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Author: Livia Cárdenas
Publisher: BRILL
Published: 2020-11-16
Total Pages: 574
ISBN-13: 9004440127
DOWNLOAD EBOOK →Textures of Images presents for the first time a fundamental analysis and synopsis of the printed relic-book genre. The author brings into focus the specific mediality and aesthetics of this kind of printed books between the Late Middle Ages and the Early Modern Period.
Author: Chih-Cheng Hung
Publisher: Springer
Published: 2019-06-05
Total Pages: 264
ISBN-13: 3030137732
DOWNLOAD EBOOK →This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks. This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.
Author: Jyotismita Chaki
Publisher: Springer Nature
Published: 2019-10-24
Total Pages: 100
ISBN-13: 9811508534
DOWNLOAD EBOOK →The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based. It also covers applications related to texture features, such as facial imaging. It is a valuable resource for machine vision researchers and practitioners in different application areas.
Author: Maria Petrou
Publisher:
Published: 1999
Total Pages: 347
ISBN-13: 9780470852538
DOWNLOAD EBOOK →Image processing has been one of the most active areas of research in recent years. The techniques involved have found significant applications in areas as diverse as video-conferencing, image communication, robotics, geoscience, and medicine.; Providing a step-by-step guide to the basic principles underlying all image processing tasks, this book features numerous worked examples, guiding the reader through the intricacies of reaching the solutions.
Author: Philip Rideout
Publisher: "O'Reilly Media, Inc."
Published: 2010-05-03
Total Pages: 442
ISBN-13: 1449390625
DOWNLOAD EBOOK →What does it take to build an iPhone app with stunning 3D graphics? This book will show you how to apply OpenGL graphics programming techniques to any device running the iPhone OS -- including the iPad and iPod Touch -- with no iPhone development or 3D graphics experience required. iPhone 3D Programming provides clear step-by-step instructions, as well as lots of practical advice, for using the iPhone SDK and OpenGL. You'll build several graphics programs -- progressing from simple to more complex examples -- that focus on lighting, textures, blending, augmented reality, optimization for performance and speed, and much more. All you need to get started is a solid understanding of C++ and a great idea for an app. Learn fundamental graphics concepts, including transformation matrices, quaternions, and more Get set up for iPhone development with the Xcode environment Become familiar with versions 1.1 and 2.0 of the OpenGL ES API, and learn to use vertex buffer objects, lighting, texturing, and shaders Use the iPhone's touch screen, compass, and accelerometer to build interactivity into graphics applications Build iPhone graphics applications such as a 3D wireframe viewer, a simple augmented reality application, a spring system simulation, and more
Author: Maria M. P. Petrou
Publisher: John Wiley & Sons
Published: 2021-03-22
Total Pages: 816
ISBN-13: 111961855X
DOWNLOAD EBOOK →The classic text that covers practical image processing methods and theory for image texture analysis, updated second edition The revised second edition of Image Processing: Dealing with Textures updates the classic work on texture analysis theory and methods without abandoning the foundational essentials of this landmark work. Like the first, the new edition offers an analysis of texture in digital images that are essential to a diverse range of applications such as: robotics, defense, medicine and the geo-sciences. Designed to easily locate information on specific problems, the text is structured around a series of helpful questions and answers. Updated to include the most recent developments in the field, many chapters have been completely revised including: Fractals and Multifractals, Image Statistics, Texture Repair, Local Phase Features, Dual Tree Complex Wavelet Transform, Ridgelets and Curvelets and Deep Texture Features. The book takes a two-level mathematical approach: light math is covered in the main level of the book, with harder math identified in separate boxes. This important text: Contains an update of the classic advanced text that reviews practical image processing methods and theory for image texture analysis Puts the focus exclusively on an in-depth exploration of texture Contains a companion website with exercises and algorithms Includes examples that are fully worked to enhance the learning experience Written for students and researchers of image processing, the second edition of Image Processing has been revised and updated to incorporate the foundational information on the topic and information on the latest advances.
Author: Rani, Geeta
Publisher: IGI Global
Published: 2020-10-16
Total Pages: 586
ISBN-13: 1799827437
DOWNLOAD EBOOK →By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.
Author: Phil Brodatz
Publisher:
Published: 1999
Total Pages: 0
ISBN-13: 9780486406992
DOWNLOAD EBOOK →Over 100 royalty-free illustrations of fieldstone, reptile skin, pressed cork, raffia weave, lace, straw matting, beach pebbles, European marble, water, many other materials. Immediately usable designs can be scanned into PCs.
Author: Adrien Depeursinge
Publisher: Academic Press
Published: 2017-08-25
Total Pages: 432
ISBN-13: 0128123214
DOWNLOAD EBOOK →Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images. Defines biomedical texture precisely and describe how it is different from general texture information considered in computer vision Defines the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements Describes, using intuitive concepts, how the most popular biomedical texture analysis approaches (e.g., gray-level matrices, fractals, wavelets, deep convolutional neural networks) work, what they have in common, and how they are different Identifies the strengths, weaknesses, and current challenges of existing methods including both handcrafted and learned representations, as well as deep learning. The goal is to establish foundations for building the next generation of biomedical texture operators Showcases applications where biomedical texture analysis has succeeded and failed Provides details on existing, freely available texture analysis software, helping experts in medicine or biology develop and test precise research hypothesis
Author: A. Ravishankar Rao
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 221
ISBN-13: 1461397774
DOWNLOAD EBOOK →A central issue in computer vision is the problem of signal to symbol transformation. In the case of texture, which is an important visual cue, this problem has hitherto received very little attention. This book presents a solution to the signal to symbol transformation problem for texture. The symbolic de- scription scheme consists of a novel taxonomy for textures, and is based on appropriate mathematical models for different kinds of texture. The taxonomy classifies textures into the broad classes of disordered, strongly ordered, weakly ordered and compositional. Disordered textures are described by statistical mea- sures, strongly ordered textures by the placement of primitives, and weakly ordered textures by an orientation field. Compositional textures are created from these three classes of texture by using certain rules of composition. The unifying theme of this book is to provide standardized symbolic descriptions that serve as a descriptive vocabulary for textures. The algorithms developed in the book have been applied to a wide variety of textured images arising in semiconductor wafer inspection, flow visualization and lumber processing. The taxonomy for texture can serve as a scheme for the identification and description of surface flaws and defects occurring in a wide range of practical applications.
