Memristorbased Pixel For Eventdetection Vision Sensor

• doi: 10.1109/ICSENS.2015.7370688
• title: Memristor-based pixel for event-detection vision sensor
• publisher: IEEE
• isbn: 978-1-4799-8202-8
• issn:
• rank: 2991
• access_type: LOCKED
• content_type: Conferences
• abstract: We report on a vision sensor architecture relying on a pixel-embedded memristive device to perform dynamic background subtraction as basic image processing components, aimed at detecting anomalous events in the scene. A Light-To-Frequency Converter generates digital pulses, which are linearly proportional with the light intensity. During the exposure time, a certain number of pulses, with proper width and amplitude, drive the memristor MS, changing its resistance. The value of MS is then compared with two memristors, MH and ML, used as thresholds. After each frame, the values of MH and ML are adjusted in order to satisfy ML < MS < MH. The rate at which the two memristors are updated is application-dependent and can be digitally programmed. If the value of MS trespasses either MH or ML, due to a light change, the pixel behaviour is recognized as anomalous (hot-pixel) By aggregating the hot-pixels of the image, anomalous events can be detected through standard processing techniques. The pixel architecture has been designed in a 0.35μm standard CMOS process and validated through simulation.
• article_number: 7370688
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7370688
• html_url: https://ieeexplore.ieee.org/document/7370688/
• abstract_url: https://ieeexplore.ieee.org/document/7370688/
• publication_title: 2015 IEEE SENSORS
• conference_location: Busan, Korea (South)
• conference_dates: 1-4 Nov. 2015
• publication_number: 7350021
• is_number: 7370096
• publication_year: 2015
• publication_date: 1-4 Nov. 2015
• start_page: 1
• end_page: 4
• citing_paper_count: 5
• citing_patent_count: 1
• download_count: 363
• insert_date: 20160107
• index_terms:
  • ieee_terms:
    • Memristors
    • Resistance
    • Photodiodes
    • Threshold voltage
    • Mathematical model
    • Simulation
    • Image processing
  • author_terms:
    • memristive devices
    • memristor
    • light-to-frequency converter
    • light-to-resistance encoding
    • pixel
    • vision sensor
    • memory
    • pulse frequency modulation
  • dynamic_index_terms:
    • Event Detection
    • Vision Sensors
    • Image Processing
    • Light Intensity
    • Background Subtraction
    • Anomalous Events
    • Standard CMOS
    • Low-pass
    • Low-pass Filter
    • Integration Time
    • Photodiode
    • Low Voltage
    • Operation Principle
    • Passive Circuit
• isbn_formats:
  • format: USB ISBN, value: 978-1-4799-8202-8, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-4799-8203-5, isbnType: New-2005
• authors:
  • Author Name: Olufemi A. Olumodeji
    Affiliation: Fondazione Bruno Kessler, Centre for Materials and Microsystems, Trento, Italy
    Author URL: https://ieeexplore.ieee.org/author/37085582782
    ID: 37085582782
    Order: 1
    Author Affiliations:
    • Fondazione Bruno Kessler, Centre for Materials and Microsystems, Trento, Italy
  • Author Name: Alessandro Paolo Bramanti
    Affiliation: Department of Industrial Engineering, University of Trento
    Author URL: https://ieeexplore.ieee.org/author/37085614545
    ID: 37085614545
    Order: 2
    Author Affiliations:
    • Department of Industrial Engineering, University of Trento
  • Author Name: Massimo Gottardi
    Affiliation: Fondazione Bruno Kessler, Centre for Materials and Microsystems, Trento, Italy
    Author URL: https://ieeexplore.ieee.org/author/37273443400
    ID: 37273443400
    Order: 3
    Author Affiliations:
    • Fondazione Bruno Kessler, Centre for Materials and Microsystems, Trento, Italy

Image Sensor

• sensor_type: CMOS
• resolution: 64x64 pixels
• 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: Real-time image processing for event detection using memristor technology.

Supporting Organizations

• supported_by: Provincia Autonoma di Trento

Manuscript Details

• publication_date: 1-4 Nov. 2015

Relevancy Score

• score: 8
• missing_fields:
  • 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

Processed JSON Filename

request_3c9ecb2a-34c6-45e2-bc72-14cd5c823132-memristorbased_pixel_for_eventdetection_vision_sensor.json