Computer vision deals with the problem of manipulating information contained in large quantities of sensory data, where raw data emerge from the transducing 6 7 sensors at rates between 10 to 10 pixels per second. Conventional general purpose computers are unable to achieve the computation rates required to op erate in real time or even in near real time, so massively parallel systems have been used since their conception in this important practical application area. The development of massively parallel computers was initially character ized by efforts to reach a speedup factor equal to the number of processing elements (linear scaling assumption). This behavior pattern can nearly be achieved only when there is a perfect match between the computational struc ture or data structure and the system architecture. The theory of hierarchical modular systems (HMSs) has shown that even a small number of hierarchical levels can sizably increase the effectiveness of very large systems. In fact, in the last decade several hierarchical architectures that support capabilities which can overcome performances gained with the assumption of linear scaling have been proposed. Of these architectures, the most commonly considered in com puter vision is the one based on a very large number of processing elements (PEs) embedded in a pyramidal structure. Pyramidal architectures supply the same image at different resolution lev els, thus ensuring the use of the most appropriate resolution for the operation, task, and image at hand.

This book contains the proceedings of the NATO Advanced Research Workshop held in Maratea (Italy), May 5-9, 1986 on Pyramidal Systems for Image Processing and Computer Vision. We had 40 participants from 11 countries playing an active part in the workshop and all the leaders of groups that have produced a prototype pyramid machine or a design for such a machine were present. Within the wide field of parallel architectures for image processing a new area was recently born and is growing healthily: the area of pyramidally structured multiprocessing systems. Essentially, the processors are arranged in planes (from a base to an apex) each one of which is generally a reduced (usually by a power of two) version of the plane underneath: these processors are horizontally interconnected (within a plane) and vertically connected with "fathers" (on top planes) and "children" on the plane below. This arrangement has a number of interesting features, all of which were amply discussed in our Workshop including the cellular array and hypercube versions of pyramids. A number of projects (in different parts of the world) are reported as well as some interesting applications in computer vision, tactile systems and numerical calculations.

The exponential explosion of images and videos concerns everybody's common life, since this media is now present everywhere and in all human activities. Scientists, artists and engineers, in any field, need to be aware of the basic mechanisms that allow them to understand how images are essentially information carriers. Images bear a strong evocative power because their perception quickly brings into mind a number of related pictorial contents of past experiences and even of abstract concepts like pleasure, attraction or aversion.This book analyzes the visual hints, thanks to which images are generally interpreted, processed and exploited both by humans and computer programs. - Comprehensive introductory text - Introduces the reader to the large world of imagery on which many human activities are based, from politics to entertainment, from technical reports to artistic creations - Provides a unified framework where both biological and artificial vision are discussed through visual cues, through the role of contexts and the available multi-channels to deliver information

Parallel Computer Vision

Computer vision solutions used to be very specific and difficult to adapt to different or even unforeseen situations. The current development is calling for simple to use yet robust applications that could be employed in various situations. This trend requires the reassessment of some theoretical issues in computer vision. A better general understanding of vision processes, new insights and better theories are needed. The papers selected from the conference staged in Dagstuhl in 1996 to gather scientists from the West and the former eastern-block countries address these goals and cover such fields as 2D images (scale space, morphology, segmentation, neural networks, Hough transform, texture, pyramids), recovery of 3-D structure (shape from shading, optical flow, 3-D object recognition) and how vision is integrated into a larger task-driven framework (hand-eye calibration, navigation, perception-action cycle).

This volume contains papers on Image Compression, Implementations, Feature Detection, 3-D Vision, Document Processing, Multi-Resolution Processing, Medical Imaging, Image Analysis Modelling, Neural Networks, Object Recognition, Remote Sensing, Dynamic Vision, Application, System & Architecture, Image Restoration/Enhancement and Image Segmentation.

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role. This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication. Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field. This state-of-the-art book brings together selected review articles and accounts of current projects from world-renowned researchers at the forefront of this exciting area. The contributions cover topics such as: - Psychology of perception - Image processing - Computational geometry - Visual knowledge representation and languages It is this truly multi-disciplinary approach that has produced successful theories and applications for the subject.

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.

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.

This book contains a selection of papers which were presented at the Vision Interface '92 Conference. It also includes several invited articles from prominent researchers in the field, suggesting future directions in Computer Vision.