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Vision Chips

  • Book
  • © 2000

Overview

Authors:
  1. Alireza Moini

    1. The University of Adelaide, Australia

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 526)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Introduction and Background

    1. Front Matter

      Pages xvii-xvii
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    2. Introduction

      • Alireza Moini
      Pages 1-5

    3. Computer Vision for Analog VLSI

      • Alireza Moini
      Pages 7-22

    4. Analog VLSI for Computer Vision

      • Alireza Moini
      Pages 23-44

  3. Synthesis of Vision Algorithms

    1. Front Matter

      Pages 45-48
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    2. Vision Chips Architectures

      • Alireza Moini
      Pages 49-63

    3. Building Blocks for Vision Chips

      • Alireza Moini
      Pages 65-100

    4. Testing vision chips

      • Alireza Moini
      Pages 101-107

    5. Other Design Issues

      • Alireza Moini
      Pages 109-128

  4. Vision Sensors

    1. Front Matter

      Pages 129-129
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    2. Spatial Image Processing Vision Chips

      • Alireza Moini
      Pages 131-162

    3. Spatio-Temporal Image Processing Vision Chips

      • Alireza Moini
      Pages 163-197

    4. Analog VLSI Chips for Vision Processing

      • Alireza Moini
      Pages 199-203

  6. Back Matter

    Pages 243-300
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Keywords

About this book

This chapter presents a set of introductory material, which in addition to providing a general view on the topic, highlights the importance of research in this area. It also presents a short history of the design of smart vision sensors, and points out some of the fundamental issues in the design of such sensors. 1. 1 A General Overview Machine vision is one of the main branches of artificial intelligence. The richness of information present in images makes them the first choice as an input to an artificial system which tries to interact with its environment. A large proportion of the brain of many advanced species is dedicated to visual information processing, which illustrates the importance of visual information in biological systems. Biological visual systems have evolved over millions of years, and each specie has developed a specialized visual system tailored for the essential tasks of survival, such as catching a prey, or escaping a predator. Implementing electronic hardware for image processing, therefore, may benefit from the underlying fundamental aspects of biological vision, though in no respect should this be regarded as a solid framework for electronic vision systems. Traditionally, computer vision algorithms are performed on images captured by conventional cameras, and processing is accomplished by means of general purpose digital computers. More advanced systems utilize dedicated hardware to speed up the processing stage.

Authors and Affiliations

  • The University of Adelaide, Australia

    Alireza Moini

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