Human and Machine Vision

Human and Machine Vision

1st Edition - December 1, 1983

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  • Editors: Jacob Beck, Barbara Hope, Azriel Rosenfeld
  • eBook ISBN: 9781483266961

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Human and Machine Vision provides information pertinent to an interdisciplinary program of research in visual perception. This book presents a psychophysical study of the human visual system, which provides insights on how to model the flexibility required by a general-purpose visual system. Organized into 17 chapters, this book begins with an overview of how a visual display is segmented into components on the basis of textual differences. This text then proposes three criteria for judging representations of shape. Other chapters consider an increased use of machine vision programs as models of human vision and of data from human vision in developing programs for machine vision. This book discusses as well the diversity and flexibility of systems for representing visual information. The final chapter deals with dot patterns and discusses the process of interring orientation information from collections of them. This book is a valuable resource for psychologists, neurophysiologists, and computer scientists.

Table of Contents

  • Contributors



    A Theory of Textural Segmentation

    Criteria for Representations of Shape

    Contrasts Between Human and Machine Vision: Should Technology Recapitulate Phylogeny?

    Flexibility in Representational Systems

    Computing with Connections

    Stimulus Information and Processing Mechanisms in Visual Space Perception

    Mapping Image Properties into Shape Constraints: Skewed Symmetry, Affine-Transformable Patterns, and the Shape-from-Texture Paradigm

    Visual Computation

    The Psychology of Perceptual Organization: A Transformational Approach

    Why the Human Perceiver Is a Bad Machine

    Spatiotemporal Interpolation in Vision

    Isolating Representational Systems

    A Sketch of a (Computational) Theory of Visual Kinesthesis

    Environment-Centered Representation of Spatial Layout: Available Visual Information from Texture and Perspective

    Recent Computational Studies in the Interpretation of Structure from Motion

    On the Role of Structure in Vision

    Computational and Psychophysical Experiments in Grouping: Early Orientation Selection

Product details

  • No. of pages: 580
  • Language: English
  • Copyright: © Academic Press 1983
  • Published: December 1, 1983
  • Imprint: Academic Press
  • eBook ISBN: 9781483266961

About the Editors

Jacob Beck

Barbara Hope

Azriel Rosenfeld

The late Azriel Rosenfeld was a tenured research professor, a distinguished university professor, and the Founding Director of the Center for Automation Research at the University of Maryland in College Park, where he also held affiliate professorships in the departments of computer science, electrical engineering, and psychology. Dr. Rosenfeld was widely regarded as the leading researcher in the world in the field of computer image analysis. Over a period of nearly 40 years, he made fundamental and pioneering contributions to nearly every area of that field. He wrote the first textbook in the field, was founding editor of its first journal, and was co-chairman of its first international conference. He published over 30 books and over 600 book chapters and journal articles, and directed nearly 60 Ph.D. dissertations. Dr. Rosenfeld's research on digital image analysis—specifically on digital geometry and topology and the accurate measurement of statistical features of digital images in the 1960s and 1970s—formed the foundation for a generation of industrial vision inspection systems that have found widespread applications from the automotive to the electronics industry. He was a Fellow of the IEEE and the Washington Academy of Sciences; a Founding Fellow of the AAAI, the ACM, and the IAPR. Among his numerous awards and honors are the IEEE's Emanuel Piore Award, its Third Millennium Medal, and its Distinguished Service Award for Lifetime Achievement in Computer Vision and Pattern Recognition.

Affiliations and Expertise

University of Maryland, College Park, U.S.A.

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