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Machine Vision for the Inspection of Natural Products

  • Mark Graves
  • Bruce Batchelor

Table of contents

  1. Front Matter
    Pages i-xxiv
  2. B. G. Batchelor
    Pages 1-33
  3. B. G. Batchelor, P. F. Whelan
    Pages 35-86
  4. B. G. Batchelor
    Pages 87-140
  5. S. C. Bee, M. J. Honeywood
    Pages 163-189
  6. A. K. Forrest
    Pages 191-213
  7. P. Ngan, D. Penman, C. Bowman
    Pages 215-239
  8. W. Daley, D. Britton
    Pages 241-258
  9. M. Mufti, G. Vachtsevanos, L. Dorrity
    Pages 279-304
  10. R. D. Tillett, J. A. Lines, D. Chan, N. J. B. McFarlane, L. G. Ross
    Pages 331-345
  11. J. A. Marchant, C. P. Schofield
    Pages 347-366
  12. P. Hilton, W. Power, M. Hayes, C. Bowman
    Pages 367-392
  13. B. G. Batchelor, M. Graves
    Pages 451-457
  14. Back Matter
    Pages 459-471

About this book

Introduction

Machine vision technology has revolutionised the process of automated inspection in manufacturing. The specialist techniques required for inspection of natural products, such as food, leather, textiles and stone is still a challenging area of research. Topological variations make image processing algorithm development, system integration and mechanical handling issues much more complex. The practical issues of making machine vision systems operate robustly in often hostile environments together with the latest technological advancements are reviewed in this volume. Features:
- Case studies based on real-world problems to demonstrate the practical application of machine vision systems.
- In-depth description of system components including image processing, illumination, real-time hardware, mechanical handling, sensing and on-line testing.
- Systems-level integration of constituent technologies for bespoke applications across a variety of industries.
- A diverse range of example applications that a system may be required to handle from live fish to ceramic tiles.
Machine Vision for the Inspection of Natural Products will be a valuable resource for researchers developing innovative machine vision systems in collaboration with food technology, textile and agriculture sectors. It will also appeal to practising engineers and managers in industries where the application of machine vision can enhance product safety and process efficiency.

Keywords

Textil algorithms control design development environment image processing machine machine vision mathematical morphology model pattern recognition quality safety software

Editors and affiliations

  • Mark Graves
    • 1
  • Bruce Batchelor
    • 2
  1. 1.Spectral Fusion TechnologiesColeshill, Birmngham
  2. 2.Department of Computer ScienceUniversity of CardiffCardiff

Bibliographic information