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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Hlavní autoři: Fernández-Berni, Jorge, Carmona-Galán, Ricardo (Autor), Rodriguez-Vazquez, Angel (Autor)
Médium: Livre numérique
Jazyk:Anglais
Vydáno: New York, NY : Springer New York 2012.
Cham : Springer Nature
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Edition sous un autre format:• Low-power smart imagers for vision-enabled sensor networks, Jorge Fernández-Berni, Ricardo Carmona-Galán, Ángel Rodríguez-Vásquez, New York, Springer, 2012, 1 vol. (xxiii-156 p.), 978-1-4614-2391-1
• Low-Power Smart Imagers for Vision-Enabled Sensor Networks, Texte imprimé, 9781461423935
• Low-Power Smart Imagers for Vision-Enabled Sensor Networks, Texte imprimé, 9781489995407
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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. 
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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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700 1 |a Rodriguez-Vazquez, Angel.  |4 aut 
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