In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.

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

Hyperspectral imaging or imaging spectroscopy is a novel technology for acquiring and analysing an image of a real scene by computers and other devices in order to obtain quantitative information for quality evaluation and process control. Image processing and analysis is the core technique in computer vision. With the continuous development in hardware and software for image processing and analysis, the application of hyperspectral imaging has been extended to the safety and quality evaluation of meat and produce. Especially in recent years, hyperspectral imaging has attracted much research and development attention, as a result rapid scientific and technological advances have increasingly taken place in food and agriculture, especially on safety and quality inspection, classification and evaluation of a wide range of food products, illustrating the great advantages of using the technology for objective, rapid, non-destructive and automated safety inspection as well as quality control. Therefore, as the first reference book in the area, Hyperspectral Imaging Technology in Food and Agriculture focuses on these recent advances. The book is divided into three parts, which begins with an outline of the fundamentals of the technology, followed by full covering of the application in the most researched areas of meats, fruits, vegetables, grains and other foods, which mostly covers food safety and quality as well as remote sensing applicable for crop production. Hyperspectral Imaging Technology in Food and Agriculture is written by international peers who have both academic and professional credentials, with each chapter addressing in detail one aspect of the relevant technology, thus highlighting the truly international nature of the work. Therefore the book should provide the engineer and technologist working in research, development, and operations in the food and agricultural industry with critical, comprehensive and readily accessible information on the art and science of hyperspectral imaging technology. It should also serve as an essential reference source to undergraduate and postgraduate students and researchers in universities and research institutions.

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

This book is about the novel aspects and future trends of the hyperspectral imaging in agriculture, food, and environment. The topics covered by this book are hyperspectral imaging and their applications in the nondestructive quality assessment of fruits and vegetables, hyperspectral imaging for assessing quality and safety of meat, multimode hyperspectral imaging for food quality and safety, models fitting to pattern recognition in hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization method to process hyperspectral image, and soil contamination mapping with hyperspectral imagery. This book is a general reference work for students, professional engineers, and readers with interest in the subject.

A comprehensive source of in-depth information provided on existing and emerging food technologies based on the electromagnetic spectrum Electromagnetic Technologies in Food Science examines various methods employed in food applications that are based on the entire electromagnetic (EM) spectrum. Focusing on recent advances and challenges in food science and technology, this is an up-to-date volume that features vital contributions coming from an international panel of experts who have shared both fundamental and advanced knowledge of information on the dosimetry methods, and on potential applications of gamma irradiation, electron beams, X-rays, radio and microwaves, ultraviolet, visible, pulsed light, and more. Organized into four parts, the text begins with an accessible overview of the physics of the electromagnetic spectrum, followed by discussion on the application of the EM spectrum to non-thermal food processing. The physics of infrared radiation, microwaves, and other advanced heating methods are then deliberated in detail—supported by case studies and examples that illustrate a range of both current and potential applications of EM-based methods. The concluding section of the book describes analytical techniques adopted for quality control, such as hyperspectral imaging, infrared and Raman spectroscopy. This authoritative book resource: Covers advanced theoretical knowledge and practical applications on the use of EM spectrum as novel methods in food processing technology Discusses the latest progress in developing quality control methods, thus enabling the control of continuous fast-speed processes Explores future challenges and benefits of employing electromagnetic spectrum in food technology applications Addresses emerging processing technologies related to improving safety, preservation, and overall quality of various food commodities Electromagnetic Technologies in Food Science is an essential reading material for undergraduate and graduate students, researchers, academics, and agri-food professionals working in the area of food preservation, novel food processing techniques and sustainable food production.

The first book in this rapidly expanding area, Computer Vision Technology for Food Quality Evaluation thoroughly discusses the latest advances in image processing and analysis. Computer vision has attracted much research and development attention in recent years and, as a result, significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. This unique work provides engineers and technologists working in research, development, and operations in the food industry with critical, comprehensive and readily accessible information on the art and science of computer vision technology. Undergraduate and postgraduate students and researchers in universities and research institutions will also find this an essential reference source. · Discusses novel technology for recognizing objects and extracting quantitative information from digital images in order to provide objective, rapid, non-contact and non-destructive quality evaluation. · International authors with both academic and professional credentials address in detail one aspect of the relevant technology per chapter making this ideal for textbook use· Divided into three parts, it begins with an outline of the fundamentals of the technology, followed by full coverage of the application in the most researched areas of meats and other foods, fruits, vegetables and grains.