Bimodal Palm Biometric Feature Extraction Using A Single Rgb Image

• doi:
• title: Bimodal palm biometric feature extraction using a single RGB image
• publisher: IEEE
• isbn: 978-3-88579-624-4
• issn:
• rank: 1719
• access_type: LOCKED
• content_type: Conferences
• abstract: This paper proposes a method for palm bimodal biometric feature (vein and crease pattern) acquisition from a single RGB image. Typical bimodal biometric systems require combining infrared and visible images for this task. We use a single CMOS color sensor and a specific illumination comprising of two wavelengths to acquire the image. As a result each biometric modality is more pronounced in its own color channel. The image is processed by applying adapted matched filters with non-linear modifications. Performance of the proposed method is evaluated against feature separation with optical band-pass and band-stop approach on a database of 64 people. The results show the average true positive rate is 70.6 % for vein detection and 64.7 % for crease detection, whereas in 14.8 % and 9.29 % of the cases feature of wrong modality is detected.
• article_number: 7029410
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7029410
• html_url: https://ieeexplore.ieee.org/document/7029410/
• abstract_url: https://ieeexplore.ieee.org/document/7029410/
• publication_title: 2014 International Conference of the Biometrics Special Interest Group (BIOSIG)
• conference_location: Darmstadt, Germany
• conference_dates: 10-12 Sept. 2014
• publication_number: 7023494
• is_number: 7029401
• publication_year: 2014
• publication_date: 10-12 Sept. 2014
• start_page: 1
• end_page: 7
• citing_paper_count: 0
• citing_patent_count: 0
• download_count: 211
• insert_date: 20150205
• index_terms:
  • ieee_terms:
    • Kernel
    • Veins
    • Image color analysis
    • Biomedical imaging
    • Feature extraction
    • Lighting
  • dynamic_index_terms:
    • RGB Images
    • Biometric Characteristics
    • Biometric Features
    • Bimodal Character
    • Bimodal Feature
    • Color Channels
    • Matched Filter
    • Biometric Systems
    • Blood Vessels
    • False Positive Rate
    • Linewidth
    • Rotation Angle
    • Near-infrared Spectroscopy
    • Near-infrared Spectra
    • Image Sensor
    • Camera Sensor
    • Red Channel
    • Near-infrared Light
    • Optical Filter
    • Blue Channel
    • Ground Truth Image
    • Artifact Removal
    • Marked Regions
    • Filter Kernel
    • Filter Response
    • Modal Features
    • Modal Characteristics
    • Example Of Distribution
    • Filter Structure
    • RGB Channels
    • Dark Regions
    • Thick Line
• isbn_formats:
  • format: Print ISBN, value: 978-3-88579-624-4, isbnType: New-2005
  • format: Electronic ISBN, value: 978-3-88579-624-4, isbnType: New-2005
• authors:
  • Author Name: Teodors Eglitis
    Affiliation: Institute of Electronics and Computer Science, Riga, Latvia
    Author URL: https://ieeexplore.ieee.org/author/37075883400
    ID: 37075883400
    Order: 1
    Author Affiliations:
    • Institute of Electronics and Computer Science, Riga, Latvia
  • Author Name: Mihails Pudzs
    Affiliation: Institute of Electronics and Computer Science, Riga, Latvia
    Author URL: https://ieeexplore.ieee.org/author/37567477300
    ID: 37567477300
    Order: 2
    Author Affiliations:
    • Institute of Electronics and Computer Science, Riga, Latvia
  • Author Name: Modris Greitans
    Affiliation: Institute of Electronics and Computer Science, Riga, Latvia
    Author URL: https://ieeexplore.ieee.org/author/37568146100
    ID: 37568146100
    Order: 3
    Author Affiliations:
    • Institute of Electronics and Computer Science, Riga, Latvia

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: CMOS image sensors enable digital imaging across several applications including smartphones, medical devices, and automotive systems.

Supporting Organizations

• supported_by: not specified

Manuscript Details

• publication_date: 10-12 Sept. 2014

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
  • supported_by
  • publication_date

Processed JSON Filename

request_0386def5-c9c5-4e74-a85c-1cefb3ee056f-bimodal_palm_biometric_feature_extraction_using_a_single_rgb_image.json