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Complex Energy Signal Model for Digital Human Fingerprint Matching
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/></div></noscript> <!-- /Yandex.Metrika counter --> <!-- Matomo --> <!-- End Matomo Code --> <title>Complex Energy Signal Model for Digital Human Fingerprint Matching</title> <meta name="description" content="Complex Energy Signal Model for Digital Human Fingerprint Matching"> <meta name="keywords" content="Affine Invariant, Fingerprint Recognition, Matching,Minutiae."> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Complex Energy Signal Model for Digital Human Fingerprint Matching"> <meta name="citation_author" content="Jason Zalev"> <meta name="citation_author" content="Reza Sedaghat"> <meta name="citation_publication_date" content="2008/01/27"> <meta name="citation_journal_title" content="International Journal of Computer and Information Engineering"> <meta name="citation_volume" content="2"> <meta name="citation_issue" content="1"> <meta 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href="https://publications.waset.org/search?q=Reza%20Sedaghat"> Reza Sedaghat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes a complex energy signal model that is isomorphic with digital human fingerprint images. By using signal models, the problem of fingerprint matching is transformed into the signal processing problem of finding a correlation between two complex signals that differ by phase-rotation and time-scaling. A technique for minutiae matching that is independent of image translation, rotation and linear-scaling, and is resistant to missing minutiae is proposed. The method was tested using random data points. The results show that for matching prints the scaling and rotation angles are closely estimated and a stronger match will have a higher correlation. <iframe src="https://publications.waset.org/908.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Affine%20Invariant" title="Affine Invariant">Affine Invariant</a>, <a href="https://publications.waset.org/search?q=Fingerprint%20Recognition" title=" Fingerprint Recognition"> Fingerprint Recognition</a>, <a href="https://publications.waset.org/search?q=Matching" title=" Matching"> Matching</a>, <a href="https://publications.waset.org/search?q=Minutiae." title="Minutiae.">Minutiae.</a> </p> <p class="card-text"><strong>Digital Object Identifier (DOI):</strong> <a href="https://doi.org/10.5281/zenodo.1329292" target="_blank">doi.org/10.5281/zenodo.1329292</a> </p> <a href="https://publications.waset.org/908/complex-energy-signal-model-for-digital-human-fingerprint-matching" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/908/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/908/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/908/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/908/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/908/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/908/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/908/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/908/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/908/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/908/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/908.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">1318</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] Zalev, J.; Sedaghat, R., "Automatic fingerprint recognition algorithm." Electrical and Computer Engineering, 2004. Canadian Conference on, Volume: 4, 2-5 May 2004. Pages:2263 - 2266 <br>[2] Jain, A.K.; Prabhakar, S.; Hong, L.; Pankanti, S., "FingerCode: a filterbank for fingerprint representation and matching." Computer Vision and Pattern Recognition, 1999. IEEE Computer Society, Volume: 2 , 23- 25 June 1999 Pages: 193 <br>[3] Rerkrai, K.; Areekul, V., "A new reference point for fingerprint recognition." Image Processing, 2000. Proceedings. 2000 International, Volume: 2, 10-13 Sept. 2000. Pages:499 - 502 <br>[4] Bigun, J.; Bigun, T.; Nilsson, K., "Recognition by symmetry derivatives and the generalized structure tensor." Pattern Analysis and Machine Intelligence, IEEE Transactions on, Volume: 26, Issue: 12 , Dec. 2004 Pages:1590 - 1605 <br>[5] Tico, M.; Kuosmanen, P., "An algorithm for fingerprint image postprocessing." Signals, Systems and Computers, 2000. Conference Record of the Thirty-Fourth Asilomar, Volume: 2 , 29 Oct.-1 Nov. 2000 Pages:1735 - 1739 <br>[6] Lathi, B. P. "Modern Digital and Analog Communication Systems." 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