Vision Chips

Vision Chips

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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.
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Product details

  • Hardback | 300 pages
  • 163.8 x 242.1 x 23.4mm | 657.72g
  • Dordrecht, Netherlands
  • English
  • 2000 ed.
  • XVII, 300 p.
  • 0792386647
  • 9780792386643

Table of contents

Part I: Introduction and Background: 1. Introduction. 2. Computer Vision for Analog VLSI. 3. Analog VLSI for Computer Vision. Part II: Synthesis of Vision Algorithms: 4. Vision Chips Architectures. 5. Building Blocks for Vision Chips. 6. Testing Vision Chips. 7. Other Design Issues. Part III: Vision Sensors: 8. Spatial Vision Chips. 9. Spatio-Temporal Vision Chips. 10. Analog VLSI Chips for Vision Processing. Part IV: Case Studies: 11. Bugeye II: The Second Insect Vision Motion Detection Chip. 12. Bugeye V. 13. MNCSI. Part V: Appendices: A. Quantum Efficiency of Photodetectors. B. Analysis of Second-Order Resistive Networks. Bibliography. Index.
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