Machine vision : theory, algorithms, practicalities

書誌事項

Machine vision : theory, algorithms, practicalities

E.R. Davies

Morgan Kaufmann, c2005

3rd ed

大学図書館所蔵 件 / 19

この図書・雑誌をさがす

注記

Includes bibliographical references (p. 869-915) and indexes

内容説明・目次

内容説明

In the last 40 years, machine vision has evolved into a mature field embracing a wide range of applications including surveillance, automated inspection, robot assembly, vehicle guidance, traffic monitoring and control, signature verification, biometric measurement, and analysis of remotely sensed images. While researchers and industry specialists continue to document their work in this area, it has become increasingly difficult for professionals and graduate students to understand the essential theory and practicalities well enough to design their own algorithms and systems. This book directly addresses this need.As in earlier editions, E.R. Davies clearly and systematically presents the basic concepts of the field in highly accessible prose and images, covering essential elements of the theory while emphasizing algorithmic and practical design constraints. In this thoroughly updated edition, he divides the material into horizontal levels of a complete machine vision system. Application case studies demonstrate specific techniques and illustrate key constraints for designing real-world machine vision systems.

目次

1. Vision, the Challenge Part 1 Low-Level Vision 2. Images and Imaging Operations 3. Basic Image Filtering Operations 4. Thresholding Techniques 5. Edge Detection 6. Binary Shape Analysis 7. Boundary Pattern Analysis 8. Mathematical Morphology Part 2 Intermediate-Level Vision 9. Line Detection 10. Circle Detection 11. The Hough Transform and Its Nature 12. Ellipse Detection 13. Hole Detection 14. Polygon and Corner Detection 15. Abstract Pattern Matching Techniques Part 3 3-D Vision and Motion 16. The Three-Dimensional World 17. Tackling the Perspective n-Point Problem 18. Motion 19. Invariants and their Applications 20. Egomotion and Related Tasks 21. Image Transformations and Camera Calibration Part 4 Towards Real-Time Pattern Recognition Systems 22. Automated Visual Inspection 23. Inspection of Cereal Grains 24. Statistical Pattern Recognition 25. Biologically Inspired Recognition Schemes 26. Texture 27. Image Acquisition 28. Real-Time Hardware and Systems Design Considerations Part 5 Perspectives on Vision 29. Machine Vision, Art or Science? Appendix A Robust Statistics

「Nielsen BookData」 より

詳細情報

  • NII書誌ID(NCID)
    BA70977842
  • ISBN
    • 0122060938
  • LCCN
    2005270146
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    San Francisco, Calif. ; Tokyo
  • ページ数/冊数
    xxxiii, 934 p., [4] p. of plates
  • 大きさ
    24 cm
  • 分類
  • 件名
ページトップへ