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
Author(s): Da-Wen Sun
Edition: 1
Publisher: Academic Press
Year: 2010
Language: English
Pages: 493
Tags: Информатика и вычислительная техника;Обработка медиа-данных;Обработка изображений;
Title page......Page 4
Copyright
......Page 5
Contents......Page 6
About the Editor......Page 8
Contributors......Page 10
Preface......Page 14
PART 1
Fundamentals......Page 16
INTRODUCTION......Page 18
RELATIONSHIP BETWEEN SPECTROSCOPY,IMAGING, AND HYPERSPECTRAL IMAGING......Page 20
FUNDAMENTALS OF HYPERSPECTRAL IMAGING......Page 26
CONFIGURATION OF HYPERSPECTRALIMAGING SYSTEM......Page 39
CALIBRATION OF HYPERSPECTRALIMAGING SYSTEM......Page 47
SPECTRAL DATA ANALYSIS AND CHEMOMETRICS......Page 51
CONCLUSIONS......Page 54
INTRODUCTION......Page 60
HYPERSPECTRAL IMAGE SPECTRALPREPROCESSING......Page 61
CONCLUSIONS......Page 85
HYPERSPECTRAL IMAGE CLASSIFICATION INFOOD: AN OVERVIEW......Page 94
OPTIMAL FEATURE AND BAND EXTRACTION......Page 96
CLASSIFICATIONS BASED ON FIRST- ANDSECOND-ORDER STATISTICS......Page 104
HYPERSPECTRAL IMAGE CLASSIFICATION USINGNEURAL NETWORKS......Page 106
KERNEL METHOD FOR HYPERSPECTRAL IMAGECLASSIFICATION......Page 107
CONCLUSIONS......Page 109
INTRODUCTION......Page 114
IMAGE ENHANCEMENT......Page 115
IMAGE SEGMENTATION......Page 124
OBJECT MEASUREMENT......Page 130
HYPERSPECTRAL IMAGING SOFTWARE......Page 133
CONCLUSIONS......Page 139
INTRODUCTION......Page 144
METHODS FOR HYPERSPECTRAL IMAGEACQUISITION......Page 146
INSTRUMENTS FOR CONSTRUCTINGHYPERSPECTRAL IMAGING SYSTEMS......Page 148
INSTRUMENTS FOR CALIBRATINGHYPERSPECTRAL IMAGING SYSTEMS......Page 174
CONCLUSIONS......Page 182
PART 2
Applications......Page 188
INTRODUCTION......Page 190
MEAT QUALITY EVALUATION TECHNIQUES......Page 193
HYPERSPECTRAL IMAGING SYSTEM......Page 201
HYPERSPECTRAL IMAGING FOR MEATQUALITY EVALUATION......Page 207
CONCLUSIONS......Page 245
INTRODUCTION......Page 256
CURRENT UNITED STATES POULTRYINSPECTION PROGRAM......Page 258
DEVELOPMENT OF VIS/NIR SPECTROSCOPYBASEDPOULTRY INSPECTION SYSTEMS......Page 260
DEVELOPMENT OF TARGET-TRIGGERED IMAGINGFOR ON-LINE POULTRY INSPECTION......Page 264
DEVELOPMENT OF LINE-SCAN IMAGINGFOR ON-LINE POULTRY INSPECTION......Page 270
CONCLUSIONS......Page 282
INTRODUCTION......Page 288
SUBJECTIVE ROI ON HYPERSPECTRAL IMAGESFOR FISH FRESHNESS IDENTIFICATION......Page 292
MORPHOMETRIC SUPERIMPOSITION FORTOPOGRAPHICAL FISH FRESHNESS COMPARISON......Page 297
CONCLUSIONS......Page 303
INTRODUCTION......Page 310
GENERAL METHODS TO DETECT BRUISE DAMAGE......Page 312
HYPERSPECTRAL IMAGING TECHNOLOGY......Page 314
AN EXAMPLE OF A HYPERSPECTRAL SYSTEMDEVELOPED FOR EARLY DETECTION OF APPLEBRUISE DAMAGE......Page 320
CONCLUSIONS......Page 330
INTRODUCTION......Page 336
A FIRST APPROACH TO AUTOMATIC INSPECTIONOF CITRUS: MULTISPECTRAL IDENTIFICATION OFBLEMISHES ON CITRUS PEEL......Page 338
CONSIDERATIONS ON HYPERSPECTRALIMAGE ACQUISITION FOR CITRUS......Page 341
DESCRIPTION AND TUNING OFA HYPERSPECTRAL SYSTEM FOR CITRUSFRUIT INSPECTION......Page 346
AUTOMATIC EARLY DETECTION OF ROTTENFRUIT USING HYPERSPECTRAL IMAGE ANALYSIS......Page 354
CONCLUSIONS......Page 360
INTRODUCTION......Page 364
VISUALIZATION BY VISIBLE WAVELENGTHREGION......Page 365
VISUALIZATION BY SUGAR ABSORPTIONWAVELENGTH......Page 371
CONCLUSIONS......Page 380
INTRODUCTION......Page 384
HYPERSPECTRAL IMAGING COMPARED TOCOLOR VISION......Page 386
MEASURING COMPOUND DISTRIBUTION INRIPENING TOMATOES......Page 394
ON-LINE UNSUPERVISED MEASUREMENT OFTOMATO MATURITY......Page 397
HYPERSPECTRAL IMAGE ANALYSIS FORMODELING TOMATO MATURITY......Page 402
CONCLUSIONS......Page 413
INTRODUCTION......Page 418
HYPERSPECTRAL IMAGING OF MUSHROOMS......Page 420
CONCLUSIONS......Page 442
INTRODUCTION......Page 446
DETECTION OF EXTERNAL BRUISE......Page 448
DETECTION OF INTERNAL DEFECT......Page 453
CONCLUSIONS......Page 460
INTRODUCTION......Page 464
CLASSIFICATION METHODS......Page 467
NIR HYPERSPECTRAL IMAGING......Page 470
WHEAT CLASSIFICATION BY NIRHYPERSPECTRAL IMAGING......Page 474
CHALLENGES TO THE HSI TECHNOLOGY......Page 479
CONCLUSION......Page 480
Index......Page 486
