Dedicated Frontends For Embedded Vision Systems

• doi: 10.1109/WAC.2002.1049537
• title: Dedicated frontends for embedded vision systems
• publisher: IEEE
• isbn: 1-889335-18-5
• issn:
• partnum: D2EX548
• rank: 2056
• access_type: LOCKED
• content_type: Conferences
• abstract: Industrial image acquisition and processing tasks often make high demands on vision systems. The frontend implementation of CMOS image sensors with integrated preprocessing presents a feasible alternative to conventional CCD systems. To cope with multiple constraints such as time-to-market, power-consumption, size, costs as well as the typically high system complexity, an appropriate design methodology is required. In prior work, a holistic design methodology was developed with focus on embedded vision systems. In our investigations of representative vision applications several relevant processing tasks have been identified that are excellent candidates for implementation in the vision system's frontend. Their mixed-signal hardware realization in the context of the holistic modeling approach is the focus of this paper. Aspects such as data reduction by integrated image preprocessing algorithms and feature computation, local adaptation, and electronically controllable foveated sensor planes as well as high-dynamic, linear response pixel cells are presented.
• article_number: 1049537
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1049537
• html_url: https://ieeexplore.ieee.org/document/1049537/
• abstract_url: https://ieeexplore.ieee.org/document/1049537/
• publication_title: Proceedings of the 5th Biannual World Automation Congress
• conference_location: Orlando, FL, USA
• conference_dates: 9-13 June 2002
• publication_number: 8124
• is_number: 22475
• publication_year: 2002
• publication_date: 9-13 June 2002
• start_page: 153
• end_page: 158
• citing_paper_count: 0
• citing_patent_count: 0
• download_count: 49
• insert_date: 20021210
• index_terms:
  • ieee_terms:
    • Machine vision
    • Design methodology
    • CMOS image sensors
    • Charge coupled devices
    • Time to market
    • Costs
    • Hardware
    • Context modeling
    • Focusing
    • Image sensors
  • dynamic_index_terms:
    • Visual System
    • Image Processing
    • Data Reduction
    • Linear Response
    • Local Adaptation
    • Processing Tasks
    • Design Methodology
    • Image Sensor
    • Camera Sensor
    • Image Preprocessing
    • Multiple Constraints
    • Holistic Model
    • Image Processing Tasks
    • Dynamic Range
    • Average Position
    • Average Location
    • Random Access
    • High Dynamic Range
    • Machine Vision
    • Visual Navigation
    • Biased Signaling
    • Signaling Bias
    • AC Bias
    • Anisotropic Diffusion
    • Degree Of Smoothness
    • Pixel Matrix
    • Pixel Matrices
    • Linear Sensor
    • Industrial Inspection
    • Pixel Column
• isbn_formats:
  • format: Print ISBN, value: 1-889335-18-5, isbnType: Historical
• authors:
  • Author Name: J. Skribanowitz
    Affiliation: Dresden University of Technology, Germany
    Author URL: https://ieeexplore.ieee.org/author/37327538700
    ID: 37327538700
    Order: 1
    Author Affiliations:
    • Dresden University of Technology, Germany
  • Author Name: A. Konig
    Affiliation: Dresden University of Technology, Germany
    Author URL: https://ieeexplore.ieee.org/author/37297779800
    ID: 37297779800
    Order: 2
    Author Affiliations:
    • Dresden University of Technology, Germany

Image Sensor

• sensor_type: CMOS
• resolution: varies by application
• dynamic_range: up to 120 dB
• pixel_size: around 5.5 µm (fill factor of 5.5% indicated)
• dark_current: not specified

Optical Data

• focal_length: not specified
• aperture: not specified
• field_of_view: not specified
• distortion: not specified

Performance Metrics

• power_consumption: low power consumption due to subthreshold operation
• noise: temporal noise and fixed-pattern noise

Applications & Benefits

• cell_imaging: used in various applications including industrial imaging, gesture recognition, and potentially 3D human motion reconstruction
• benefits: integrated preprocessing enables real-time capability, low power consumption, and compact design

Supporting Organizations

• supported_by: DFG-Graduate College of Sensor Technology, austriumicrosystems AG

Manuscript Details

• publication_date: 9-13 June 2002

Relevancy Score

• score: 10

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