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Low-Power Smart Imagers for Vision-Enabled Sensor Networks [electronic resource] / by Jorge Fernández-Berni, Ricardo Carmona-Galán, Ángel Rodríguez-Vázquez.

By: Fernández-Berni, Jorge [author.].
Contributor(s): Carmona-Galán, Ricardo [author.] | Rodríguez-Vázquez, Ángel [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: New York, NY : Springer New York, 2012Description: XXIII, 156 p. 109 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781461423928.Subject(s): Engineering | Electronics | Systems engineering | Engineering | Circuits and Systems | Electronics and Microelectronics, Instrumentation | Signal, Image and Speech ProcessingDDC classification: 621.3815 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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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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.

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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