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Low-Power Smart Imagers for Vision-Enabled Sensor Networks

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 analy...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Fernández-Berni, Jorge (Autor), Carmona-Galán, Ricardo (Autor), Rodríguez-Vázquez, Ángel (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2012.
Edición:1st ed. 2012.
Temas:
Acceso en línea:Texto Completo

MARC

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505 0 |a 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. 
520 |a 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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650 2 4 |a Signal, Speech and Image Processing . 
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700 1 |a Rodríguez-Vázquez, Ángel.  |e author.  |0 (orcid)0000-0002-1006-5241  |1 https://orcid.org/0000-0002-1006-5241  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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