Dissertation/Thesis Abstract

A Novel Global Pattern Recognition Algorithm
by Stoffa, Joseph M., Ph.D., West Virginia University, 2010, 185; 3448238
Abstract (Summary)

The background, development, performance assessment, and analysis of a novel pattern recognition algorithm that is applicable to any set of binary images are discussed. The efficacy of the algorithm when applied to the problem of fingerprint recognition is quantified. The conclusion was that the algorithm is relatively poor as a fingerprint identification algorithm, averaging an equal error rate of approximately 19% as calculated by the rules specified in the Year 2000 Fingerprint Verification Competition. The positive attributes of the algorithm were its ultra-fast matching times, orientation independence, lack of rejection events, relative insensitivity to resolution difference, and one-way transformations. The mechanism of algorithm operation as applied to fingerprints was investigated using integral geometry. This investigation showed that the algorithm was an indirect measure of ridge width, which explained the algorithm’s relatively poor performance. Another set of experiments suggests that the algorithm may be well-suited to other pattern recognition problems, specifically cloud and precipitation particle recognition and camouflage recognition. In summary, the research extends the field of pattern recognition by developing, assessing the performance, and determining the mechanism of operation of a novel pattern recognition algorithm that is applicable to any set of binary images.

Indexing (document details)
Advisor: Stiller, Alfred H.
School: West Virginia University
School Location: United States -- West Virginia
Source: DAI-B 72/05, Dissertation Abstracts International
Subjects: Applied Mathematics, Chemical engineering, Computer science
Keywords: Fingerprint recognition, Pattern recognition, Random walks
Publication Number: 3448238
ISBN: 978-1-124-54318-5
Copyright © 2020 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy