Computer Vision Technology for Food Quality Evaluation
- 2nd Edition - April 27, 2016
- Editor: Da-Wen Sun
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 8 0 2 2 3 2 - 0
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 0 2 5 9 9 - 4
Computer Vision Technology for Food Quality Evaluation, Second Edition continues to be a valuable resource to engineers, researchers, and technologists in research and develo… Read more
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Computer Vision Technology for Food Quality Evaluation, Second Edition continues to be a valuable resource to engineers, researchers, and technologists in research and development, as well as a complete reference to students interested in this rapidly expanding field. This new edition highlights the most recent developments in imaging processing and analysis techniques and methodology, captures cutting-edge developments in computer vision technology, and pinpoints future trends in research and development for food quality and safety evaluation and control. It is a unique reference that provides a deep understanding of the issues of data acquisition and image analysis and offers techniques to solve problems and further develop efficient methods for food quality assessment.
- Thoroughly explains what computer vision technology is, what it can do, and how to apply it for food quality evaluation
- Includes a wide variety of computer vision techniques and applications to evaluate a wide variety of foods
- Describes the pros and cons of different techniques for quality evaluation
Engineers and technologists working in research and development and operations within the food industry, instructors and students in food engineering and food technology
Part 1. Fundamentals of Computer Vision Technology
Chapter 1. Image Acquisition Systems
- 1.1. Introduction
- 1.2. The Electromagnetic Spectrum
- 1.3. Image Acquisition Systems
- 1.4. Future Trends
- Nomenclature
Chapter 2. Image Segmentation Techniques
- 2.1. Introduction
- 2.2. Preprocessing Techniques
- 2.3. Segmentation Techniques
- Nomenclature
Chapter 3. Object Measurement Methods
- 3.1. Introduction
- 3.2. Size
- 3.3. Shape
- 3.4. Color
- 3.5. Texture
- 3.6. Combined Measurements
- Nomenclatures
- Appendix
Chapter 4. Object Classification Methods
- 4.1. Introduction
- 4.2. Artificial Neural Network
- 4.3. Statistical Classification (SC)
- 4.4. Fuzzy Logic
- 4.5. Decision Tree
- 4.6. Support Vector Machine
- Nomenclature
Chapter 5. Introduction to Hyperspectral Imaging Technology
- 5.1. Introduction
- 5.2. Fundamentals of Hyperspectral Imaging Technology
- 5.3. Multivariate Data Analysis
- 5.4. Hyperspectral Image Analysis Software
- 5.5. Application of HSI for Muscle Foods
Chapter 6. Introduction to Raman Chemical Imaging Technology
- 6.1. Introduction
- 6.2. Principles of Raman Scattering
- 6.3. Raman Spectroscopy Techniques
- 6.4. Raman Chemical Imaging and Acquisition Methods
- 6.5. Raman Imaging Instruments
- 6.6. Raman Image Analysis Techniques
- 6.7. Applications for Food and Agricultural Products
Part 2. Quality Evaluation of Meat, Poultry and Seafood
Chapter 7. Quality Evaluation of Meat Cuts
- 7.1. Introduction
- 7.2. Quality Evaluation Using Computer Vision
- 7.3. Quality Evaluation Using Hyperspectral Imaging
- 7.4. Future Work
Chapter 8. Quality Measurement of Cooked Meats
- 8.1. Introduction
- 8.2. Shrinkage
- 8.3. Pores and Porosity
- 8.4. Color
- 8.5. Image Texture
- Nomenclature
Chapter 9. Quality Evaluation of Poultry Carcass
- 9.1. Introduction
- 9.2. Poultry Quality Inspection
- 9.3. Color Imaging for Quality Inspection
- 9.4. Spectral Imaging
- 9.5. Poultry Image Classifications
Chapter 10. Quality Evaluation of Seafoods
- 10.1. Introduction
- 10.2. New Methods
- 10.3. Color
- 10.4. Automation
- 10.5. Conclusion and Outlook
Part 3. Quality Evaluation of Fruit and Vegetables
Chapter 11. Quality Evaluation of Apples
- 11.1. Introduction
- 11.2. Detection of Surface Defects
- 11.3. Detection of Internal Defects
- 11.4. Evaluation of Texture and Flavor
- 11.5. Quality Evaluation Based on Optical Properties of Apples
- 11.6. In-Orchard Sorting and Grading of Apples
- 11.7. Future Trends
Chapter 12. Quality Evaluation of Citrus Fruits
- 12.1. Introduction
- 12.2. Analysis of Visible Images for Automatic Citrus Fruit Inspection
- 12.3. Quality Inspection Using Nonstandard Computer Vision
- 12.4. Internal Quality Inspection
Chapter 13. Quality Evaluation of Strawberry
- 13.1. Introduction
- 13.2. Grading of Size, Shape, and Ripeness
- 13.3. Detection of Bruises and Fecal Contamination
- 13.4. Estimation of Firmness and Soluble Solids Content
- 13.5. Further Challenges
Chapter 14. Classification and Quality Evaluation of Table Olives
- 14.1. Introduction
- 14.2. Table Olive Classification
- 14.3. Application of Computer Vision
- 14.4. Industrial Applications
Chapter 15. Grading of Potatoes
- 15.1. Introduction
- 15.2. Surface Potato Defects
- 15.3. Potato Classification
- 15.4. Applications
Part 4. Quality Evaluation of Grains
Chapter 16. Wheat Quality Evaluation
- 16.1. Introduction
- 16.2. Machine Vision
- 16.3. Soft X-Ray Imaging
- 16.4. Near Infrared Spectroscopy (NIRS) and Hyperspectral Imaging
- 16.5. Thermal Imaging
- 16.6. Potential Practical Applications
Chapter 17. Quality Evaluation of Rice
- 17.1. Introduction
- 17.2. Quality of Rice
- 17.3. Quality Evaluation of Raw Rice
- 17.4. Quality Evaluation of Cooked Rice
- 17.5. Quality Evaluation of Rice-Related Products
Chapter 18. Quality Evaluation of Corn/Maize
- 18.1. Introduction
- 18.2. Corn
- 18.3. Machine Vision Determination of Corn Quality
Part 5. Quality Evaluation of Other Foods
Chapter 19. Quality Evaluation of Pizzas
- 19.1. Introduction
- 19.2. Pizza Base Production
- 19.3. Pizza Sauce Spread
- 19.4. Pizza Toppings Applied
- Nomenclature
Chapter 20. Cheese Quality Evaluation
- 20.1. Introduction
- 20.2. Cheese Quality Attributes
Chapter 21. Quality Evaluation of Bakery Products
- 21.1. Introduction
- 21.2. Quality Characteristics of Bakery Products
- 21.3. Computer Vision Inspection of Bakery Products
- Nomenclature
Chapter 22. Quality Evaluation and Control of Potato Chips
- 22.1. Introduction
- 22.2. Computer Vision
- 22.3. Image Features
- 22.4. Applications
- 22.5. Fried Potato Sorting
- Edition: 2
- Published: April 27, 2016
- Language: English
DS
Da-Wen Sun
Dr. Da-Wen Sun is internationally recognized for his leadership in food engineering research and education and is a highly respected journal editor. He is the recipient of numerous awards and honors including election to the Royal Irish Academy in 2010, selection as a Member of Academia Europaea (The Academy of Europe) in 2011, induction as a Fellow of International Academy of Food Science and Technology in 2012, recipient of the International Association for Food Protection (IAFP) Freezing Research Award in 2013, recipient of the International Association of Engineering and Food (IAEF) Lifetime Achievement Award in 2015, and named as a Thomson Reuters Highly Cited Researcher in 2015.
Dr. Da-Wen Sun is internationally recognized for his leadership in food engineering research and education and a highly respected journal editor. He is the recipient of numerous awards and honors including election to the Royal Irish Academy in 2010, selection as a Member of Academia Europaea (The Academy of Europe) in 2011, induction as a Fellow of International Academy of Food Science and Technology in 2012, the International Association for Food Protection (IAFP) Freezing Research Award in 2013, the International Association of Engineering and Food (IAEF) Lifetime Achievement Award in 2015 and naming as 2015 Thomson Reuters Highly Cited Researcher. His many scholarly works have become standard reference materials for researchers in the areas of computer vision/hyperspectral imaging, computational fluid dynamics modelling, and vacuum cooling. Results of his work have been published in more than 400 peer-reviewed journal papers (Web of Science h-index = 66), among them; thirty papers have been selected by ESI as highly-cited papers, ranking him first in the world in Agricultural Sciences.
Affiliations and expertise
Food Refrigeration and Computerised Food Technology, University College Dublin, National University of Ireland, Belfield, Dublin, IrelandRead Computer Vision Technology for Food Quality Evaluation on ScienceDirect