• DocumentCode
    3658392
  • Title

    Segmentation of Forensic Latent Fingerprint Images Lifted Contact-Less from Planar Surfaces with Optical Coherence Tomography

  • Author

    Rethabile Khutlang;Fulufhelo V. Nelwamondo;Ann Singh

  • Author_Institution
    Modelling &
  • Volume
    3
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    30
  • Lastpage
    34
  • Abstract
    Lifting latent fingerprints through means that do not make contact with the surface where the fingerprint is imprinted, is advantageous in many ways. Some of these advantages include: being able to lift the print multiple times, there is no physical or chemical processing of a substrate required, the substrate can be concurrently analyzed for DNA for instance, and this can provide a non-destructive lifting of the fingerprint, something that can aid in scene preservation. In this paper, we present an automatic segmentation of latent fingerprint images lifted contact-less from planar surfaces using swept source optical coherence tomography. We do not perform any localization scans as we know the position of fingerprint impressions left on a substrate. The 3-D lifted scan is processed on a per cross-sectional image basis. First the cross-sections are filtered to reduce the effects of speckle noise, then the one dimensional Sobel edge detection is applied horizontally. The detected edge represents the substrate surface plus the latent fingerprint impression left on it. They are concatenated together to form a 2-D segmented image of the lifted fingerprint. After enhancement using contrast-limited adaptive histogram equalization, minutiae were extracted from the segmented images as an implicit quality evaluation procedure, on top of the subjective one carried out. Segmented images of latent fingerprints lifted off some substrates like glass and stainless steel were of sufficient quality for minutia extraction.
  • Keywords
    "Fingerprint recognition","Substrates","Image edge detection","Image matching","Surface treatment","Image segmentation","Glass"
  • Publisher
    ieee
  • Conference_Titel
    Computer Software and Applications Conference (COMPSAC), 2015 IEEE 39th Annual
  • Electronic_ISBN
    0730-3157
  • Type

    conf

  • DOI
    10.1109/COMPSAC.2015.166
  • Filename
    7273319