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Vision with Direction

A Systematic Introduction to Image Processing and Computer Vision

By Josef Bigun

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  • ISBN13: 978-3-5402-7322-6
  • 412 Pages
  • User Level: Students
  • Publication Date: May 1, 2006
  • Available eBook Formats: PDF
Full Description
This introductory textbook presents the modern signal processing concepts used in computer vision and image analysis in a systematic and mathematically coherent way. For the first time in a textbook on image processing, single direction, group direction, corners and edges, Hough transform, and motion estimation are developed in a principled way using direction tensors as the unifying concept. The topics presented include Hilbert spaces, the Fourier transform, scale analysis, direction fields, structure tensors, motion tensors, the Hough transform, grouping, and segmentation. Directional signal processing, an increasingly crucial element of computer vision for which neural circuits exist in human vision, is dealt with in depth by use of tensors. All chapters are richly illustrated, with color graphics from cover to cover; applications are studied in various fields, including biometric person authentication, texture analysis, optical character recognition, and motion estimation and tracking; and exercises help the sudent verify progress. Developed out of courses given by the author, this introductory textbook addresses advanced undergarduates as well as master and PhD students in computer science, engineering, mathematics, and in other disciplines where techniques from computer vision, image processing, visual computation and signal analysis are applied.
Table of Contents

Table of Contents

  1. From the contents: Part I: Human and Computer Vision: Organization in Human Vision.
  2. Direction, Frequency, and Velocity Preference.
  3. Color.
  4. Face Recognition.
  5. Part II: Linear Tools of Vision: Discrete Images and Hilbert Spaces.
  6. Continous Functions and Hilbert Spaces.
  7. Finite Extension or Periodic Functions – Fourier Coefficients.
  8. Fourier Transform
  9. Infinite Extension Functions.
  10. Properties of the Fourier Transform.
  11. Reconstruction and Approximation.
  12. Scales and Frequency Channels.
  13. Part III: Vision of Single Direction: Direction in 2
  14. D.
  15. Generalized Direction in 2
  16. D.
  17. Part IV: Multiple Directions in Vision: N
  18. folded Symmetry in Images.
  19. Part V: Grouping, Segmentation, and Region Description: Reducing the Dimension of Features.
  20. Feature Clustering.
  21. Image Segmentation and Region Categorization.
  22. Region and Boundary Descriptors.
  23. Part VI: Vision of World Geometry: Camera Parameters.
  24. World Geometry by Measurements in Images.
  25. References.

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