The study of similarity score calculation methods for minutia-based fingerprint matching algorithms

De Kock, Antonie Johannes (2016-11)

Thesis (MSc)--Stellenbosch University, 2016

Thesis

ENGLISH ABSTRACT : This study aims to establish guidelines for calculating the similarity score between two minutia point representations of ngerprints for minutia-based ngerprint matching. Existing research does not provide clear guidelines on how to calculate the similarity score between two minutia point representations and the reported performance of most existing algorithms include those comparisons for which the point matching algorithm failed. This study therefore compares the performance of existing similarity score calculation methods after the erroneous comparisons from the point matching algorithm have been removed. It furthermore investigates in which way and to what extent these methods are a ected by intra-class variations and inter-class similarities. The results indicate that none of the existing similarity score calculation methods is superior to all the others when implemented on the FVC2002 and FVC2004 ngerprint databases. This study also proposes an improved local descriptor for local similarity score calculation and investigates whether the combination of di erent types of similarity score calculation methods better addresses intraclass variations and inter-class similarities and therefore improves pro ciency. The results indicate that similarity score calculation methods that address both global and local inter-class similarities, and are robust to intra-class variations, perform better across multiple databases. Even though this study concludes that the combination of di erent types of similarity score calculation methods generally improves pro ciency, high levels of noise and nonlinear distortion still adversely a ect performance. Future work should therefore focus on improving the stages preceding the similarity score calculation stage, i.e. minutia extraction and point matching.

AFRIKAANSE OPSOMMING : Hierdie studie poog om riglyne vir die berekening van die eendersheidtelling tussen twee minutia-puntvoorstellings van vingerafdrukke vir minutiagebaseerde vingerafdrukpassing daar te stel. Bestaande navorsing verskaf nie duidelike riglyne vir hoe om die eendersheid-telling tussen twee minutia puntvoorstellings te bereken nie en die gerapporteerde prestasie vir die meeste bestaande algoritmes sluit daardie vergelykings waarvoor die puntpassingsalgoritme misluk in. Hierdie studie vergelyk dus die prestasie van bestaande eendersheid-telling berekeningsmetodes nadat die foutiewe vergelykings van die puntpassingsalgoritme verwyder is. Dit ondersoek ook op watter manier en in watter mate hierdie metodes deur intra-klas variasies en inter-klas ooreenstemmings beïnvloed word. Die resultate dui daarop dat geen van die bestaande eendersheid-telling berekeningsmetodes better as al die ander vaar wanneer dit op die FVC2002 en FVC2004 vingerafdruk databasisse geïmplementeer word nie. Hierdie studie stel ook 'n verbeterde lokale beskrywer vir lokale eendersheid-telling berekening voor en ondersoek of die kombinasie van verskillende eendersheid-telling berekeingsmetodes intra-klas variasies and inter-klas ooreenstemmings beter aanspreek en dus die prestasie verhoog. Die resultate dui daarop dat eendersheid-telling berekeningsmetodes wat beide globale en lokale inter-klas ooreenstemmings aanspreek, en onsensitief ten opsigte van intra-klas variasies is, beter oor veelvuldige databasisse vaar. Nieteenstaande die feit dat hierdie studie die gevolgtrekking maak dat die kombinasie van verskillende tipes van eendersheid-telling berekeningsmetodes die prestasie in die algemeen verhoog, word die prestasie steeds deur hoë ruisvlakke en nie-lineêre vervorming verswak. Toekomstige werk moet dus op die verbetering van die stadia wat die eerdersheid-telling berekeningstadium voorafgaan fokus, m.a.w. minutia-onttrekking en puntpassing.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/100100
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