3. Toward a Structural Textural Analyzer Based on Statistical Methods
  10. Chapter 4. Stochastic Boundary Estimation and Object Recognition
  11. Chapter 5. Edge Detection in Textures
  12. Chapter 6. Comparative Analysis of Line-Drawing Modeling Schemes
  13. Chapter 7. Statistical Models for the Image Restoration Problem
  14. Chapter 8. Syntactic Image Modeling Using Stochastic Tree Grammars
  15. Chapter 9. Edge and Region Analysis for Digital Image Data
  16. Chapter 10. The Use of Markov Random Fields as Models of Texture
  17. Chapter 11. On the Noise in Images Produced by Computed Tomography
  18. Chapter 12. Mathematical Models of Graphics
  19. Chapter 13. Nonstationary Statistical Image Models (and Their Application to Image Data Compression)
  20. Chapter 14. Markov Mesh Models
  21. Chapter 15. Univariate and Multivariate Random Field Models for Images
  22. Chapter 16. Image Models in Pattern Theory
  23. Chapter 17. A Survey of Geometrical Probability in the Plane, with Emphasis on Stochastic image Modeling
  24. Chapter 18. Stochastic Image Models Generated by Random Tessellations of the Plane
  25. Chapter 19. Long Crested Wave Models
  26. Chapter 20. The Boolean Model and Random Sets
  27. Chapter 21. Scene Modeling: A Structural Basis for Image Description
  28. Chapter 22. Pictorial Feature Extraction and Recognition via Image Modeling
  29. Chapter 23. Finding Structure in Co-Occurrence Matrices for Texture Analysis