@misc{10481/44550,
year = {2016},
url = {http://hdl.handle.net/10481/44550},
abstract = {This thesis starts by presenting a deep study of the scientific literature on minutiae-based
local matching matching techniques, establishing a taxonomy of the available local structures and
consolidation methods, and highlighting the main advantages and drawbacks of each of them.
Then, we will present a minutiae filtering algorithm that removes spurious or misleading minutiae to
improve both the identification time and the accuracy of the recognition process. After that, we will
describe two frameworks for massively parallel fingerprint identification, which are able to execute
diffierent matching algorithms adapting to the underlying hardware for maximum performance and
full scalability. We will also develop a framework to combine the information of two fingerprints
and the capabilities of two diferent matching algorithms to address both problems that hinder
identification in large databases: the high identification time and the loss of accuracy. Finally, we
describe a new classification strategy to reduce the penetration rate of the identification. Finally
After this introduction section, Section 2 describes in detail the background of the main areas
addressed in this thesis: fingerprint feature extraction (Section 2.1), fingerprint identification (Section
2.2), high performance computing (Section 2.3), database penetration reduction and fingerprint
classification (Section 2.4) and information fusion for fingerprint identification (Section 2.5).
After that, Section 3 presents the justification of this memory, describing the open problems
addressed throughout this thesis. The objectives pursued to address these problems are detailed
in Section 4, along with the methodology followed along the thesis in Section 5. Section 6 summarizes
the works that compose this memory, while Section 7 presents the results obtained in them,
performing an analysis in relation with the tackled objectives and how they have been reached.
Section 8 presents the conclusions after the work carried out for this thesis. Finally, in Section 9
we point out several future lines of work that have been derived from the results achieved.},
organization = {Tesis Univ. Granada. Programa Oficial de Doctorado en: Tecnologías de la Información y la Comunicación},
organization = {Becas de Formacióon de Profesorado Universitario del Ministerio de Educación y Ciencia, en su Resolución del 28 de
Febrero de 2013, bajo la referencia FPU12/04902.},
publisher = {Universidad de Granada},
keywords = {Minería de datos},
keywords = {Identificación},
keywords = {Dactiloscopia},
keywords = {Computación de altas prestaciones},
keywords = {Proceso electrónico de datose},
title = {Minería de datos en computación de altas prestaciones para identificación en base a huellas dactilares},
author = {Peralta, Daniel},
}