rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Low-Power Smart Imagers for Vision-Enabled Sensor Networks
  name:
    name part: Fernández-Berni, Jorge.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Carmona-Galán, Ricardo.
    role:
      role term: author.
  name:
    name part: Rodríguez-Vázquez, Ángel.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXIV, 156 p. online resource.
  abstract: 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.
  table of 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.
  note: by Jorge Fernández-Berni, Ricardo Carmona-Galán, Ángel Rodríguez-Vázquez.
  subject:
    topic: Engineering
  subject:
    topic: Electronics
  subject:
    topic: Microelectronics
  subject:
    topic: Electronic circuits
  subject:
    topic: Engineering
  subject:
    topic: Circuits and Systems
  subject:
    topic: Electronics and Microelectronics, Instrumentation
  subject:
    topic: Signal, Image and Speech Processing
  classification: TK7888.4
  classification: 621.3815
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781461423928
  identifier: http://dx.doi.org/10.1007/978-1-4614-2392-8
  record info:
    record creation date: 120405
    record change date: 20151125162126.0
    record identifier: 978-1-4614-2392-8