Handbook of Texture Analysis


Book Description

Texture analysis is one of the fundamental aspects of human vision by which we discriminate between surfaces and objects. In a similar manner, computer vision can take advantage of the cues provided by surface texture to distinguish and recognize objects. In computer vision, texture analysis may be used alone or in combination with other sensed features (e.g. color, shape, or motion) to perform the task of recognition. Either way, it is a feature of paramount importance and boasts a tremendous body of work in terms of both research and applications.Currently, the main approaches to texture analysis must be sought out through a variety of research papers. This collection of chapters brings together in one handy volume the major topics of importance, and categorizes the various techniques into comprehensible concepts. The methods covered will not only be relevant to those working in computer vision, but will also be of benefit to the computer graphics, psychophysics, and pattern recognition communities, academic or industrial.




Handbook Of Pattern Recognition And Computer Vision (2nd Edition)


Book Description

The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.




Computational Modelling of Objects Represented in Images III


Book Description

Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III contains all contributions presented at the International Symposium CompIMAGE 2012 - Computational Modelling of Object Presented in Images: Fundamentals, Methods and Applications (Rome, Italy, 5-7 September 2012). The contributions cover the state-of-art and new trends in the fields of: - 3D Vision; - Biometric Recognition; - Computational Bioimaging and Visualization; - Computer Vision in Robotics and Automation; - Data Acquisition, Interpolation, Registration and Compression; - Image Enhancement and Restoring; - Image Processing and Analysis; - Image Segmentation; - Medical Imaging; - Modeling and Simulation; - Motion and Deformation Analysis; - Remote Sensing; - Scientific Visualization Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications III addresses different techniques, such as optimization methods, geometry, finite element method, principal component analysis, stochastic methods, neural networks and fuzzy logic. The book is useful to researchers and students with multidisciplinary interests related to Computational Vision, Computational Mechanics, Medicine, Engineering and Architecture.




Image Texture Analysis


Book Description

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.




Texturing & Modeling


Book Description

The third edition of this classic tutorial and reference on procedural texturing and modeling is thoroughly updated to meet the needs of today's 3D graphics professionals and students. New for this edition are chapters devoted to real-time issues, cellular texturing, geometric instancing, hardware acceleration, futuristic environments, and virtual universes. In addition, the familiar authoritative chapters on which readers have come to rely contain all-new material covering L-systems, particle systems, scene graphs, spot geometry, bump mapping, cloud modeling, and noise improvements. There are many new spectacular color images to enjoy, especially in this edition's full-color format. As in the previous editions, the authors, who are the creators of the methods they discuss, provide extensive, practical explanations of widely accepted techniques as well as insights into designing new ones. New to the third edition are chapters by two well-known contributors: Bill Mark of NVIDIA and John Hart of the University of Illinois at Urbana-Champaign on state-of-the-art topics not covered in former editions. An accompanying Web site (www.texturingandmodeling.com) contains all of the book's sample code in C code segments (all updated to the ANSI C Standard) or in RenderMan shading language, plus files of many magnificent full-color illustrations. No other book on the market contains the breadth of theoretical and practical information necessary for applying procedural methods. More than ever, Texturing & Modeling remains the chosen resource for professionals and advanced students in computer graphics and animation. *New chapters on: procedural real-time shading by Bill Mark, procedural geometric instancing and real-time solid texturing by John Hart, hardware acceleration strategies by David Ebert, cellular texturing by Steven Worley, and procedural planets and virtual universes by Ken Musgrave. *New material on Perlin Noise by Ken Perlin. *Printed in full color throughout. *Companion Web site contains revised sample code and dozens of images.







Biomedical Texture Analysis


Book Description

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




Computational Modeling of Objects Presented in Images: Fundamentals, Methods, and Applications


Book Description

This book constitutes the refereed proceedings of the 4th International Conference on Computational Modeling of Objects Presented in Images, CompIMAGE 2014, held in Pittsburgh, PA, USA, in September 2014. The 29 revised full papers presented together with 10 short papers and 6 keynote talks were carefully reviewed and selected from 54 submissions. The papers cover the following topics: medical treatment, imaging and analysis; image registration, denoising and feature identification; image segmentation; shape analysis, meshing and graphs; medical image processing and simulations; image recognition, reconstruction and predictive modeling; image-based modeling and simulations; and computer vision and data-driven investigations.




Visual Texture


Book Description

This book surveys the state of the art in multidimensional, physically-correct visual texture modeling. Features: reviews the entire process of texture synthesis, including material appearance representation, measurement, analysis, compression, modeling, editing, visualization, and perceptual evaluation; explains the derivation of the most common representations of visual texture, discussing their properties, advantages, and limitations; describes a range of techniques for the measurement of visual texture, including BRDF, SVBRDF, BTF and BSSRDF; investigates the visualization of textural information, from texture mapping and mip-mapping to illumination- and view-dependent data interpolation; examines techniques for perceptual validation and analysis, covering both standard pixel-wise similarity measures and also methods of visual psychophysics; reviews the applications of visual textures, from visual scene analysis in medical applications, to high-quality visualizations in the automotive industry.