Jorge Fernández-Berni, Ricardo Carmona-Galán, Ángel Rodríguez-Vázquez

Low-Power Smart Imagers for Vision-Enabled Sensor Networks (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book presents a comprehensive, systematic approach to the development of vision system architectures that employ sensory-processing concurrency and parallel processing to meet the autonomy challenges posed by a variety of safety and surveillance applications. Coverage includes a thorough analysis of resistive diffusion networks embedded within an image sensor array. This analysis supports a systematic approach to the design of spatial image filters and their implementation as vision chips in CMOS technology. The book also addresses system-level considerations pertaining to the embedding of these vision chips into vision-enabled wireless sensor networks.

• Describes a system-level approach for designing of vision devices and embedding them into vision-enabled, wireless sensor networks;
• Surveys state-of-the-art, vision-enabled WSN nodes;
• Includes details of specifications and challenges of vision-enabled WSNs;
• Explains architectures for low-energy CMOS vision chips with embedded, programmable spatial filtering capabilities;
• Includes considerations pertaining to the integration of vision chips into off-the-shelf WSN platforms.

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Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 156
• Englisch
• ISBN-13: 9781461423928
• Artikelnr.: 37361540

Inhaltsangabe

Introduction.- Vision-enabled WSN Nodes: State of the Art.- Processing Primitives for Image Simplification.- VLSI Implementation of Linear Diffusion.- FLIP-Q: A QCIF Resolution Focal-plane Array for Low-power Image Processing.- Wi-FLIP: A Low-power Vision-enabled WSN Node.- Case Study: Early Detection of Forest Fires.