Computer vision technology in the food and beverage industries

516 Pages·2012·37.818 MB·English

by  Da-Wen Sun

Computer vision technology in the food and
beverage industries
© Woodhead Publishing Limited, 2012
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© Woodhead Publishing Limited, 2012
Woodhead Publishing Series in Food Science, Technology and Nutrition:
Number 238
Computer vision
technology in the food and
beverage industries
Edited by
Da-Wen Sun
Oxford Cambridge Philadelphia New Delhi
© Woodhead Publishing Limited, 2012
Published by Woodhead Publishing Limited,
80 High Street, Sawston, Cambridge CB22 3HJ, UK
www.woodheadpublishing.com
www.woodheadpublishingonline.com
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First published 2012, Woodhead Publishing Limited
© Woodhead Publishing Limited, 2012; except Chapter 1 © Elsevier, 2007 and Chapter 17
© Canadian Grain Commission, Government of Canada, 2012
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ISBN 978-0-85709-036-2 (print)
ISBN 978-0-85709-577-0 (online)
ISSN 2042-8049 Woodhead Publishing Series in Food Science, Technology and Nutrition (print)
ISSN 2042-8057 Woodhead Publishing Series in Food Science, Technology and Nutrition (online)
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© Woodhead Publishing Limited, 2012
Contents
Contributor contact details .......................................................................... xi
About the editor ............................................................................................ xv
Woodhead Publishing Series in Food Science, Technology
and Nutrition ................................................................................................ xviii
Part I An introduction to computer vision in the
food and beverage industries ...................................................... 1
1 Computer vision and infrared techniques for image acquisition
in the food and beverage industries .................................................... 3
M. Z. Abdullah, Universiti Sains Malaysia, Malaysia
1.1 Introduction .................................................................................. 3
1.2 The electromagnetic spectrum ..................................................... 5
1.3 Image acquisition systems ........................................................... 7
1.4 Conclusions .................................................................................. 24
1.5 References .................................................................................... 24
1.6 Appendix: nomenclature and abbreviations ................................. 26
2 Hyperspectral and multispectral imaging in the
food and beverage industries ............................................................... 27
J. Qin, United States Department of Agriculture, USA
2.1 Introduction .................................................................................. 27
2.2 Spectral image acquisition methods ............................................. 28
2.3 Construction of spectral imaging systems ................................... 30
2.4 Calibration of spectral imaging system s ...................................... 41
2.5 Spectral images and analysis techniques ..................................... 47
2.6 Applications for food and beverage products .............................. 54
2.7 Conclusions .................................................................................. 58
© Woodhead Publishing Limited, 2012
vi Contents
2.8 Further information ...................................................................... 58
2.9 References .................................................................................... 59
3 Tomographic techniques for computer vision in the
food and beverage industries ............................................................... 64
M. Z. Abdullah, Universiti Sains Malaysia, Malaysia
3.1 Introduction .................................................................................. 64
3.2 Nuclear tomography ..................................................................... 65
3.3 Electrical impedance .................................................................... 69
3.4 Image reconstruction .................................................................... 86
3.5 Applications ................................................................................. 89
3.6 Conclusions .................................................................................. 93
3.7 References .................................................................................... 93
3.8 Appendix: nomenclature and abbreviations ................................. 95
4 Image processing techniques for computer vision in the
food and beverage industries ................................................................. 97
N. A. Valous and D.-W. Sun, University College Dublin, Ireland
4.1 Introduction .................................................................................. 97
4.2 Digital image analysis techniques ................................................ 99
4.3 Classification ................................................................................ 113
4.4 Relevance, impact and trends for the
food and beverage industry .......................................................... 119
4.5 Conclusions .................................................................................. 122
4.6 References .................................................................................... 123
Part II Computer vision applications in food and beverage
processing operations/technologies ........................................... 131
5 Computer vision in food processing: an overview ............................. 133
R. Lind and A. Murhed, SICK IVP AB, Sweden
5.1 Introduction to computer vision ................................................... 133
5.2 Technology selection ................................................................... 136
5.3 Selection of image analysis methods ........................................... 139
5.4 Application examples ................................................................... 143
5.5 Conclusion ................................................................................... 148
5.6 References .................................................................................... 148
6 Computer vision for automatic sorting in the food
industry ................................................................................................. 150
E. R. Davies, Royal Holloway, University of London, UK
6.1 Introduction .................................................................................. 150
6.2 Basic techniques and their application ......................................... 152
6.3 Advanced techniques and their application ................................. 160
6.4 Alternative image modalities ....................................................... 172
© Woodhead Publishing Limited, 2012
Contents vii
6.5 Special real-time hardware for food sorting ................................ 173
6.6 Recent advances in computer vision for food sorting .................. 175
6.7 Future trends ................................................................................ 176
6.8 Conclusion ................................................................................... 177
6.9 Sources of further information and advice ................................... 177
6.10 Acknowledgements ...................................................................... 178
6.11 References .................................................................................... 178
7 Computer vision for foreign body detection and
removal in the food industry ............................................................... 181
N. Toyofuku and R. P. Haff, Plant Mycotoxin Research
Unit, USDA ARS WRRC, USA
7.1 Introduction .................................................................................. 181
7.2 Optical inspection ........................................................................ 183
7.3 Fundamentals of X-ray inspection ............................................... 188
7.4 X-ray inspection of food products ............................................... 195
7.5 Conclusions .................................................................................. 200
7.6 References .................................................................................... 200
8 Automated cutting in the food industry using computer
vision ...................................................................................................... 206
W. D. R. Daley, Georgia Institute of Technology, USA and
O. Arif, King Abdullah University of Science and Technology,
Saudi Arabia
8.1 Introduction .................................................................................. 206
8.2 Machine vision and computer vision ........................................... 208
8.3 Feature selection, extraction and analysis .................................... 211
8.4 Machine learning algorithms ....................................................... 212
8.5 Application examples: sensing for automated
cutting and handling ..................................................................... 213
8.6 Future trends ................................................................................ 228
8.7 Conclusions .................................................................................. 230
8.8 Acknowledgments ........................................................................ 231
8.9 References .................................................................................... 231
9 Image analysis of food microstructure ............................................... 233
J. C. Russ, North Carolina State University, USA
9.1 Introduction .................................................................................. 233
9.2 Quality control applications of digital imaging ........................... 234
9.3 Characterizing the internal structure ............................................ 237
9.4 Volume, surface and length .......................................................... 238
9.5 Number and spatial distribution ................................................... 243
9.6 Surfaces and fractal dimensions ................................................... 249
9.7 Conclusions .................................................................................. 250
9.8 References .................................................................................... 251
© Woodhead Publishing Limited, 2012
viii Contents
Part III Current and future applications of computer vision for
quality control and processing of particular products .......... 253
10 Computer vision in the fresh and processed meat industries ........... 255
P. Jackman and D.-W. Sun, University College Dublin, Ireland
10.1 Introduction .................................................................................. 255
10.2 Meat image features ..................................................................... 256
10.3 Application and implementation .................................................. 260
10.4 Application and implementation for lamb,
pork and other processed meats ................................................... 269
10.5 Future trends ................................................................................ 271
10.6 Conclusions .................................................................................. 271
10.7 References .................................................................................... 272
11 Real-time ultrasound (RTU) imaging methods
for quality control of meats ................................................................ 277
S. R. Silva, CECAV, University of Trás-os-Montes e Alto Douro, Portugal
and V. P. Cadavez, CIMO, ESA, Instituto Politécnico
de Bragança, Portugal
11.1 Introduction .................................................................................. 277
11.2 Historical background on ultrasound use for carcass
composition and meat traits evaluation ........................................ 278
11.3 Basic ultrasound imaging principles ............................................ 282
11.4 Applications of real-time ultrasound (RTU) to predict
carcass composition and meat traits in large animals .................. 285
11.5 Applications of RTU to predict carcass composition and
meat traits in small animals and fish ............................................ 293
11.6 Using real-time ultrasonography to predict intramuscular
fat (IMF) in vivo ........................................................................... 303
11.7 Optimization of production system and market
carcass characteristics .................................................................. 310
11.8 The future for RTU imaging in the meat industry ....................... 313
11.9 Conclusion ................................................................................... 314
11.10 References .................................................................................... 315
12 Computer vision in the poultry industry ............................................ 330
K. Chao, Henry A. Wallace Beltsville Agricultural Research Center,
USA, B. Park, Richard B. Russell Research Center, USA and
M. S. Kim, Henry A. Wallace Beltsville Agricultural Research
Center, USA
12.1 Introduction .................................................................................. 330
12.2 Poultry processing applications ................................................... 331
12.3 Development of spectral imaging for poultry inspection ............ 333
12.4 Case studies for online line-scan poultry safety inspection ......... 336
12.5 Future trends ................................................................................ 350
© Woodhead Publishing Limited, 2012
Contents ix
12.6 Conclusions .................................................................................. 350
12.7 References .................................................................................... 351
13 Computer vision in the fish industry .................................................. 352
J. R. Mathiassen, E. Misimi, S. O. Østvik and I. G. Aursand,
Department of Processing Technology, SINTEF Fisheries and
Aquaculture, Norway
13.1 Introduction .................................................................................. 352
13.2 The need for computer vision in the fish industry ....................... 353
13.3 Automated sorting and grading .................................................... 354
13.4 Automated processing .................................................................. 360
13.5 Process understanding and optimization ...................................... 367
13.6 Challenges in applying computer vision in the fish industry ....... 373
13.7 Future trends ................................................................................ 374
13.8 Further information ...................................................................... 375
13.9 Conclusions .................................................................................. 376
13.10 References .................................................................................... 376
14 Fruit, vegetable and nut quality evaluation and control
using computer vision .......................................................................... 379
J. Blasco, IVIA – Instituto Valenciano de Investigaciones Agrarias,
Centro de Agroingeniería, Spain, N. Aleixos, I3BH, Universitat
Politècnica de València, Spain and S. Cubero and D. Lorente, IVIA –
Instituto Valenciano de Investigaciones Agrarias, Centro de
Agroingeniería, Spain
14.1 Introduction .................................................................................. 379
14.2 Basics of machine vision systems for fruit,
vegetable and nut quality evaluation and control ........................ 381
14.3 Applications of computer vision in the inspection
of external features ....................................................................... 386
14.4 Real-time automatic inspection systems ...................................... 388
14.5 Future trends ................................................................................ 392
14.6 Conclusions .................................................................................. 394
14.7 Sources of further information ..................................................... 395
14.8 Acknowledgements ...................................................................... 396
14.9 References .................................................................................... 396
15 Grain quality evaluation by computer vision .................................... 400
D. S. Jayas and C. B. Singh, University of Manitoba, Canada
15.1 Introduction .................................................................................. 400
15.2 Colour imaging ............................................................................ 402
15.3 Hyperspectral imaging ................................................................. 406
15.4 X-ray imaging .............................................................................. 411
15.5 Thermal imaging .......................................................................... 415
15.6 Conclusions .................................................................................. 418
© Woodhead Publishing Limited, 2012
x Contents
15.7 Acknowledgements ...................................................................... 418
15.8 References .................................................................................... 419
16 Computer vision in the bakery industry ............................................ 422
C.-J. Du, University of Warwick, UK, Q. Cheng, University of
Reading, UK, and D.-W. Sun, University College Dublin, Ireland
16.1 Introduction .................................................................................. 422
16.2 Computer vision applications for analysing bread ....................... 423
16.3 Computer vision applications for analysing muffins ................... 432
16.4 Computer vision applications for analysing biscuits ................... 436
16.5 Computer vision applications for analysing pizza bases ............. 439
16.6 Computer vision applications for analysing
other bakery products ................................................................... 444
16.7 Future trends and further information .......................................... 445
16.8 Conclusions .................................................................................. 446
16.9 References .................................................................................... 447
17 Development of multispectral imaging systems for quality
evaluation of cereal grains and grain products ................................. 451
M. A. Shahin, D. W. Hatcher and S. J. Symons, Canadian Grain
Commission, Canada
17.1 Introduction .................................................................................. 452
17.2 Hyperspectral imaging ................................................................. 456
17.3 Detection of mildew damage in wheat ......................................... 459
17.4 Detection of fusarium damage in wheat ...................................... 461
17.5 Sprout damage in wheat ............................................................... 465
17.6 Determination of green immature kernels in cereal grains .......... 469
17.7 Effect of mildew on the quality of end-products ......................... 471
17.8 Development of multispectral imaging systems .......................... 473
17.9 Conclusions .................................................................................. 477
17.10 Acknowledgements ...................................................................... 478
17.11 References .................................................................................... 478
Index ....................................................................................................... 483
© Woodhead Publishing Limited, 2012