Sun Hyperspectral Imaging for Food Quality Analysis and Control

1. Auflage 2010
ISBN: 978-0-08-088628-2
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: 6 - ePub Watermark

E-Book, Englisch, 496 Seiten

Based on the integration of computer vision and spectrscopy techniques, hyperspectral imaging is a novel technology for obtaining both spatial and spectral information on a product. Used for nearly 20 years in the aerospace and military industries, more recently hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods of non-destructive food quality analysis and control. Hyperspectral Imaging for Food Quality Analysis and Control provides the core information about how this proven science can be practically applied for food quality assessment, including information on the equipment available and selection of the most appropriate of those instruments. Additionally, real-world food-industry-based examples are included, giving the reader important insights into the actual application of the science in evaluating food products. - Presentation of principles and instruments provides core understanding of how this science performs, as well as guideline on selecting the most appropriate equipment for implementation - Includes real-world, practical application to demonstrate the viability and challenges of working with this technology - Provides necessary information for making correct determination on use of hyperspectral imaging

Autoren/Hrsg.

Sun, Da-Wen

Inhaltsverzeichnis

1;Front Cover;1
2;Hyperspectral Imaging for FoodQuality Analysis and Control;4
3;Copyright;5
4;Contents;6
5;About the Editor;8
6;Contributors;10
7;Preface;14
8;PART 1Fundamentals;16
8.1;CHAPTER 1Principles of Hyperspectral Imaging Technology;18
8.1.1;INTRODUCTION;18
8.1.2;RELATIONSHIP BETWEEN SPECTROSCOPY,IMAGING, AND HYPERSPECTRAL IMAGING;20
8.1.3;FUNDAMENTALS OF HYPERSPECTRAL IMAGING;26
8.1.4;CONFIGURATION OF HYPERSPECTRALIMAGING SYSTEM;39
8.1.5;CALIBRATION OF HYPERSPECTRALIMAGING SYSTEM;47
8.1.6;SPECTRAL DATA ANALYSIS AND CHEMOMETRICS;51
8.1.7;CONCLUSIONS;54
8.2;CHAPTER 2Spectral Preprocessing and Calibration Techniques;60
8.2.1;INTRODUCTION;60
8.2.2;HYPERSPECTRAL IMAGE SPECTRALPREPROCESSING;61
8.2.3;CONCLUSIONS;85
8.3;CHAPTER 3Hyperspectral Image Classification Methods;94
8.3.1;HYPERSPECTRAL IMAGE CLASSIFICATION INFOOD: AN OVERVIEW;94
8.3.2;OPTIMAL FEATURE AND BAND EXTRACTION;96
8.3.3;CLASSIFICATIONS BASED ON FIRST- ANDSECOND-ORDER STATISTICS;104
8.3.4;HYPERSPECTRAL IMAGE CLASSIFICATION USINGNEURAL NETWORKS;106
8.3.5;KERNEL METHOD FOR HYPERSPECTRAL IMAGECLASSIFICATION;107
8.3.6;CONCLUSIONS;109
8.4;CHAPTER 4Hyperspectral Image Processing Techniques;114
8.4.1;INTRODUCTION;114
8.4.2;IMAGE ENHANCEMENT;115
8.4.3;IMAGE SEGMENTATION;124
8.4.4;OBJECT MEASUREMENT;130
8.4.5;HYPERSPECTRAL IMAGING SOFTWARE;133
8.4.6;CONCLUSIONS;139
8.5;CHAPTER 5Hyperspectral Imaging Instruments;144
8.5.1;INTRODUCTION;144
8.5.2;METHODS FOR HYPERSPECTRAL IMAGEACQUISITION;146
8.5.3;INSTRUMENTS FOR CONSTRUCTINGHYPERSPECTRAL IMAGING SYSTEMS;148
8.5.4;INSTRUMENTS FOR CALIBRATINGHYPERSPECTRAL IMAGING SYSTEMS;174
8.5.5;CONCLUSIONS;182
9;PART 2Applications;188
9.1;CHAPTER 6Meat Quality Assessment Using a Hyperspectral Imaging System;190
9.1.1;INTRODUCTION;190
9.1.2;MEAT QUALITY EVALUATION TECHNIQUES;193
9.1.3;HYPERSPECTRAL IMAGING SYSTEM;201
9.1.4;HYPERSPECTRAL IMAGING FOR MEATQUALITY EVALUATION;207
9.1.5;CONCLUSIONS;245
9.2;CHAPTER 7Automated Poultry Carcass Inspection by a Hyperspectral-Multispectral Line-Scan Imaging System;256
9.2.1;INTRODUCTION;256
9.2.2;CURRENT UNITED STATES POULTRYINSPECTION PROGRAM;258
9.2.3;DEVELOPMENT OF VIS/NIR SPECTROSCOPYBASEDPOULTRY INSPECTION SYSTEMS;260
9.2.4;DEVELOPMENT OF TARGET-TRIGGERED IMAGINGFOR ON-LINE POULTRY INSPECTION;264
9.2.5;DEVELOPMENT OF LINE-SCAN IMAGINGFOR ON-LINE POULTRY INSPECTION;270
9.2.6;CONCLUSIONS;282
9.3;CHAPTER 8Quality Evaluation of Fish by Hyperspectral Imaging;288
9.3.1;INTRODUCTION;288
9.3.2;SUBJECTIVE ROI ON HYPERSPECTRAL IMAGESFOR FISH FRESHNESS IDENTIFICATION;292
9.3.3;MORPHOMETRIC SUPERIMPOSITION FORTOPOGRAPHICAL FISH FRESHNESS COMPARISON;297
9.3.4;CONCLUSIONS;303
9.4;CHAPTER 9Bruise Detection of Apples Using Hyperspectral Imaging;310
9.4.1;INTRODUCTION;310
9.4.2;GENERAL METHODS TO DETECT BRUISE DAMAGE;312
9.4.3;HYPERSPECTRAL IMAGING TECHNOLOGY;314
9.4.4;AN EXAMPLE OF A HYPERSPECTRAL SYSTEMDEVELOPED FOR EARLY DETECTION OF APPLEBRUISE DAMAGE;320
9.4.5;CONCLUSIONS;330
9.5;CHAPTER 10Analysis of Hyperspectral Images of Citrus Fruits;336
9.5.1;INTRODUCTION;336
9.5.2;A FIRST APPROACH TO AUTOMATIC INSPECTIONOF CITRUS: MULTISPECTRAL IDENTIFICATION OFBLEMISHES ON CITRUS PEEL;338
9.5.3;CONSIDERATIONS ON HYPERSPECTRALIMAGE ACQUISITION FOR CITRUS;341
9.5.4;DESCRIPTION AND TUNING OFA HYPERSPECTRAL SYSTEM FOR CITRUSFRUIT INSPECTION;346
9.5.5;AUTOMATIC EARLY DETECTION OF ROTTENFRUIT USING HYPERSPECTRAL IMAGE ANALYSIS;354
9.5.6;CONCLUSIONS;360
9.6;CHAPTER 11Visualization of Sugar Distribution of Melons by Hyperspectral Technique;364
9.6.1;INTRODUCTION;364
9.6.2;VISUALIZATION BY VISIBLE WAVELENGTHREGION;365
9.6.3;VISUALIZATION BY SUGAR ABSORPTIONWAVELENGTH;371
9.6.4;CONCLUSIONS;380
9.7;CHAPTER 12Measuring Ripening of Tomatoes Using Imaging Spectrometry;384
9.7.1;INTRODUCTION;384
9.7.2;HYPERSPECTRAL IMAGING COMPARED TOCOLOR VISION;386
9.7.3;MEASURING COMPOUND DISTRIBUTION INRIPENING TOMATOES;394
9.7.4;ON-LINE UNSUPERVISED MEASUREMENT OFTOMATO MATURITY;397
9.7.5;HYPERSPECTRAL IMAGE ANALYSIS FORMODELING TOMATO MATURITY;402
9.7.6;CONCLUSIONS;413
9.8;CHAPTER 13Using Hyperspectral Imaging for Quality Evaluation ofnbspMushrooms;418
9.8.1;INTRODUCTION;418
9.8.2;HYPERSPECTRAL IMAGING OF MUSHROOMS;420
9.8.3;CONCLUSIONS;442
9.9;CHAPTER 14Hyperspectral Imaging fornbspDefect Detection of Pickling Cucumbers;446
9.9.1;INTRODUCTION;446
9.9.2;DETECTION OF EXTERNAL BRUISE;448
9.9.3;DETECTION OF INTERNAL DEFECT;453
9.9.4;CONCLUSIONS;460
9.10;CHAPTER 15Classification of Wheat Kernels Using Near-Infrared Reflectance Hyperspectral Imaging;464
9.10.1;INTRODUCTION;464
9.10.2;CLASSIFICATION METHODS;467
9.10.3;NIR HYPERSPECTRAL IMAGING;470
9.10.4;WHEAT CLASSIFICATION BY NIRHYPERSPECTRAL IMAGING;474
9.10.5;CHALLENGES TO THE HSI TECHNOLOGY;479
9.10.6;CONCLUSION;480
10;Index;486