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A machine vision system should be able to analyze images and produce descriptions of what it "sees". The descriptions should capture the aspects of the objects being imaged and be useful for accomplishing some specific tasks. In this volume a number of subjects are discussed. They include theoretical aspects which focus on shape analysis, special architectures, 3-D image decomposition, inspection by machine vision, and others. Applications include geophysical image analysis, robotics, sparse image understanding, biomedical applications. An ample survey of the present industrial applications is also provided.
This book presents reports by well-known experts on the most recent research results in image coding, analysis and understanding, and promising applications for solving real problems in manufacturing, remote sensing and biomedicine. The topics covered include shape analysis and computer vision, pattern recognition methods and applications, parallel computer architectures for image processing and analysis, human perception and use of artificial intelligence techniques for image understanding, languages for image abstraction, processing and retrieval, vision modules and neural computation.
Perceptual processes in humans and machines, investigated and simulated by means of the computational approach, are the subject matter of this volume. Researchers in artificial intelligence, pattern recognition, and psychology discuss aspects of vision, speech understanding, sensory-motor coordination, and their interplay with cognitive and behavioral functionalities. The papers adopt the computational approach as the basic research paradigm. Connectionist models, numerical and statistical techniques, symbolic (logic-based) formalisms, and hybrid representations provide the formal background to the research. Some of the papers were prepared for a workshop held in Trieste, Italy, in October 1992.
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