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Computer Vision Technology in the Food and Beverage Industries

Book Description

The use of computer vision systems to control manufacturing processes and product quality has become increasingly important in food processing. Computer vision technology in the food and beverage industries reviews image acquisition and processing technologies and their applications in particular sectors of the food industry.

Part one provides an introduction to computer vision in the food and beverage industries, discussing computer vision and infrared techniques for image analysis, hyperspectral and multispectral imaging, tomographic techniques and image processing. Part two goes on to consider computer vision technologies for automatic sorting, foreign body detection and removal, automated cutting and image analysis of food microstructure. Current and future applications of computer vision in specific areas of the food and beverage industries are the focus of part three. Techniques for quality control of meats are discussed alongside computer vision in the poultry, fish and bakery industries, including techniques for grain quality evaluation, and the evaluation and control of fruit, vegetable and nut quality.

With its distinguished editor and international team of expert contributors, Computer vision technology in the food and beverage industries is an indispensible guide for all engineers and researchers involved in the development and use of state-of-the-art vision systems in the food industry.

  • Discusses computer vision and infrared techniques for image analysis, hyperspectral and multispectral imaging, tomographic techniques and image processing
  • Considers computer vision technologies for automatic sorting, foreign body detection and removal, automated cutting and image analysis of food microstructure
  • Examines techniques for quality control and computer vision in various industries including the poultry, fish and bakery, fruit, vegetable and nut industry

Table of Contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Contributor contact details
  6. About the editor
  7. Woodhead Publishing Series in Food Science, Technology and Nutrition
  8. Part I: An introduction to computer vision in the food and beverage industries
    1. Chapter 1: Computer vision and infrared techniques for image acquisition in the food and beverage industries
      1. Abstract:
      2. 1.1 Introduction
      3. 1.2 The electromagnetic spectrum
      4. 1.3 Image acquisition systems
      5. 1.4 Conclusions
      6. 1.6 Appendix: nomenclature and abbreviations
    2. Chapter 2: Hyperspectral and multispectral imaging in the food and beverage industries
      1. Abstract:
      2. 2.1 Introduction
      3. 2.2 Spectral image acquisition methods
      4. 2.3 Construction of spectral imaging systems
      5. 2.4 Calibration of spectral imaging systems
      6. 2.5 Spectral images and analysis techniques
      7. 2.6 Applications for food and beverage products
      8. 2.7 Conclusions
    3. Chapter 3: Tomographic techniques for computer vision in the food and beverage industries
      1. Abstract:
      2. 3.1 Introduction
      3. 3.2 Nuclear tomography
      4. 3.3 Electrical impedance
      5. 3.4 Image reconstruction
      6. 3.5 Applications
      7. 3.6 Conclusions
      8. 3.8 Appendix: nomenclature and abbreviations
    4. Chapter 4: Image processing techniques for computer vision in the food and beverage industries
      1. Abstract:
      2. 4.1 Introduction
      3. 4.2 Digital image analysis techniques
      4. 4.3 Classification
      5. 4.4 Relevance, impact and trends for the food and beverage industry
      6. 4.5 Conclusions
  9. Part II: Computer vision applications in food and beverage processing operations/technologies
    1. Chapter 5: Computer vision in food processing: an overview
      1. Abstract:
      2. 5.1 Introduction to computer vision
      3. 5.2 Technology selection
      4. 5.3 Selection of image analysis methods
      5. 5.4 Application examples
      6. 5.5 Conclusion
    2. Chapter 6: Computer vision for automatic sorting in the food industry
      1. Abstract:
      2. 6.1 Introduction
      3. 6.2 Basic techniques and their application
      4. 6.3 Advanced techniques and their application
      5. 6.4 Alternative image modalities
      6. 6.5 Special real-time hardware for food sorting
      7. 6.6 Recent advances in computer vision for food sorting
      8. 6.7 Future trends
      9. 6.8 Conclusion
      10. 6.10 Acknowledgements
    3. Chapter 7: Computer vision for foreign body detection and removal in the food industry
      1. Abstract:
      2. 7.1 Introduction
      3. 7.2 Optical inspection
      4. 7.3 Fundamentals of X-ray inspection
      5. 7.4 X-ray inspection of food products
      6. 7.5 Conclusions
    4. Chapter 8: Automated cutting in the food industry using computer vision
      1. Abstract:
      2. 8.1 Introduction
      3. 8.2 Machine vision and computer vision
      4. 8.3 Feature selection, extraction and analysis
      5. 8.4 Machine learning algorithms
      6. 8.5 Application examples: sensing for automated cutting and handling
      7. 8.6 Future trends
      8. 8.7 Conclusions
      9. 8.8 Acknowledgments
    5. Chapter 9: Image analysis of food microstructure
      1. Abstract:
      2. 9.1 Introduction
      3. 9.2 Quality control applications of digital imaging
      4. 9.3 Characterizing the internal structure
      5. 9.4 Volume, surface and length
      6. 9.5 Number and spatial distribution
      7. 9.6 Surfaces and fractal dimensions
      8. 9.7 Conclusions
  10. Part III: Current and future applications of computer vision for quality control and processing of particular products
    1. Chapter 10: Computer vision in the fresh and processed meat industries
      1. Abstract:
      2. 10.1 Introduction
      3. 10.2 Meat image features
      4. 10.3 Application and implementation
      5. 10.4 Application and implementation for lamb, pork and other processed meats
      6. 10.5 Future trends
      7. 10.6 Conclusions
    2. Chapter 11: Real-time ultrasound (RTU) imaging methods for quality control of meats
      1. Abstract:
      2. 11.1 Introduction
      3. 11.2 Historical background on ultrasound use for carcass composition and meat traits evaluation
      4. 11.3 Basic ultrasound imaging principles
      5. 11.4 Applications of real-time ultrasound (RTU) to predict carcass composition and meat traits in large animals
      6. 11.5 Applications of RTU to predict carcass composition and meat traits in small animals and fish
      7. 11.6 Using real-time ultrasonography to predict intramuscular fat (IMF) in vivo
      8. 11.7 Optimization of production system and market carcass characteristics
      9. 11.8 The future of RTU imaging in the meat industry
      10. 11.9 Conclusion
    3. Chapter 12: Computer vision in the poultry industry
      1. Abstract:
      2. 12.1 Introduction
      3. 12.2 Poultry processing applications
      4. 12.3 Development of spectral imaging for poultry inspection
      5. 12.4 Case studies for online line-scan poultry safety inspection
      6. 12.5 Future trends
      7. 12.6 Conclusions
    4. Chapter 13: Computer vision in the fish industry
      1. Abstract:
      2. 13.1 Introduction
      3. 13.2 The need for computer vision in the fish industry
      4. 13.3 Automated sorting and grading
      5. 13.4 Automated processing
      6. 13.5 Process understanding and optimization
      7. 13.6 Challenges in applying computer vision in the fish industry
      8. 13.7 Future trends
      9. 13.8 Further information
      10. 13.9 Conclusions
    5. Chapter 14: Fruit, vegetable and nut quality evaluation and control using computer vision
      1. Abstract:
      2. 14.1 Introduction
      3. 14.2 Basics of machine vision systems for fruit, vegetable and nut quality evaluation and control
      4. 14.3 Applications of computer vision in the inspection of external features
      5. 14.4 Real-time automatic inspection systems
      6. 14.5 Future trends
      7. 14.6 Conclusions
      8. 14.7 Sources of further information
      9. 14.8 Acknowledgements
    6. Chapter 15: Grain quality evaluation by computer vision
      1. Abstract:
      2. 15.1 Introduction
      3. 15.2 Colour imaging
      4. 15.3 Hyperspectral imaging
      5. 15.4 X-ray imaging
      6. 15.5 Thermal imaging
      7. 15.6 Conclusions
      8. 15.7 Acknowledgements
    7. Chapter 16: Computer vision in the bakery industry
      1. Abstract:
      2. 16.1 Introduction
      3. 16.2 Computer vision applications for analysing bread
      4. 16.3 Computer vision applications for analysing muffins
      5. 16.4 Computer vision applications for analysing biscuits
      6. 16.5 Computer vision applications for analysing pizza bases
      7. 16.6 Computer vision applications for analysing other bakery products
      8. 16.7 Future trends and further information
      9. 16.8 Conclusions
    8. Chapter 17: Development of multispectral imaging systems for quality evaluation of cereal grains and grain products
      1. Abstract:
      2. 17.1 Introduction
      3. 17.2 Hyperspectral imaging
      4. 17.3 Detection of mildew damage in wheat
      5. 17.4 Detection of fusarium damage in wheat
      6. 17.5 Sprout damage in wheat
      7. 17.6 Determination of green immature kernels in cereal grains
      8. 17.7 Effect of mildew on the quality of end-products
      9. 17.8 Development of multispectral imaging systems
      10. 17.9 Conclusions
      11. 17.10 Acknowledgements
  11. Index