Computer Vision Technology in the Food and Beverage Industries - 1st Edition - ISBN: 9780857090362, 9780857095770

Computer Vision Technology in the Food and Beverage Industries

1st Edition

Editors: D-W Sun
Hardcover ISBN: 9780857090362
eBook ISBN: 9780857095770
Imprint: Woodhead Publishing
Published Date: 13th August 2012
Page Count: 528
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Table of Contents

Contributor contact details

About the editor

Woodhead Publishing Series in Food Science, Technology and Nutrition

Part I: An introduction to computer vision in the food and beverage industries

Chapter 1: Computer vision and infrared techniques for image acquisition in the food and beverage industries

Abstract:

1.1 Introduction

1.2 The electromagnetic spectrum

1.3 Image acquisition systems

1.4 Conclusions

1.6 Appendix: nomenclature and abbreviations

Chapter 2: Hyperspectral and multispectral imaging in the food and beverage industries

Abstract:

2.1 Introduction

2.2 Spectral image acquisition methods

2.3 Construction of spectral imaging systems

2.4 Calibration of spectral imaging systems

2.5 Spectral images and analysis techniques

2.6 Applications for food and beverage products

2.7 Conclusions

Chapter 3: Tomographic techniques for computer vision in the food and beverage industries

Abstract:

3.1 Introduction

3.2 Nuclear tomography

3.3 Electrical impedance

3.4 Image reconstruction

3.5 Applications

3.6 Conclusions

3.8 Appendix: nomenclature and abbreviations

Chapter 4: Image processing techniques for computer vision in the food and beverage industries

Abstract:

4.1 Introduction

4.2 Digital image analysis techniques

4.3 Classification

4.4 Relevance, impact and trends for the food and beverage industry

4.5 Conclusions

Part II: Computer vision applications in food and beverage processing operations/technologies

Chapter 5: Computer vision in food processing: an overview

Abstract:

5.1 Introduction to computer vision

5.2 Technology selection

5.3 Selection of image analysis methods

5.4 Application examples

5.5 Conclusion

Chapter 6: Computer vision for automatic sorting in the food industry

Abstract:

6.1 Introduction

6.2 Basic techniques and their application

6.3 Advanced techniques and their application

6.4 Alternative image modalities

6.5 Special real-time hardware for food sorting

6.6 Recent advances in computer vision for food sorting

6.7 Future trends

6.8 Conclusion

6.10 Acknowledgements

Chapter 7: Computer vision for foreign body detection and removal in the food industry

Abstract:

7.1 Introduction

7.2 Optical inspection

7.3 Fundamentals of X-ray inspection

7.4 X-ray inspection of food products

7.5 Conclusions

Chapter 8: Automated cutting in the food industry using computer vision

Abstract:

8.1 Introduction

8.2 Machine vision and computer vision

8.3 Feature selection, extraction and analysis

8.4 Machine learning algorithms

8.5 Application examples: sensing for automated cutting and handling

8.6 Future trends

8.7 Conclusions

8.8 Acknowledgments

Chapter 9: Image analysis of food microstructure

Abstract:

9.1 Introduction

9.2 Quality control applications of digital imaging

9.3 Characterizing the internal structure

9.4 Volume, surface and length

9.5 Number and spatial distribution

9.6 Surfaces and fractal dimensions

9.7 Conclusions

Part III: Current and future applications of computer vision for quality control and processing of particular products

Chapter 10: Computer vision in the fresh and processed meat industries

Abstract:

10.1 Introduction

10.2 Meat image features

10.3 Application and implementation

10.4 Application and implementation for lamb, pork and other processed meats

10.5 Future trends

10.6 Conclusions

Chapter 11: Real-time ultrasound (RTU) imaging methods for quality control of meats

Abstract:

11.1 Introduction

11.2 Historical background on ultrasound use for carcass composition and meat traits evaluation

11.3 Basic ultrasound imaging principles

11.4 Applications of real-time ultrasound (RTU) to predict carcass composition and meat traits in large animals

11.5 Applications of RTU to predict carcass composition and meat traits in small animals and fish

11.6 Using real-time ultrasonography to predict intramuscular fat (IMF) in vivo

11.7 Optimization of production system and market carcass characteristics

11.8 The future of RTU imaging in the meat industry

11.9 Conclusion

Chapter 12: Computer vision in the poultry industry

Abstract:

12.1 Introduction

12.2 Poultry processing applications

12.3 Development of spectral imaging for poultry inspection

12.4 Case studies for online line-scan poultry safety inspection

12.5 Future trends

12.6 Conclusions

Chapter 13: Computer vision in the fish industry

Abstract:

13.1 Introduction

13.2 The need for computer vision in the fish industry

13.3 Automated sorting and grading

13.4 Automated processing

13.5 Process understanding and optimization

13.6 Challenges in applying computer vision in the fish industry

13.7 Future trends

13.8 Further information

13.9 Conclusions

Chapter 14: Fruit, vegetable and nut quality evaluation and control using computer vision

Abstract:

14.1 Introduction

14.2 Basics of machine vision systems for fruit, vegetable and nut quality evaluation and control

14.3 Applications of computer vision in the inspection of external features

14.4 Real-time automatic inspection systems

14.5 Future trends

14.6 Conclusions

14.7 Sources of further information

14.8 Acknowledgements

Chapter 15: Grain quality evaluation by computer vision

Abstract:

15.1 Introduction

15.2 Colour imaging

15.3 Hyperspectral imaging

15.4 X-ray imaging

15.5 Thermal imaging

15.6 Conclusions

15.7 Acknowledgements

Chapter 16: Computer vision in the bakery industry

Abstract:

16.1 Introduction

16.2 Computer vision applications for analysing bread

16.3 Computer vision applications for analysing muffins

16.4 Computer vision applications for analysing biscuits

16.5 Computer vision applications for analysing pizza bases

16.6 Computer vision applications for analysing other bakery products

16.7 Future trends and further information

16.8 Conclusions

Chapter 17: Development of multispectral imaging systems for quality evaluation of cereal grains and grain products

Abstract:

17.1 Introduction

17.2 Hyperspectral imaging

17.3 Detection of mildew damage in wheat

17.4 Detection of fusarium damage in wheat

17.5 Sprout damage in wheat

17.6 Determination of green immature kernels in cereal grains

17.7 Effect of mildew on the quality of end-products

17.8 Development of multispectral imaging systems

17.9 Conclusions

17.10 Acknowledgements

Index


Description

Contributor contact details

About the editor

Woodhead Publishing Series in Food Science, Technology and Nutrition

Part I: An introduction to computer vision in the food and beverage industries

Chapter 1: Computer vision and infrared techniques for image acquisition in the food and beverage industries

Abstract:

1.1 Introduction

1.2 The electromagnetic spectrum

1.3 Image acquisition systems

1.4 Conclusions

1.6 Appendix: nomenclature and abbreviations

Chapter 2: Hyperspectral and multispectral imaging in the food and beverage industries

Abstract:

2.1 Introduction

2.2 Spectral image acquisition methods

2.3 Construction of spectral imaging systems

2.4 Calibration of spectral imaging systems

2.5 Spectral images and analysis techniques

2.6 Applications for food and beverage products

2.7 Conclusions

Chapter 3: Tomographic techniques for computer vision in the food and beverage industries

Abstract:

3.1 Introduction

3.2 Nuclear tomography

3.3 Electrical impedance

3.4 Image reconstruction

3.5 Applications

3.6 Conclusions

3.8 Appendix: nomenclature and abbreviations

Chapter 4: Image processing techniques for computer vision in the food and beverage industries

Abstract:

4.1 Introduction

4.2 Digital image analysis techniques

4.3 Classification

4.4 Relevance, impact and trends for the food and beverage industry

4.5 Conclusions

Part II: Computer vision applications in food and beverage processing operations/technologies

Chapter 5: Computer vision in food processing: an overview

Abstract:

5.1 Introduction to computer vision

5.2 Technology selection

5.3 Selection of image analysis methods

5.4 Application examples

5.5 Conclusion

Chapter 6: Computer vision for automatic sorting in the food industry

Abstract:

6.1 Introduction

6.2 Basic techniques and their application

6.3 Advanced techniques and their application

6.4 Alternative image modalities

6.5 Special real-time hardware for food sorting

6.6 Recent advances in computer vision for food sorting

6.7 Future trends

6.8 Conclusion

6.10 Acknowledgements

Chapter 7: Computer vision for foreign body detection and removal in the food industry

Abstract:

7.1 Introduction

7.2 Optical inspection

7.3 Fundamentals of X-ray inspection

7.4 X-ray inspection of food products

7.5 Conclusions

Chapter 8: Automated cutting in the food industry using computer vision

Abstract:

8.1 Introduction

8.2 Machine vision and computer vision

8.3 Feature selection, extraction and analysis

8.4 Machine learning algorithms

8.5 Application examples: sensing for automated cutting and handling

8.6 Future trends

8.7 Conclusions

8.8 Acknowledgments

Chapter 9: Image analysis of food microstructure

Abstract:

9.1 Introduction

9.2 Quality control applications of digital imaging

9.3 Characterizing the internal structure

9.4 Volume, surface and length

9.5 Number and spatial distribution

9.6 Surfaces and fractal dimensions

9.7 Conclusions

Part III: Current and future applications of computer vision for quality control and processing of particular products

Chapter 10: Computer vision in the fresh and processed meat industries

Abstract:

10.1 Introduction

10.2 Meat image features

10.3 Application and implementation

10.4 Application and implementation for lamb, pork and other processed meats

10.5 Future trends

10.6 Conclusions

Chapter 11: Real-time ultrasound (RTU) imaging methods for quality control of meats

Abstract:

11.1 Introduction

11.2 Historical background on ultrasound use for carcass composition and meat traits evaluation

11.3 Basic ultrasound imaging principles

11.4 Applications of real-time ultrasound (RTU) to predict carcass composition and meat traits in large animals

11.5 Applications of RTU to predict carcass composition and meat traits in small animals and fish

11.6 Using real-time ultrasonography to predict intramuscular fat (IMF) in vivo

11.7 Optimization of production system and market carcass characteristics

11.8 The future of RTU imaging in the meat industry

11.9 Conclusion

Chapter 12: Computer vision in the poultry industry

Abstract:

12.1 Introduction

12.2 Poultry processing applications

12.3 Development of spectral imaging for poultry inspection

12.4 Case studies for online line-scan poultry safety inspection

12.5 Future trends

12.6 Conclusions

Chapter 13: Computer vision in the fish industry

Abstract:

13.1 Introduction

13.2 The need for computer vision in the fish industry

13.3 Automated sorting and grading

13.4 Automated processing

13.5 Process understanding and optimization

13.6 Challenges in applying computer vision in the fish industry

13.7 Future trends

13.8 Further information

13.9 Conclusions

Chapter 14: Fruit, vegetable and nut quality evaluation and control using computer vision

Abstract:

14.1 Introduction

14.2 Basics of machine vision systems for fruit, vegetable and nut quality evaluation and control

14.3 Applications of computer vision in the inspection of external features

14.4 Real-time automatic inspection systems

14.5 Future trends

14.6 Conclusions

14.7 Sources of further information

14.8 Acknowledgements

Chapter 15: Grain quality evaluation by computer vision

Abstract:

15.1 Introduction

15.2 Colour imaging

15.3 Hyperspectral imaging

15.4 X-ray imaging

15.5 Thermal imaging

15.6 Conclusions

15.7 Acknowledgements

Chapter 16: Computer vision in the bakery industry

Abstract:

16.1 Introduction

16.2 Computer vision applications for analysing bread

16.3 Computer vision applications for analysing muffins

16.4 Computer vision applications for analysing biscuits

16.5 Computer vision applications for analysing pizza bases

16.6 Computer vision applications for analysing other bakery products

16.7 Future trends and further information

16.8 Conclusions

Chapter 17: Development of multispectral imaging systems for quality evaluation of cereal grains and grain products

Abstract:

17.1 Introduction

17.2 Hyperspectral imaging

17.3 Detection of mildew damage in wheat

17.4 Detection of fusarium damage in wheat

17.5 Sprout damage in wheat

17.6 Determination of green immature kernels in cereal grains

17.7 Effect of mildew on the quality of end-products

17.8 Development of multispectral imaging systems

17.9 Conclusions

17.10 Acknowledgements

Index

Key Features

  • 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

Readership

Engineers in the food industry working on vision systems; Researchers with an interest in this field


Details

No. of pages:
528
Language:
English
Copyright:
© Woodhead Publishing 2012
Published:
Imprint:
Woodhead Publishing
eBook ISBN:
9780857095770
Hardcover ISBN:
9780857090362

About the Editors

D-W Sun Editor

Professor Da-Wen Sun is a world authority in food engineering research and education. He is a member of the Royal Irish Academy, the highest academic honour in Ireland, and is also a member of Academia Europaea (The Academy of Europe). His main research activities include cooling, drying, and refrigeration processes and systems; quality and safety of food products; bioprocess simulation and optimization; and computer vision technology. His many scholarly works have become standard reference materials for researchers in such areas as computer vision, computational fluid dynamics modelling and vacuum cooling.

Affiliations and Expertise

University College Dublin, Ireland