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Titre :	Bio-imaging : principles, techniques, and applications Ajouter au panier
Auteur(s) :	R. Vadivambal Digvir S. Jayas
Type de document :	Livre
Sujets :	AGRICULTURE ; PRODUIT AGRICOLE ; INDUSTRIE ALIMENTAIRE ; DONNEES STATISTIQUES ; PROPRIETE OPTIQUE ; COULEUR ; PRODUIT ALIMENTAIRE ; ANALYSE D'IMAGE ; AUTOMATISATION ; BIOCAPTEUR ; RESEAU DE NEURONES
Résumé :	Highlights the Emergence of Image Processing in Food and Agriculture In addition to uses specifically related to health and other industries, biological imaging is now being used for a variety of applications in food and agriculture. Bio-Imaging: Principles, Techniques, and Applications fully details and outlines the processes of bio-imaging applicable to food and agriculture, and connects other bio-industries, as well as relevant topics. Due to the noncontact and nondestructive nature of the technology, biological imaging uses unaltered samples, and allows for internal quality evaluation and the detection of defects. Compared to conventional methods, biological imaging produces results that are more consistent and reliable, and can ensure quality monitoring for a variety of practice[...] Highlights the Emergence of Image Processing in Food and Agriculture In addition to uses specifically related to health and other industries, biological imaging is now being used for a variety of applications in food and agriculture. Bio-Imaging: Principles, Techniques, and Applications fully details and outlines the processes of bio-imaging applicable to food and agriculture, and connects other bio-industries, as well as relevant topics. Due to the noncontact and nondestructive nature of the technology, biological imaging uses unaltered samples, and allows for internal quality evaluation and the detection of defects. Compared to conventional methods, biological imaging produces results that are more consistent and reliable, and can ensure quality monitoring for a variety of practices used in food and agriculture industries as well as many other biological industries. The book highlights every imaging technique available along with their components, image acquisition procedures, advantages, and comparisons to other approaches. Describes essential components of imaging technique in great detail Incorporates case studies in appropriate chapters Contains a wide range of applications from a number of biological fields Bio-Imaging: Principles, Techniques, and Applications focuses on the imaging techniques for biological materials and the application of biological imaging. This technology, which is quickly becoming a standard practice in agriculture and food-related industries, can aid in enhanced process efficiency, quality assurance, and food safety management overall.
Editeur(s) :	Boca Raton : CRC Press
Date de publication :	2016
Format :	1 vol. (XVIII-381 p.) / ill. en coul., couv. ill. en coul. / 26 cm
Note(s) :	Bibliogr. p. 313-359. Index
Table des matières :	Chapter 1 Introduction to bio-imaging 1.1 Introduction 1.1.1 What is bio-imaging? 1.1.2 Need for bio-imaging 1.1.3 Ease of use and cost effectiveness of bio-imaging 1.2 Current applications 1.3 Research studies and potential future applications 1.3.1 Agriculture 1.3.2 Grain 1.3.3 Fruits and vegetables 1.3.4 Other foods 1.3.5 Meat 1.3.6 Aquaculture 1.3.7 Packaged food 1.4 Conclusions Chap[...] Chapter 1 Introduction to bio-imaging 1.1 Introduction 1.1.1 What is bio-imaging? 1.1.2 Need for bio-imaging 1.1.3 Ease of use and cost effectiveness of bio-imaging 1.2 Current applications 1.3 Research studies and potential future applications 1.3.1 Agriculture 1.3.2 Grain 1.3.3 Fruits and vegetables 1.3.4 Other foods 1.3.5 Meat 1.3.6 Aquaculture 1.3.7 Packaged food 1.4 Conclusions Chapter 2 Image acquisition and processing 2.1 Introduction 2.2 Image acquisition 2.2.1 Illumination 2.2.2 Image acquisition using different types of sensors 2.2.2.1 Image acquisition using X-ray 2.2.2.2 Thermal imaging detectors 2.2.2.3 MRI 2.3 Image preprocessing 2.3.1 Local preprocessing 2.3.2 Image restoration 2.3.3 Noise 2.4 Image segmentation 2.4.1 Thresholding 2.4.1.1 Otsu’s thresholding 2.4.2 Region-based segmentation 2.4.3 Edge-based (gradient-based) segmentation 2.5 Image representation and description 2.5.1 Methods of shape representation 2.5.1.1 Contour-based global shape representation 2.5.1.2 Region-based shape representation 2.5.2 Feature extraction 2.5.2.1 Morphological features 2.5.2.2 Color features 2.5.2.3 Textural features 2.5.3 Classification of food based on shape and size features 2.5.4 Classification of food based on texture and color features Chapter 3 Classification: Statistical and neural network 3.1 Introduction 3.1.1 Classifiers for pattern recognition 3.2 Artificial neutral networks 3.2.1 Basic concept of ANNs 3.2.2 Categorization of ANNs 3.2.2.1 Multilayer neural network 3.2.2.2 Kohonen network or self-organizing map 3.2.2.3 Radial basis function neural network 3.2.2.4 General regression neural network 3.2.2.5 Multilayer perceptron 3.2.2.6 Probabilistic neural network 3.2.2.7 Deep learning 3.2.3 Potential of neural network classifiers for image classification related to food and agriculture applications 3.3 Statistical classifiers 3.3.1 Different types of statistical classifiers 3.3.1.1 Linear and quadratic discriminant analysis 3.3.1.2 Mahalanobis distance classifier 3.3.1.3 K-nearest neighbor 3.3.1.4 Support vector machine 3.3.2 Potential of statistical classifiers for image classification related to food and agriculture applications 3.3.3 Studies involving both statistical and neural network classifiers 3.4 Comparison of statistical and neural network classifiers 3.5 Fuzzy logic 3.6 Conclusions Chapter 4 Imaging in the visible spectrum 4.1 Introduction 4.2 Image sensors and components of an imaging system 4.2.1 Sensors 4.2.1.1 Charge-coupled device sensors 4.2.1.2 Complementary metal-oxide silicon sensors 4.2.2 Performance of image sensors 4.2.3 Comparison of CCD and CMOS sensors 4.2.4 Line and area scan imaging 4.2.5 Comparison of line and area scan imaging 4.2.6 Components of line and area scan imaging 4.3 Applications of digital imaging in the visible spectrum 4.3.1 Agriculture 4.3.1.1 Weed control 4.3.1.2 Quality of seed germination 4.3.1.3 Disease detection in trees 4.3.1.4 Quality grading of wood 4.3.1.5 Fruit recognition 4.3.1.6 Cereal grain 4.3.2 Applications of visible imaging for fresh produce and other food products 4.3.2.1 Potato 4.3.2.2 Apple 4.3.2.3 Strawberry 4.3.2.4 Raisins 4.3.2.5 Cantaloupe 4.3.2.6 Mandarin 4.3.2.7 Tomato 4.3.3 Color measurements 4.3.4 Quality evaluation of other food products using digital imaging 4.3.4.1 Ready-to-eat meals 4.3.4.2 Egg 4.3.4.3 Beef 4.3.4.4 Yeast biomass 4.3.4.5 Bakery 4.3.4.6 Pasta 4.3.5 Inspection of packaging of food components in bottles 4.3.6 Engineering applications of digital imaging in the visible spectrum 4.4 Advantages, limitations, and future of imaging in the visible spectrum 4.4.1 Advantages 4.4.2 Limitations 4.4.3 Future Chapter 5 Hyperspectral imaging 5.1 Introduction 5.2 Hyperspectral imaging 5.2.1 Principle 5.2.2 Instrumentation for hyperspectral imaging 5.3 Applications of hyperspectral imaging techniques 5.3.1 Agriculture 5.3.2 Wood 5.3.3 Grain 5.3.3.1 Sprout- and midge-damaged kernels 5.3.3.2 Kernel hardness and wheat class identification 5.3.3.3 Insect and fungal damage detection 5.3.4 Food 5.3.4.1 Fruits and vegetables 5.3.4.2 Nuts and beans 5.3.4.3 Meat 5.3.4.4 Aquaculture 5.3.4.5 Sanitation in food industry 5.3.5 Engineering 5.3.6 Medicine 5.3.6.1 Cancer 5.3.6.2 Diabetes 5.3.6.3 Blood vessel detection 5.3.6.4 Counterfeit drug detection 5.4 Advantages, limitations, and future of hyperspectral imaging 5.4.1 Advantages 5.4.2 Limitations 5.4.3 Future Chapter 6 Thermal imaging 6.1 Introduction 6.2 Principle and components of thermal imaging 6.2.1 Principle 6.2.2 Components 6.2.2.1 Infrared lens 6.2.2.2 Detector 6.2.2.3 Video signal processing 6.2.2.4 Display 6.2.2.5 Important factors to be considered in selection of camera 6.3 Applications of thermal imaging 6.3.1 Agriculture 6.3.1.1 Soil water status 6.3.1.2 Estimate canopy temperature and identify plant stress 6.3.1.3 Measurement of leaf temperature 6.3.1.4 Insect and fungal damage in grain 6.3.2 Food 6.3.2.1 Quality of fruits and vegetables 6.3.2.2 Harvesting and yield estimation 6.3.2.3 Detection of foreign bodies in food 6.3.2.4 Meat 6.3.3 Applications of thermal imaging in engineering 6.3.4 Applications of thermal imaging in bio-medicine 6.3.4.1 Cancer/tumor 6.3.4.2 Diabetes 6.3.4.3 Pediatrics 6.3.4.4 Arthritis and arteriosclerosis 6.3.4.5 Sports medicine 6.3.4.6 Ophthalmology 6.3.4.7 Other medical and pharmaceutical applications 6.4 Advantages, limitations, and future of thermal imaging 6.4.1 Advantages 6.4.2 Limitations 6.4.3 Future Chapter 7 X-ray imaging 7.1 Introduction 7.2 Components and principles of an X-ray imaging system 7.2.1 X-ray source 7.2.2 Image intensifier 7.2.3 Detectors and camera 7.2.4 Image processing system (A/D converter, frame grabber, and computer) 7.2.5 Principle 7.2.6 X-ray machine specification and type 7.2.6.1 Vertical beam X-ray system 7.2.6.2 Horizontal beam X-ray system 7.2.6.3 Combination beam system 7.3 Present applications in bio-industries 7.3.1 Detection of contamination 7.3.2 Shell removal from whelk 7.3.3 Inspection of pumped products 7.3.4 Determination of composition 7.3.5 Detection of defects in products 7.3.6 Monitoring packaging and sealing 7.4 Agricultural and food product inspection and quality evaluation 7.4.1 X-ray quarantine for agricultural products 7.4.2 Dynamic X-ray imaging 7.4.3 Quantification and flow rate measurements 7.4.4 Detection of insect infestation 7.4.4.1 Grain 7.4.4.2 Produce 7.4.4.3 Nuts 7.4.5 Quality evaluation of agricultural products using X-ray imaging 7.4.5.1 Detection of body composition 7.4.5.2 Aquaculture (bone detection) 7.4.5.3 Wood 7.5 Medical applications of X-ray 7.6 Applications of X-ray imaging in engineering industry 7.7 Advantages and limitations of product inspection using X-rays 7.7.1 Advantages 7.7.2 Limitations 7.8 Cost comparison, safety, and future applications 7.8.1 Economics 7.8.2 Safety 7.8.3 Shielding 7.8.4 Future applications Chapter 8 X-ray computed tomography imaging 8.1 Introduction 8.2 Computed tomography 8.2.1 Principle of X-ray CT 8.2.2 Common configurations of X-ray CT 8.2.3 Instrumentation or components of X-ray CT 8.2.3.1 X-ray source 8.2.3.2 X-ray detectors 8.2.3.3 Image processor (digital acquisition system) 8.2.4 Microtomography 8.3 Applications of X-ray CT 8.3.1 Forestry and agriculture 8.3.1.1 Knot detection in wood 8.3.1.2 Assessment of wood decay 8.3.1.3 Tree ring measurement 8.3.1.4 Assessment of soil structure 8.3.1.5 Hydrology 8.3.1.6 Plant development study 8.3.1.7 Grain 8.3.2 Food 8.3.2.1 Fruits 8.3.2.2 Ripening assessment 8.3.2.3 Cereal products 8.3.2.4 Bread 8.3.2.5 Frying of potato 8.3.2.6 Chocolate 8.3.2.7 Bouillon 8.3.2.8 Meat 8.3.3 Aquaculture 8.3.4 Livestock management 8.3.5 Engineering applications 8.3.6 Applications of X-ray CT in medicine 8.3.6.1 Cardiology 8.3.6.2 Lung and related diseases 8.3.6.3 CT colonography 8.4 Advantages, limitations, and future of X-ray CT 8.4.1 Advantages 8.4.2 Limitations 8.4.3 Future Chapter 9 Magnetic resonance imaging 9.1 Introduction 9.2 Magnetic resonance imaging 9.2.1 Principle 9.2.2 Components of MRI scanner 9.2.2.1 Magnet 9.2.2.2 Radio frequency coil 9.2.2.3 Gradient coil 9.2.2.4 Processor 9.3 Applications of MRI 9.3.1 Agriculture 9.3.1.1 Soil 9.3.1.2 Wood 9.3.1.3 Cereal grains 9.3.2 Aquaculture 9.3.2.1 Effect of freezing 9.3.2.2 Evaluation of quality 9.3.2.3 Sex determination and gonad development 9.3.3 Meat 9.3.3.1 Body composition 9.3.3.2 Fat content and quality evaluation 9.3.4 Food 9.3.4.1 Confectionery 9.3.4.2 Dairy food 9.3.4.3 Moisture migration 9.3.4.4 Detection of spoilage 9.3.5 Fruits and vegetables 9.3.5.1 Apple 9.3.5.2 Pomegranate 9.3.5.3 Tomato 9.3.5.4 Pears 9.3.5.5 Wine grapes 9.3.5.6 Avocado and cherry 9.3.5.7 Courgettes (zucchini) 9.3.5.8 Strawberry 9.3.6 Medical applications 9.3.6.1 Lung diseases 9.3.6.2 Cancer 9.3.6.3 Cardiac diseases 9.3.6.4 Kidney 9.3.6.5 Arthritis 9.3.6.6 MRI in tissue engineering 9.3.7 Engineering applications 9.4 Advantages, limitations, and future of MRI 9.4.1 Advantages 9.4.2 Limitations 9.4.3 Future Chapter 10 Optical coherence tomography imaging 10.1 Introduction 10.2 Principle of optical coherence tomography 10.3 Applications of OCT 10.3.1 Agriculture 10.3.1.1 Detection of viral infection 10.3.1.2 Seed structure 10.3.1.3 Hull thickness 10.3.1.4 Plant tissue 10.3.1.5 Rice varieties 10.3.2 Fruits and vegetables 10.3.2.1 Botanical samples 10.3.2.2 Defects in onion 10.3.2.3 Wax coating in apple 10.3.2.4 Microstructure of apple peel 10.3.2.5 Fungal disease detection 10.3.2.6 Extruded cereals 10.3.2.7 Quality control of foil 10.3.3 Applications of OCT in engineering 10.3.3.1 Aerospace materials 10.3.3.2 Printed electronic board 10.3.3.3 Glass fiber-reinforced polymer 10.3.3.4 Subsurface defect detection 10.3.3.5 Paper making 10.3.4 Medical applications of OCT 10.3.4.1 Cancer 10.3.4.2 Cardiology 10.3.4.3 Dentistry 10.3.4.4 Pharmacy 10.4 Advantages, limitations, and future of OCT 10.4.1 Advantages 10.4.2 Limitations 10.4.3 Future Chapter 11 Imaging-based automation in the food and agriculture industry 11.1 Introduction 11.2 Need for automation with focus on imaging 11.2.1 Typical product flow in food processing industry 11.3 Current uses of imaging-based automation in agriculture and food industries 11.3.1 Agriculture 11.3.1.1 Weeding 11.3.1.2 Identification of plants in field/harvesting 11.3.1.3 Grading/sorting 11.3.2 Food 11.3.2.1 Bakery inspection 11.3.2.2 Pizza/tortilla 11.3.2.3 Cheese 11.3.2.4 Monitoring fill levels 11.3.2.5 Label inspection and validation 11.3.2.6 Sealing inspection 11.3.2.7 To determine weak chain link in conveyer 11.3.2.8 Meat 11.4 Advantages and limitations of machine vision technology 11.4.1 Advantages 11.4.2 Concerns and limitations 11.4.3 Costs 11.4.3.1 Maintenance of machine vision systems 11.4.3.2 Myths about machine vision 11.5 Future of machine vision in food and agriculture 11.5.1 Machine vision systems based on smart cameras versus PCs 11.5.2 Growth of machine vision
Langue(s) :	Anglais
Identifiant :	978-1-4665-9367-1
Lien vers la notice :	https://infodoc.agroparistech.fr/index.php?lvl=notice_display&id=185878

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