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Today, the scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Advanced Image Processing Techniques and Applications is an essential reference publication for the latest research on digital image processing advancements. Featuring expansive coverage on a broad range of topics and perspectives, such as image and video steganography, pattern recognition, and artificial vision, this publication is ideally designed for scientists, professionals, researchers, and academicians seeking current research on solutions for new challenges in image processing.
Book Synopsis Advanced Image Processing Techniques and Applications by : Kumar, N. Suresh
Download or read book Advanced Image Processing Techniques and Applications written by Kumar, N. Suresh and published by IGI Global. This book was released on 2017-02-10 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, the scope of image processing and recognition has broadened due to the gap in scientific visualization. Thus, new imaging techniques have developed, and it is imperative to study this progression for optimal utilization. Advanced Image Processing Techniques and Applications is an essential reference publication for the latest research on digital image processing advancements. Featuring expansive coverage on a broad range of topics and perspectives, such as image and video steganography, pattern recognition, and artificial vision, this publication is ideally designed for scientists, professionals, researchers, and academicians seeking current research on solutions for new challenges in image processing.
The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.
Book Synopsis Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by : Pramod K. Varshney
Download or read book Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data written by Pramod K. Varshney and published by Springer Science & Business Media. This book was released on 2004-08-12 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.
Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.
Book Synopsis Image Processing by : Tinku Acharya
Download or read book Image Processing written by Tinku Acharya and published by John Wiley & Sons. This book was released on 2005-10-03 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering.
This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others. The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning,dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts. The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision.
Book Synopsis Advanced Image and Video Processing Using MATLAB by : Shengrong Gong
Download or read book Advanced Image and Video Processing Using MATLAB written by Shengrong Gong and published by Springer. This book was released on 2018-08-21 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others. The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning,dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts. The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision.
This textbook is the third of three volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on which to build, and practitioners in search of critical analysis and concrete implementations of the most important techniques. This volume builds upon the introductory material presented in the first two volumes with additional key concepts and methods in image processing. Features: practical examples and carefully constructed chapter-ending exercises; real implementations, concise mathematical notation, and precise algorithmic descriptions designed for programmers and practitioners; easily adaptable Java code and completely worked-out examples for easy inclusion in existing applications; uses ImageJ; provides a supplementary website with the complete Java source code, test images, and corrections; additional presentation tools for instructors including a complete set of figures, tables, and mathematical elements.
Book Synopsis Principles of Digital Image Processing by : Wilhelm Burger
Download or read book Principles of Digital Image Processing written by Wilhelm Burger and published by Springer Science & Business Media. This book was released on 2013-11-18 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is the third of three volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on which to build, and practitioners in search of critical analysis and concrete implementations of the most important techniques. This volume builds upon the introductory material presented in the first two volumes with additional key concepts and methods in image processing. Features: practical examples and carefully constructed chapter-ending exercises; real implementations, concise mathematical notation, and precise algorithmic descriptions designed for programmers and practitioners; easily adaptable Java code and completely worked-out examples for easy inclusion in existing applications; uses ImageJ; provides a supplementary website with the complete Java source code, test images, and corrections; additional presentation tools for instructors including a complete set of figures, tables, and mathematical elements.
This book covers the technology of digital image processing in various fields with big data and their applications. Readers will understand various technologies and strategies used in digital image processing as well as handling big data, using machine-learning techniques. This book will help to improve the skills of students and researchers in such fields as engineering, agriculture, and medical imaging. There is a need to be able to understand and analyse the latest developments of digital image technology. As such, this book will cover: · Applications such as biomedical science and biometric image processing, content-based image retrieval, remote sensing, pattern recognition, shape and texture analysis · New concepts in color interpolation to produce the full color from the sub-pattern bare pattern color prevalent in today's digital cameras and other imaging devices · Image compression standards that are needed to serve diverse applications · Applications of remote sensing, medical science, traffic management, education, innovation, and analysis in agricultural design and image processing · Both soft and hard computing approaches at great length in relation to major image processing tasks · The direction and development of current and future research in many areas of image processing · A comprehensive bibliography for additional research (integrated within the framework of the book) This book focuses not only on theoretical and practical knowledge in the field but also on the traditional and latest tools and techniques adopted in image processing and data science. It also provides an indispensable guide to a wide range of basic and advanced techniques in the fields of image processing and data science.
Book Synopsis Advanced Digital Image Processing and Its Applications in Big Data by : Ankur Dumka
Download or read book Advanced Digital Image Processing and Its Applications in Big Data written by Ankur Dumka and published by CRC Press. This book was released on 2020-12-09 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the technology of digital image processing in various fields with big data and their applications. Readers will understand various technologies and strategies used in digital image processing as well as handling big data, using machine-learning techniques. This book will help to improve the skills of students and researchers in such fields as engineering, agriculture, and medical imaging. There is a need to be able to understand and analyse the latest developments of digital image technology. As such, this book will cover: · Applications such as biomedical science and biometric image processing, content-based image retrieval, remote sensing, pattern recognition, shape and texture analysis · New concepts in color interpolation to produce the full color from the sub-pattern bare pattern color prevalent in today's digital cameras and other imaging devices · Image compression standards that are needed to serve diverse applications · Applications of remote sensing, medical science, traffic management, education, innovation, and analysis in agricultural design and image processing · Both soft and hard computing approaches at great length in relation to major image processing tasks · The direction and development of current and future research in many areas of image processing · A comprehensive bibliography for additional research (integrated within the framework of the book) This book focuses not only on theoretical and practical knowledge in the field but also on the traditional and latest tools and techniques adopted in image processing and data science. It also provides an indispensable guide to a wide range of basic and advanced techniques in the fields of image processing and data science.
The book explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc. The security features of image processing like image watermarking and image encryption etc. are also discussed in this book. This book will be useful for those who are working in the field of image processing, pattern recognition, and security for digital images. This book targets researchers, academicians, industry, and professionals from R&D organizations, and students, healthcare professionals working in the field of medical imaging, telemedicine, cybersecurity, data scientist, artificial intelligence, image processing, digital hospital, intelligent medicine.
Book Synopsis Advance Concepts of Image Processing and Pattern Recognition by : Narendra Kumar
Download or read book Advance Concepts of Image Processing and Pattern Recognition written by Narendra Kumar and published by Springer Nature. This book was released on 2022-02-21 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc. The security features of image processing like image watermarking and image encryption etc. are also discussed in this book. This book will be useful for those who are working in the field of image processing, pattern recognition, and security for digital images. This book targets researchers, academicians, industry, and professionals from R&D organizations, and students, healthcare professionals working in the field of medical imaging, telemedicine, cybersecurity, data scientist, artificial intelligence, image processing, digital hospital, intelligent medicine.
"Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution.
Book Synopsis Advanced Image Acquisition, Processing Techniques and Applications by : Dimitrios Ventzas
Download or read book Advanced Image Acquisition, Processing Techniques and Applications written by Dimitrios Ventzas and published by BoD – Books on Demand. This book was released on 2012-03-14 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Advanced Image Acquisition, Processing Techniques and Applications" is the first book of a series that provides image processing principles and practical software implementation on a broad range of applications. The book integrates material from leading researchers on Applied Digital Image Acquisition and Processing. An important feature of the book is its emphasis on software tools and scientific computing in order to enhance results and arrive at problem solution.
Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.
Book Synopsis Hands-On Image Processing with Python by : Sandipan Dey
Download or read book Hands-On Image Processing with Python written by Sandipan Dey and published by Packt Publishing Ltd. This book was released on 2018-11-30 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key FeaturesPractical coverage of every image processing task with popular Python librariesIncludes topics such as pseudo-coloring, noise smoothing, computing image descriptorsCovers popular machine learning and deep learning techniques for complex image processing tasksBook Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learnPerform basic data pre-processing tasks such as image denoising and spatial filtering in PythonImplement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in PythonDo morphological image processing and segment images with different algorithmsLearn techniques to extract features from images and match imagesWrite Python code to implement supervised / unsupervised machine learning algorithms for image processingUse deep learning models for image classification, segmentation, object detection and style transferWho this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No prior knowledge of the image processing techniques is expected.
This book presents a study of the use of optimization algorithms in complex image processing problems. The problems selected explore areas ranging from the theory of image segmentation to the detection of complex objects in medical images. Furthermore, the concepts of machine learning and optimization are analyzed to provide an overview of the application of these tools in image processing. The material has been compiled from a teaching perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, and can be used for courses on Artificial Intelligence, Advanced Image Processing, Computational Intelligence, etc. Likewise, the material can be useful for research from the evolutionary computation, artificial intelligence and image processing communities.
Book Synopsis Advances and Applications of Optimised Algorithms in Image Processing by : Diego Oliva
Download or read book Advances and Applications of Optimised Algorithms in Image Processing written by Diego Oliva and published by Springer. This book was released on 2016-11-21 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a study of the use of optimization algorithms in complex image processing problems. The problems selected explore areas ranging from the theory of image segmentation to the detection of complex objects in medical images. Furthermore, the concepts of machine learning and optimization are analyzed to provide an overview of the application of these tools in image processing. The material has been compiled from a teaching perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, and can be used for courses on Artificial Intelligence, Advanced Image Processing, Computational Intelligence, etc. Likewise, the material can be useful for research from the evolutionary computation, artificial intelligence and image processing communities.
