Cmos Image Sensor Applications And Working Principles

• doi: 10.1049/icp.2024.4462
• title: CMOS image sensor applications and working principles
• publisher: IET
• isbn: 978-1-83724-267-2
• issn:
• rank: 1818
• access_type: LOCKED
• content_type: Conferences
• abstract: Complementary Metal Oxide Semiconductor (CMOS) image sensor is a fundamental component that is widely used in industries that require imaging, such as in digital cameras or smartphones. It can convert optical images to electronic signals, allowing engineers to recover the original image or analyse the signals in subsequent procedures. The rapid expansion of the transistor market in recent years has significantly contributed to the development of CMOS technology. These iterations make CMOS image sensor able to be applied in more advance industries, including autonomous vehicles and biometrics. This paper presents a basic introduction to the history and recent developments of CMOS image sensor and its applications in multiple related fields. Then, a project that design a 3*3 pixels CMOS image sensor will be illustrated, in which will further interpret how an image sensor functions to meet specific requirements. Some basic circuit diagrams will also be presented for readers better understanding and a final output image will be generated through Excel.
• article_number: 10854192
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10854192
• html_url: https://ieeexplore.ieee.org/document/10854192/
• abstract_url: https://ieeexplore.ieee.org/document/10854192/
• publication_title: 2nd International Conference on Mechatronic Automation and Electrical Engineering (ICMAEE 2024)
• conference_location: Hybrid Conference, Nanjing, China
• conference_dates: 22-24 Nov. 2024
• publication_number: 10853224
• is_number: 10853225
• publication_year: 2024
• publication_date: 22-24 Nov. 2024
• start_page: 98
• end_page: 104
• citing_paper_count: 0
• citing_patent_count: 0
• download_count: 15
• insert_date: 20250127
• index_terms:
  • dynamic_index_terms:
    • Image Sensor
    • Camera Sensor
    • Digital Camera
    • Autonomous Vehicles
    • Autonomous Driving
    • Image Quality
    • Surveillance System
    • Current Source
    • Current Regulations
    • Photodetector
    • Low Light
    • Optical Signal
    • Voltage Pulses
    • Low Light Conditions
    • Dark Current
    • P-n Junction
    • Capping Layer
    • Drain Current
    • Sensor Pixel
    • PIN Photodiode
    • Mobile App
    • Mobile Application
    • Smartphone Application
    • Smartphone App
• isbn_formats:
  • format: Electronic ISBN, value: 978-1-83724-267-2, isbnType: New-2005
• authors:
  • Author Name: Penghao Wang
    Affiliation: School of Engineering, The Hong Kong University of Science and Technology, Hong KongPeople's Republic of China
    Author URL: https://ieeexplore.ieee.org/author/37090029267
    ID: 37090029267
    Order: 1
    Author Affiliations:
    • School of Engineering, The Hong Kong University of Science and Technology, Hong KongPeople's Republic of China

Image Sensor

• sensor_type: CMOS
• resolution: 3x3 pixels
• dynamic_range: Not specified
• pixel_size: Not specified
• dark_current: Low (in pA or less) for low light conditions application, unspecified for standard CMOS sensor design in paper's context, typically under 10µA in cutoff mode for standard design context, detailed in specialized low light sensor section as low current operation near zero volts)

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

• power_consumption: Lower compared to CCD
• noise: Higher noise with passive pixel sensors, increased when using low light designs as dark current is magnified

Applications & Benefits

• cell_imaging: Suitable for low light and high-speed applications as highlighted in specialized CMOS sensor design section.
• benefits: Lower power consumption, capability for pixel-level processing, smaller size suitable for smartphones, intelligent surveillance without identifiable images, applicable in autonomous vehicles.

Supporting Organizations

• supported_by: The Hong Kong University of Science and Technology

Manuscript Details

• publication_date: 22-24 Nov. 2024

Relevancy Score

• score: 9
• missing_fields:
  • fill factor
  • quantum efficiency
  • readout speed
  • noise sources
  • analog-to-digital conversion techniques
  • microlenses
  • on-chip colour filters
  • global or rolling shutters
  • backside illumination

Processed JSON Filename

request_d40637ef-6d13-4af0-a211-d709fec3092e-cmos_image_sensor_applications_and_working_principles.json