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Morphing of Fingerprints
Dovičic, Denis ; Sakin, Martin (oponent) ; Kanich, Ondřej (vedoucí práce)
This bachelor`s thesis deals with the creation of a realistic looking fingerprint with a double identity. The goal is the design and subsequent implementation of an algorithm to create such a morphed fingerprint. The morphing consists of three important steps, extracting the information from the fingerprint, morphing the information to generate a new fingerprint, and verifying the morphed fingerprint against both originals to evaluate the double identity rating. As an extension, an algorithm for blurring the edges of a morphed fingerprint was implemented, the Minutia Cylinder-Code SDK was integrated into the application to immediately obtain double identity rating, and the method of obtaining suitable identities from the original fingerprints was modified to improve results. The implemented algorithms were tested on a fingerprint database, where it was shown that in the absence of damage, the information from the fingerprint is reliably extracted, from 90 % cases the morphed fingerprint acquired two identities and from 60 % it also had a realistic appearance.
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Morphed Fingerprint Detection
Dovičic, Denis ; Drahanský, Martin (oponent) ; Kanich, Ondřej (vedoucí práce)
This diploma thesis deals with the detection of morphed fingerprints, following my bachelor's thesis and project practice. There is no public work dealing with the detection of morphed fingerprints so far. Morphed and normal fingerprints are considered stochastic textures and described by binarized statistical properties, which are estimated as independent components of the scene. To achieve the goal, the classification algorithm support vector machine was chosen. SVM learns features from the histograms modeling the probability of occurrence of the BSIF descriptor in the texture. Testing was performed on morphed fingerprints, which originated from several fingerprint datasets: Bergdata, Sagem MSO, SecuGen and synthetic. SVM with polynomial kernel function proved to be the most optimal detector with an accuracy of 98 % on the Bergdata sensor dataset, 98.5 % on the Sagem MSO, 94.97 % on the SecuGen and 100 % on the synthetic fingerprints. Detection accuracy on the adaptive morphing method from my project practice is 98.85 % on the Bergdata sensor dataset, 98.49 % on the Sagem MSO, 94.97 % on the SecuGen and 100 % on the synthetic fingerprints. The improved merphing method from my project practice has not shown an effect on preventing morphing detection, although it generates stronger double identities.
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Morphing of Fingerprints
Dovičic, Denis ; Sakin, Martin (oponent) ; Kanich, Ondřej (vedoucí práce)
This bachelor`s thesis deals with the creation of a realistic looking fingerprint with a double identity. The goal is the design and subsequent implementation of an algorithm to create such a morphed fingerprint. The morphing consists of three important steps, extracting the information from the fingerprint, morphing the information to generate a new fingerprint, and verifying the morphed fingerprint against both originals to evaluate the double identity rating. As an extension, an algorithm for blurring the edges of a morphed fingerprint was implemented, the Minutia Cylinder-Code SDK was integrated into the application to immediately obtain double identity rating, and the method of obtaining suitable identities from the original fingerprints was modified to improve results. The implemented algorithms were tested on a fingerprint database, where it was shown that in the absence of damage, the information from the fingerprint is reliably extracted, from 90 % cases the morphed fingerprint acquired two identities and from 60 % it also had a realistic appearance.
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