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• 1. Introduction
• 1.1. Human and Machine Perception
• 1.2. Representation of an Information Field
• 1.3. Recursive Approach to Image Representation
• 2. Recursive Structures and their Properties
• 2.1 Recursive Descriptions and Recursive Structures
• 2.2. Representation of Some Mathematical Objects by Recursive Structures
• 2.3. The Enumeration of Cells in a Discrete Space
• 2.4. Cartesian and Positional Coordinates. Operations with Positional Coordinates
• 2.5. The Representation of Images with Pyramidal-Recursive Structures
• 3. Pyramidal Image Models
• 3.1. Comparison of Pyramidal-Recursive Structures and Two-dimensional Transforms
• 3.2. The Model of Greyscale Image
• 3.3. The Model of the Binary Image
• 4. Image Coding and Progressive Transmission with Gradual Refinement
• 4.1. Coding of Greyscale Images
• 4.2. Comparison of Some Image Coding Algorithms
• 4.3. Transmission of Greyscale Images with Gradual Refinement
• 4.4. Compression and Transmission of Binary Images
• 5. Image Processing with Pyramidal-Recursive Structures
• 5.1. Simple Operations with Images Represented by Truncated Trees
• 5.2. Fast Template Matching
• 5.3. Hierarchical Matching of Arbitrary-Oriented Template
• 6. Applications of Pyramidal-Recursive Structures and Algorithms
• 6.1. Data Flow Organization in Image Processing Systems
• 6.2. Optical Character Recognition
• 6.3. Modelling of Ore Milling
• 6.4. Special Devices for Image Processing
• 6.5. On Expert Systems Simulating Human Visual Perception.

Recently, much attention has been paid to image processing with multiresolution and hierarchical structures such as pyramids and trees. This volume deals with recursive pyramids, which combine the advantages of available multiresolution structures and which are convenient both for global and local image processing. Recursive pyramids are based on regular hierarchical (recursive) structures containing data on image fragments of different sizes. Such an image representation technique enables the effective manipulation of pictorial information as well as the development of special hardware or data structures. The major aspects of this book are two original mathematical models of greyscale and binary images represented by recursive structures. Image compression, transmission and processing are discussed using these models. A number of applications are presented, including optical character recognition, expert systems and special computer architecture for pictorial data processing. The majority of results are presented as algorithms applicable to discrete information fields of arbitrary dimensions (e.g. 2-D or 3-D images). The book is divided into six chapters: Chapter 1 provides a brief introduction. Chapter 2 then deals with recursive structures and their properties. Chapter 3 introduces pyramidal image models. Image coding and the progressive transmission of images with gradual refinement are discussed in Chapter 4. Chapters 5 and 6 are devoted to image processing with pyramidal-recursive structures and applications. The volume concludes with a comprehensive bibliography. For applied mathematicians and computer scientists whose work involves computer vision, information theory and other aspects of image representation techniques.

• AUTHORS' NOTES AND ACKNOWLEDGEMENTS; INTRODUCTION; 1.1. Objectives of this Book; 1.2. The Seeing Eye and the Knowing Eye
• 1 IMAGE AND COMPUTER; 1.1. A Short History; 1.2. The Computer's Eye; 1.3. A Beetle and an Ant-Hill; 1.4. Features and Models; 2 HOW HUMANS SEE THE WORLD; 2.1. The Eye and the Brain; 2.2. The Level of Preattention; 2.3. Right and Left Vision; 2.4. Images and Words; 3 CONVERSATIONS WITH A COMPUTER; 3.1. From a Point to a Region; 3.2. From a Region to an Object; 3.3. From an Object to a Situation; 4 AN APOLOGIA FOR VISION; 4.1. The Evolution of Vision.

• 4
• .2. Vision and Thinking4
• .3. Recollection of the Future; 4
• .4. Cognition through Vision; 5 CREATING A NEW WORLD; 5
• .1. From Elements to the System; 5
• .2. Back to Nature; 5
• .3. Who Do We Think They Are?; CONCLUSIONS; PLATES; REFERENCES; ILLUSTRATIONS; INDEX.

This book considers computer vision to be an integral part of the artificial intelligence system. The core of the book is an analysis of possible approaches to the creation of artificial vision systems, which simulate human visual perception. Much attention is paid to the latest achievements in visual psychology and physiology, the description of the functional and structural organization of the human perception mechanism, the peculiarities of artistic perception and the expression of reality. Computer vision models based on these data are investigated. They include the processes of external data analysis, internal environmental model synthesis, and the generating of behavioristic responses based on external and internal models comparison. Computer vision system evolution resulting from environmental effects is also considered. A unique feature of this book is the authors' use of black and white, and colour prints of traditional and contemporary Russian art to illustrate their principal theses. In doing so, they introduce the reader to a particularly Russian view of the world.
(source: Nielsen Book Data)