An 161Mw Mixedsignal Column Processor For Brisk Feature Extraction In Cmos Image Sensor

• doi: 10.1109/ISCAS.2014.6865064
• title: An 1.61mW mixed-signal column processor for BRISK feature extraction in CMOS image sensor
• publisher: IEEE
• isbn: 978-1-4799-3431-7
• issn: 2158-1525
• rank: 1437
• access_type: LOCKED
• content_type: Conferences
• abstract: In mobile object recognition (OR) applications, the power consumption of image sensor and data communication between image sensor and digital OR processor becomes crucial as digital OR processor consumes less power in deep sub-micron process. To reduce the amount of data transaction from image sensor to digital OR processor, digital/analog mixed-signal focal-plane processing of Binary Robust Invariant Scalable Keypoints (BRISK) feature extraction in CMOS image sensor (CIS) is proposed. The proposed CIS processor sends BRISK feature vectors instead of the whole image pixel data, resulting in 79% reduction of data communication. In this work, mixed-signal processing of corner detection and successive approximation register (SAR)-based scoring are implemented for BRISK feature point detection. To achieve scale-invariance in object recognition, scale-space is generated and stored in analog line memory. In addition, noise reduction scheme is integrated in column processing chain to remove salt and pepper noise, which degrades recognition accuracy. In a post layout simulation, the proposed system achieves 0.70pW/pixel*frame*feature at 30fps in a 130nm CMOS technology, which is 13.6% lower than the state-of-the-art.
• article_number: 6865064
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6865064
• html_url: https://ieeexplore.ieee.org/document/6865064/
• abstract_url: https://ieeexplore.ieee.org/document/6865064/
• publication_title: 2014 IEEE International Symposium on Circuits and Systems (ISCAS)
• conference_location: Melbourne, VIC, Australia
• conference_dates: 1-5 June 2014
• publication_number: 6852006
• is_number: 6865048
• publication_year: 2014
• publication_date: 1-5 June 2014
• start_page: 57
• end_page: 60
• citing_paper_count: 4
• citing_patent_count: 1
• download_count: 477
• insert_date: 20140726
• index_terms:
  • ieee_terms:
    • Feature extraction
    • Noise
    • Filtering
    • Image resolution
    • Vectors
    • Object recognition
    • Image sensors
  • dynamic_index_terms:
    • Image Sensor
    • Camera Sensor
    • Imaging Data
    • Denoising
    • Noise Reduction
    • Digital Communication
    • Data Communication
    • Digital Citizenship
    • Object Recognition
    • Feature Points
    • Characteristic Points
    • Scale-invariant
    • Salt And Pepper Noise
    • Pepper Noise
    • Feature Point Detection
    • Interest Point Detection
    • Feature Detection
    • Feature Extraction Process
    • Dark State
    • Mean Filter
    • Multiple Resolutions
    • Advanced Driver Assistance Systems
    • Driver Assistance Systems
    • Histogram Of Oriented Gradients
    • Bright State
    • Analog Domain
    • Speeded Up Robust Features
    • Descriptor Vector
• isbn_formats:
  • format: CD, value: 978-1-4799-3431-7, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-4799-3432-4, isbnType: New-2005
• authors:
  • Author Name: Kyeongryeol Bong
    Affiliation: Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
    Author URL: https://ieeexplore.ieee.org/author/37085520085
    ID: 37085520085
    Order: 1
    Author Affiliations:
    • Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
  • Author Name: Gyeonghoon Kim
    Affiliation: Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
    Author URL: https://ieeexplore.ieee.org/author/37714807800
    ID: 37714807800
    Order: 2
    Author Affiliations:
    • Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
  • Author Name: Injoon Hong
    Affiliation: Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
    Author URL: https://ieeexplore.ieee.org/author/38242546400
    ID: 38242546400
    Order: 3
    Author Affiliations:
    • Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
  • Author Name: Hoi-jun Yoo
    Affiliation: Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
    Author URL: https://ieeexplore.ieee.org/author/37274307200
    ID: 37274307200
    Order: 4
    Author Affiliations:
    • Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

Image Sensor

• sensor_type: CMOS
• resolution: 320x240
• 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

• frame_rate: 30fps
• power_consumption: 1.61mW @30fps
• noise: Salt and pepper noise reduction implemented

Applications & Benefits

• cell_imaging: Used in low-power object recognition applications such as augmented reality and advanced driver assistance systems.
• benefits: Reduced data transaction by 79%, achieving low power consumption per feature extraction.

Supporting Organizations

• supported_by: Korea Advanced Institute of Science and Technology (KAIST)

Manuscript Details

• publication_date: 1-5 June 2014

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

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