Computer Methods for Analysis and Synthesis of Visual Texture


Book Description

Computer methods are presented which deal with the problems of visual texture, specifically Texture Analysis and Texture Synthesis. The Decision Theory Method, as its name indicates, is based on the principles of statistical decision theory. This method in conjunction with the Internal Covering Theory, automatically generates a set of interval complexes which act as 2-D filters that detect texture features in the scene of analysis. The versatility of this method to deal with various problems of visual texture, such as scene segmentation using textural information, extraction of texture borders, discrimination/recognition of both spatially and chromatically textured scenes, etc. is demonstrated. A model is proposed that views the pixels of a digitized textural scene as a two- way seasonal time series. Based on this model, a method is developed for synthesis of natural looking textures. This method possesses a desirable quality that the parameters needed for the synthesis are derived from the analysis of parent'' texture, i.e., the texture to be imitated. Extending the concepts of two-dimensional formal grammars, known as array grammars, multilevel array grammars'' are introduced. These are shown capable of generating complex texture scenes, specifically brickwall-type'' texture, that is, those textures which are perceived at many levels and at each level, they can be either structural or statistical. A way of specifying these grammars for texture scenes in real cases, with the help of interval complexes, '' is also indicated. (96 references) (auth).







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.




Computer Analysis of Visual Textures


Book Description

This book presents theories and techniques for perception of textures by computer. Texture is a homogeneous visual pattern that we perceive in surfaces of objects such as textiles, tree barks or stones. Texture analysis is one of the first important steps in computer vision since texture provides important cues to recognize real-world objects. A major part of the book is devoted to two-dimensional analysis of texture patterns by extracting statistical and structural features. It also deals with the shape-from-texture problem which addresses recovery of the three-dimensional surface shapes based on the geometry of projection of the surface texture to the image plane. Perception is still largely mysterious. Realizing a computer vision system that can work in the real world requires more research and ex periment. Capability of textural perception is a key component. We hope this book will contribute to the advancement of computer vision toward robust, useful systems. vVe would like to express our appreciation to Professor Takeo Kanade at Carnegie Mellon University for his encouragement and help in writing this book; to the members of Computer Vision Section at Electrotechni cal Laboratory for providing an excellent research environment; and to Carl W. Harris at Kluwer Academic Publishers for his help in preparing the manuscript.




Digital Image Processing


Book Description

This book is the consequence of a NATO ASI held at the Chateau de BONAS, from June 23 to July 4, 1980. It contains the tutorial lectures and some papers presented at the Institute. The book is divided in four sections: Issue.s-, of general interest. Some topics are broader than the proper techniques of image processing, such as complexity, clustering, topology, physiology; but they may be of interest ... Feature detect'ion and evaluation. The first level feature detections are examined: edges and textures. Reorganization and improvement of the results are obtained by relaxation and opti mization process. Cooperative process are examined. Scenes and shapes. concerns higher level problems, and representation of images such as map and line-drawings. Applications in remote sensing, scene analysis, of one or of a sequence of images. It is hoped that this book will serve to update a domain In fast evolution. Acknowledgment: This ASI, and this book, have been made possible by the financial support of the NATO Scientific Affairs Division, and the material support of INRIA and the Institut de Programmation of the Universite P. et M. Curie. vii J. C. Simon and R. M. Haralick (eds.), Digital Image Processing, vii. Copyright © 1981 by D. Reidel Publishing Company. APPLICATION OF COMPLEXITY OF COMPUTATIONS TO SIGNAL PROCESSING S. Winograd IBM Thomas J. Watson Research Center Yorktown Heights, New York, U.S.A.




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Book Description







Computational Models for Texture Analysis and Synthesis


Book Description

Numerous computational methods for generating and simulating binary and grey-level natural digital-image textures are proposed using a variety of stochastic models. Pictorial results of each method are given and various aspects of each approach are discussed. The quality of the natural texture simulations depends on the computation time for data collection, computation time for generation, and storage used in each process. In most cases, as computation time and data storage increase, the visual match between the texture simulation and the parent texture improves. Many textures are adequately simulated using simple models thus providing a potentially great information compression for many applications.




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./a




Texture Analysis in Machine Vision


Book Description

d104ure analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. d104ure analysis has been a topic of intensive research for over three decades, but the progress has been very slow.A workshop on ?d104ure Analysis in Machine Vision? was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis. It should be of great interest both to researchers of machine vision and to practitioners in various application areas.