Low Power Image Acquisition Scheme Using Onpixel Event Driven Halftoning

• doi: 10.1109/ISVLSI.2017.53
• title: Low Power Image Acquisition Scheme Using On-Pixel Event Driven Halftoning
• publisher: IEEE
• isbn: 978-1-5090-6763-3
• issn: 2159-3477
• rank: 2912
• access_type: LOCKED
• content_type: Conferences
• abstract: Several emerging IOT applications may require ultra-low power image-acquisition techniques, at the cost of relaxed constraints on image quality. Event-driven imaging, based on address-event-representation (AER) proposed earlier, ensures event-driven motion detection and conditional image acquisition. However it relies on delta modulation of pixel data upon event detection, which may lead to error accumulation for grey-scale reconstruction. In this work we propose event-driven on-sensor halftoning scheme based on cellular neural network (CNN), which can achieve compressed image acquisition, reducing the data to one bit per active pixel, while avoiding error accumulation over multiple frames. The proposed scheme can achieve reduction in power dissipation related to image quantization, communication and storage. Event-driven current-mode discrete-time CNN (DT-CNN) circuit is proposed for integration on CMOS imager pixel, which is optimally duty cycled to achieve ultra-low power for the halftoning operation. The impact of design parameters and process variations on the final image quality is assessed through inverse halftoning. Clubbed with event-driven acquisition, the proposed on-sensor halftoning can achieve large reduction in power dissipation and data volume, reduction in total volume, as compared to frame based imaging, as well as event driven grey-scale imaging.
• article_number: 7987529
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7987529
• html_url: https://ieeexplore.ieee.org/document/7987529/
• abstract_url: https://ieeexplore.ieee.org/document/7987529/
• publication_title: 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)
• conference_location: Bochum, Germany
• conference_dates: 3-5 July 2017
• publication_number: 7985547
• is_number: 7987474
• publication_year: 2017
• publication_date: 3-5 July 2017
• start_page: 260
• end_page: 265
• citing_paper_count: 3
• citing_patent_count: 0
• download_count: 319
• insert_date: 20170724
• index_terms:
  • ieee_terms:
    • Very large scale integration
  • author_terms:
    • neural networks
    • circuits
    • analog
    • low power
    • image processing
  • dynamic_index_terms:
    • Image Acquisition
    • Halftone
    • Screening Of Lines
    • Low Acquisition
    • Image Quality
    • Design Parameters
    • Duty Cycle
    • Grayscale Images
    • Greyscale Images
    • Event Detection
    • Multiple Frames
    • Error Accumulation
    • Ultra-low Power
    • Reduction In Total Volume
    • Image Processing
    • Volume Change
    • Changes In Intensity
    • Group Size
    • Pixel Intensity
    • Block Size
    • Analog-to-digital Converter
    • Analog-to-digital
    • Digital-to-analog Converter
    • Output Current
    • Pixel Level
    • Pixel Block
    • Entire Block
    • Important Design Parameter
    • Clock Phase
    • Current Mirror
    • Circuit Implementation
    • Fill Factor
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5090-6763-3, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5090-6762-6, isbnType: New-2005
• authors:
  • Author Name: Sangamesh Kodge
    Affiliation: Department of Electrical Engineering, IIT, Kharagpur
    Author URL: https://ieeexplore.ieee.org/author/37086037573
    ID: 37086037573
    Order: 1
    Author Affiliations:
    • Department of Electrical Engineering, IIT, Kharagpur
  • Author Name: Himanshu Chaudhary
    Affiliation: Department of Electrical Engineering, IIT, Kharagpur
    Author URL: https://ieeexplore.ieee.org/author/37089129569
    ID: 37089129569
    Order: 2
    Author Affiliations:
    • Department of Electrical Engineering, IIT, Kharagpur
  • Author Name: Mrigank Sharad
    Affiliation: Department of Electronics and Electrical Comm. Eng., IIT, Kharagpur
    Author URL: https://ieeexplore.ieee.org/author/37845785900
    ID: 37845785900
    Order: 3
    Author Affiliations:
    • Department of Electronics and Electrical Comm. Eng., IIT, Kharagpur

Image Sensor

• sensor_type: CMOS
• resolution: not specified
• dynamic_range: not specified
• pixel_size: not specified
• dark_current: not specified

Optical Data

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

Performance Metrics

Applications & Benefits

• cell_imaging: not specified
• benefits: not specified

Supporting Organizations

• supported_by: not specified

Manuscript Details

• publication_date: 3-5 July 2017

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise
  • cell_imaging
  • benefits
  • supported_by
  • authors
  • publication_date

Processed JSON Filename

request_0dd3f7f6-5063-437b-b961-b5ff9a9410fd-low_power_image_acquisition_scheme_using_onpixel_event_driven_halftoning.json