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Autor(en): 
  • Ángel Rodríguez-Vázquez
  • Ricardo Carmona-Galán
  • Jorge Fernández-Berni
  • Low-Power Smart Imagers for Vision-Enabled Sensor Networks 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Mai 2014  
    Genre:  Naturwissensch., Medizin, Technik 
     
    B / Circuits and Systems / Digital and Analog Signal Processing / Electronic circuits / Electronic Circuits and Systems / Electronics / Electronics and Microelectronics, Instrumentation / Electronics engineering / engineering / Image processing / Imaging systems & technology / Microelectronics / Signal Processing / Signal, Image and Speech Processing / Speech processing systems
    ISBN:  9781489995407 
    EAN-Code: 
    9781489995407 
    Verlag:  Springer New York 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 11 mm 
    Gewicht:  283 gr 
    Seiten:  180 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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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