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dc.contributor.advisorHadidi, Nasser
dc.contributor.authorMoua, Cha Poa.
dc.contributor.authorBoldischar, Mike
dc.date.accessioned2011-05-23T17:23:38Z
dc.date.available2011-05-23T17:23:38Z
dc.date.issued2007
dc.identifier.urihttp://digital.library.wisc.edu/1793/52923
dc.description.abstractAs a means of access control and criminal identification, Automated Fingerprint Identification Systems (AFIS) are widely utilized. In many areas of business, these systems are entrusted to verify identities of personnel before allowing access to restricted information or facilities. In the area of criminal investigation, these same systems are entrusted to find, match, and identify criminals. Obviously, these systems are given critical tasks and are performing them unsupervised most of the time. Although most steps in the process are procedural and can be automated, there are two critical phases that need to be performed intelligently and reliably. These two phases are edge detection and feature extraction. In order to enhance important features accurately in the fingerprint image, methods in edge detection are applied. Once the important features are exposed and artifacts are removed, feature extraction takes place. In this phase, the print is characterized by the extracted features for matching later. This article looks at the theoretical foundations and practical aspects of these two phases to understand their automation.en
dc.rightsAll rights reserved. No part of this journal may be reproduced in any form without the permission of the University of Wisconsin-Stout.
dc.subject.lcshFingerprints--Identification--Data processing
dc.subject.lcshFingerprints--Identification
dc.titleEdge detection and feature extraction in automated fingerprint identification systemsen
dc.typeArticleen


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