Basic technologies for fingerprint feature extraction and matching have been improved to such a stage that they can be embedded into commercial Automatic Fingerprint Verification Systems (AFVSs). However, the reliability of AFVSs has kept attracting concerns from the society since AFVSs do fail occasionally due to difficulties like problematic fingers, changing environments, and malicious attacks. Furthermore, the absence of a solid theoretical foundation for evaluating AFVSs prevents these failures from been predicted and evaluated. Under the traditional empirical AFVS evaluation framework, repeated verification experiments, which can be very time consuming, have to be performed to test whether an update to an AFVS can really lead to an upgrade in its performance. Also, empirical verification results are often unable to provide deeper understanding of AFVSs. To solve these problems, we propose a novel statistical evaluation model for minutiae-based AFVSs based on the understanding of fingerprint minutiae patterns. This model can predict the verification performance metrics as well as their confidence intervals. The analytical power of our evaluation model, which makes it superior to empirical evaluation methods, can assist system developers to upgrade their AFVSs purposefully. Also, our model can facilitate the theoretical analysis of the advantages and disadvantages of various fingerprint verification techniques. We verify our claims through different and extensive experiments. / Chen, Jiansheng. / "November 2006." / Adviser: Yiu-Sang Moon. / Source: Dissertation Abstracts International, Volume: 68-08, Section: B, page: 5343. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 110-122). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.
Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_343809 |
Date | January 2006 |
Contributors | Chen, Jiansheng, Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
Source Sets | The Chinese University of Hong Kong |
Language | English, Chinese |
Detected Language | English |
Type | Text, theses |
Format | electronic resource, microform, microfiche, 1 online resource (x, 122 p. : ill.) |
Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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