Title page for ETD etd-07142011-112818


Type of Document Master's Thesis
Author Hoyle, Kevin
Author's Email Address kevin87@vt.edu
URN etd-07142011-112818
Title Minutiae Triplet-based Features with Extended Ridge Information for Determining Sufficiency in Fingerprints
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Hsiao, Michael S. Committee Chair
Abbott, A. Lynn Committee Member
Fox, Edward Alan Committee Member
Keywords
  • minutia
  • sufficiency
  • latent
  • quality
  • fingerprints
  • friction ridges
  • triangles
  • triplets
Date of Defense 2011-07-06
Availability unrestricted
Abstract
In order to deliver statistical and qualitative backing to latent fingerprint evidence, algorithms are proposed (1) to perform fingerprint matching to aid in quality assessment, and (2) to discover statistically rare features or patterns in fingerprints. These features would help establish an objective minimum-quality baseline for latent prints as well as aid in the latent examination process in making a matching comparison. The proposed methodologies use minutiae triplet-based features in a hierarchical fashion, where not only minutia points are used, but ridge information is used to help establish relations between minutiae. Results show (1) that our triplet-based descriptor is useful in eliminating false matches in the matching algorithm, and (2) that a set of distinctive features can be found that have sufficient discriminatory power to aid in quality

assessment.

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