Robust Minutia-Based Fingerprint Verification - Bookswagon
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Robust Minutia-Based Fingerprint Verification

Robust Minutia-Based Fingerprint Verification


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About the Book

This dissertation, "Robust Minutia-based Fingerprint Verification" by Huimin, Deng, 鄧惠民, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled \Robust Minutia-Based Fingerprint Verication" Submitted by Huimin Deng for the degree of Doctor of Philosophy at The University of Hong Kong in September 2006 In a network connected world, security is becoming a more and more important issue. There are a number of means for enhancing the security, notably, biomet- rics, where ngerprint verication is the most popular and successful technology. Fingerprint verication technology has been improved continuously and widely regarded since the development of Fingerprint Verication Competition (FVC). Buttherearestillalotofopenproblemsforthistechnology. Theperformanceof ngerprint verication is still highly related to image quality. Immature sensor technology and distortion due to incorrect operation and physical skin scathe may result in poor image quality. Minutiae matching is generally used in nger- printverication. Inthisthesis, ourobjectiveistodesignarobustminutia-based ngerprintvericationsystemwhichcanmakeitsdeterminationwithahighlevel of condence. We have developed a minutia extraction algorithm which works well for FVC databases without setting database-dependent control parameters. We derive a quality measure for each candidate minutia to extract true minu- tiae and to remove false minutiae. For the matching stage, we have proposed a novel approach which is based on aligned-edge-guided triangle matching. We have proposed a structural approach and a dynamic time warping approach to calculate the similarity between two ngerprint images. A feature level fusion and a decision level fusion stage are proposed to improve performance. We con- duct experiments on the databases of FVC2000, FVC2002 and FVC2004. The results show that our approaches perform very well with all these databases. DOI: 10.5353/th_b3703642 Subjects: Fingerprints - Identification Fingerprints - Data processing Algorithms


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Product Details
  • ISBN-13: 9781361434024
  • Publisher: Open Dissertation Press
  • Publisher Imprint: Open Dissertation Press
  • Height: 279 mm
  • No of Pages: 120
  • Weight: 295 gr
  • ISBN-10: 1361434023
  • Publisher Date: 27 Jan 2017
  • Binding: Paperback
  • Language: English
  • Spine Width: 6 mm
  • Width: 216 mm


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