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Computer vision technology in the food and beverage industries

Edited by D-W Sun, University College Dublin, Ireland

Woodhead Publishing Series in Food Science, Technology and Nutrition No. 238

 - 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

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.

ISBN 0 85709 036 4
ISBN-13: 978 0 85709 036 2
August 2012
528 pages  234 x 156mm  hardback  
£165.00 / US$280.00 / €200.00

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About the 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.

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Contents

PART 1 AN INTRODUCTION TO COMPUTER VISION IN THE FOOD AND BEVERAGE INDUSTRIES
PART 2 COMPUTER VISION APPLICATIONS IN FOOD AND BEVERAGE PROCESSING OPERATIONS/TECHNOLOGIES
PART 3 CURRENT AND FUTURE APPLICATIONS OF COMPUTER VISION FOR QUALITY CONTROL AND PROCESSING OF PARTICULAR PRODUCTS

PART 1 AN INTRODUCTION TO COMPUTER VISION IN THE FOOD AND BEVERAGE INDUSTRIES

Computer vision and infrared techniques for image acquisition in the food and beverage industries
M Z Abdullah, Universiti Sains Malaysia, Malaysia
 - Introduction
 - The electromagnetic spectrum
 - Image acquisition systems
 - Conclusions
 - References

Hyperspectral and multispectral imaging in the food and beverage industries
J Qin, United States Department of Agriculture, USA
 - Introduction
 - Spectral image acquisition methods
 - Construction of spectral imaging systems
 - Calibration of spectral imaging system
 - Spectral images and analysis techniques
 - Applications for food and beverage products
 - Conclusion
 - Further information
 - References

Tomographic techniques for computer vision in the food and beverage industries
M Z Abdullah, Universiti Sains Malaysia, Malaysia
 - Introduction
 - Nuclear tomography
 - Electrical impedance
 - Image reconstruction
 - Applications
 - Conclusions
 - References

Image processing techniques for computer vision in the food and beverage industries
N A Valous and D-W Sun, University College Dublin, Ireland
 - Introduction
 - Digital image analysis techniques
 - Classification
 - Relevance, impact and trends for the food and beverage industry
 - Conclusions
 - References

PART 2 COMPUTER VISION APPLICATIONS IN FOOD AND BEVERAGE PROCESSING OPERATIONS/TECHNOLOGIES

Computer vision in food processing: an overview
R Lind and A Murhed, SICK IVP AB, Sweden
 - Introduction to computer vision
 - Technology selection
 - Selection of image analysis methods
 - Application examples
 - Conclusion
 - References

Computer vision for automatic sorting in the food industry
E R Davies, Royal Holloway University of London, UK
 - Introduction
 - Basic techniques and their application
 - Advanced techniques and their application
 - Alternative image modalities
 - Special real-time hardware for food sorting
 - Recent advances in computer vision for food sorting
 - Future trends
 - Conclusion
 - Sources of further information and advice
 - Acknowledgements
 - References

Computer vision for foreign body detection and removal in the food industry
N Toyofuku and R Haff, Plant Mycotoxin Research Unit, USDA ARS WRRC, USA
 - Introduction
 - Optical inspection
 - Fundamentals of X-ray Inspection
 - X-ray inspection of food products
 - Conclusions
 - References

Automated cutting in the food industry using computer vision
W Daley and O Arif, Georgia Institute of Technology, USA
 - Introduction
 - Machine vision and computer vision
 - Feature selection, extraction and analysis
 - Machine learning algorithms
 - Application examples: sensing for automated cutting and handling
 - Future trends
 - Conclusions
 - Acknowledgements
 - References

Image analysis of food microstructure
J Russ, North Carolina State University, USA
 - Introduction
 - Quality control applications of digital imaging
 - Characterizing the internal structure
 - Volume, surface and length
 - Number and spatial distribution
 - Surfaces and fractal dimensions
 - Conclusion
 - References

PART 3 CURRENT AND FUTURE APPLICATIONS OF COMPUTER VISION FOR QUALITY CONTROL AND PROCESSING OF PARTICULAR PRODUCTS

Computer vision in the fresh and processed meat industries
P Jackman and D-W Sun, University College Dublin, Ireland
 - Introduction
 - Meat image features
 - Application and implementation
 - Application and implementation for lamb, pork and other processed meats
 - Future trends
 - Conclusions
 - References

Real-time ultrasound (RTU) imaging methods for quality control of meats
S R Silva, University of Tras-os-Montes e Alto Douro, and V P Cadavez, Escola Superior Agrária, Instituto Politécnico de Bragança, Portugal
 - Introduction
 - Historical background on ultrasound use for carcass composition and meat traits evaluation
 - Basic ultrasound imaging principles
 - Applications of real-time ultrasound (RTU) to predict carcass composition and meat traits in large animals
 - Applications of RTU to predict carcass composition and meat traits in small animals and fish
 - Using real time ultrasonography to predict intramuscular fat (IMF) in vivo
 - Optimization of production system and market carcass characteristics
 - The future of RTU imaging in the meat industry
 - Conclusion
 - References

Computer vision in the poultry industry
K Chao, Henry A Wallace Beltsville Agricultural Research Center, Environmental Microbial and Food Safety Laboratory, B Park, Richard B Russell Research Center, and M S Kim, Henry A Wallace Beltsville Agricultural Research Center, Environmental Microbial and Food Safety Laboratory, USA
 - Introduction
 - Poultry processing applications
 - Development of spectral imaging for poultry inspection
 - Case studies for online line-scan poultry safety inspection
 - Future trends
 - Conclusion
 - References

Computer vision in the fish industry
J R Mathiassen, E Misimi, S O Ostvik and I G Aursand, Department of Processing Technology, SINTEF Fisheries and Aquaculture, Norway
 - Introduction
 - The need for computer vision in the fish industry
 - Automated sorting and grading
 - Automated processing
 - Process understanding and optimization
 - Challenges in applying computer vision in the fish industry
 - Future trends
 - Further information
 - Conclusion
 - References

Fruit, vegetable and nut quality evaluation and control using computer vision
J Blasco, IVIA- Instituto Valenciano de Investigaciones Agrarias, Centro de Agroingeniería, N Aleixos, Universidad Politécnica de Valencia, S Cubero and D Lorente, IVIA- Instituto Valenciano de Investigaciones Agrarias, Centro de Agroingeniería, Spain
 - Introduction
 - Basics of machine vision systems for fruit, vegetable and nut quality evaluation and control
 - Applications of computer vision in the inspection of external features
 - Future trends
 - Conclusion
 - Sources of further information and advice
 - Acknowledgements
 - References

Grain quality evaluation by computer vision
D S Jayas and C B Singh, University of Manitoba, Canada
 - Introduction
 - Colour imaging
 - Hyperspectral imaging
 - X-ray imaging
 - Thermal imaging
 - Conclusion
 - Acknowledgements
 - References

Computer vision in the bakery industry
C-J Du, University of Warwick, Q Cheng, University of Reading, UK and D-W Sun, University College Dublin, Ireland
 - Introduction
 - Computer vision applications for analysing bread
 - Computer vision applications for analysing muffins
 - Computer vision applications for analysing biscuits
 - Computer vision applications for analysing pizza bases
 - Computer vision applications for analysing other bakery products
 - Future trends and further information
 - Conclusions
 - References

Development of multispectral imaging systems for quality evaluation of cereal grains and grain products
M A Shahin, D W Hatcher, and S J Symons, Canadian Grain Commission, Canada
 - Introduction
 - Hyperspectral imaging
 - Detection of mildew damage in wheat
 - Detection of fusarium damage in wheat
 - Sprout damage in wheat
 - Determination of green immature kernels in cereal grains
 - Effect of mildew on the quality of end-products
 - Development of multispectral imaging systems
 - Conclusion
 - Acknowledgements
 - References