• DocumentCode
    801859
  • Title

    A 100 \\mu W 128 \\times 64 Pixels Contrast-Based Asynchronous Binary Vision Sensor for Sensor N

  • Author

    Gottardi, Massimo ; Massari, Nicola ; Jawed, Syed Arsalan

  • Author_Institution
    Fondazione Bruno Kessler, Trento
  • Volume
    44
  • Issue
    5
  • fYear
    2009
  • fDate
    5/1/2009 12:00:00 AM
  • Firstpage
    1582
  • Lastpage
    1592
  • Abstract
    An ultra-low power 128 times 64 pixels vision sensor is here presented, featuring pixel-level spatial contrast extraction and binarization. The asynchronous readout only dispatches the addresses of the asserted pixels in bursts of 80 MB/s, significantly reducing the amount of data at the output. The pixel-embedded binary frame buffer allows the sensor to directly process visual information, such as motion and background subtraction, which are the most useful filters in machine vision applications. The presented sensor consumes less than 100 muW at 50 fps with 25% of pixel activity. Power consumption can be further reduced down to about 30 muW by operating the sensor in Idle-Mode, thus minimizing the sensor activity at the ouput.
  • Keywords
    CMOS image sensors; computer vision; feature extraction; low-power electronics; wireless sensor networks; CMOS vision sensor; asynchronous readout; background subtraction; byte rate 80 MByte/s; contrast-based asynchronous binary vision sensor; machine vision; pixel-embedded binary frame buffer; pixel-level binarization; power 100 muW; spatial contrast extraction; ultra-low power vision sensor; visual information; wireless sensor network; Acoustic sensors; Data mining; Energy consumption; Image sensors; Layout; Machine vision; Monitoring; Surveillance; Temperature sensors; Wireless sensor networks; CMOS vision sensors; energy autonomous low-power sensors; low-power; visual processing; wireless sensor networks;
  • fLanguage
    English
  • Journal_Title
    Solid-State Circuits, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    0018-9200
  • Type

    jour

  • DOI
    10.1109/JSSC.2009.2017000
  • Filename
    4907337