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Impressão digital metabólica do gênero Espeletia (Asteraceae) e sua correlação com dados filogenéticos e biogeográficos; Metabolomic fingerprint of the genus Espeletia (Asteraceae) and its correlation with phylogenetic and biogeographic data

Gonzalez, Guillermo Federico Padilla
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 15/09/2014 PT
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26.3%
O gênero Espeletia Mutis ex Bonpl (Asteraceae, Millerieae, Espeletiinae) constitui um exemplo clássico de um táxon sujeito a rápidos processos adaptativos evolutivos. Com ca. 71 espécies, este gênero se diversificou em elevadas altitudes num ecossistema emergente formado após o retraimento dos glaciares no final do Plioceno e início do Pleistoceno, os páramos, um tipo de ecossistema que biogeograficamente funciona como um complexo de "ilhas" presentes principalmente no noroeste dos Andes tropicais da Venezuela, Colômbia e Equador. Devido à sua complexa história evolutiva e morfologia característica, este gênero tem sido foco de muitas pesquisas envolvendo sua biologia, ecologia, taxonomia e filogenia. No entanto, do ponto de vista fitoquímico, tem sido pouco estudado e é desconhecida a influência da geografia na química do metabolismo secundário destas espécies. Neste estudo, a impressão digital metabólica de 120 amostras do gênero Espeletia foi obtida por UHPLC-UV-MS e submetida a análises quimiométricas. A correlação com dados geográficos revelou uma forte influência da biogeografia no metabolismo secundário das espécies deste gênero, apresentando uma impressão digital característica de acordo com seu país de origem numa escala global e de acordo com complexo de páramos de origem numa escala regional...

Estimativa de qualidade de impressões digitais utilizando Sistemas de Inferência Fuzzy; Fingerprint quality estimation using Fuzzy Inference Systems

Tada, Carlos Henrique Moniwa
Fonte: Universidade de Brasília Publicador: Universidade de Brasília
Tipo: Dissertação
POR
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26.38%
Dissertação (Mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2011.; A qualidade da imagem de impressões digitais influencia o desempenho de sistemas automáticos de reconhecimento de impressões digitais, tais como o AFIS. Este trabalho propõe um esquema híbrido para estimativa de qualidade de imagens de impressão digital usando medidas de características locais (contraste, curvatura, fluxo de cristas papilares) e globais (área e espectro de potência no domínio da frequência). Sistemas de inferência fuzzy são usados para combinação dessas medidas e obtenção de uma pontuação de qualidade. São feitos testes usando imagens de impressões digitais das bases de dados DB2-A e DB4-A do Fingerprint Verification Competition 2006 (FVC 2006) e o programa de identificação de digitais BOZORTH3 do NIST Biometric Image Software (NBIS). É feita uma comparação do desempenho do método proposto com o programa NFIQ. Com a remoção de 5%, 10% e 15% das impressões digitais de pior qualidade da base DB2-A, obteve-se uma melhora no EER (equal error rate) de 14,4%, 29,4% e 46,6%, respectivamente. Para a DB4-A...

Improving Fingerprint Verification Using Minutiae Triplets

Medina-Pérez, Miguel Angel; García-Borroto, Milton; Gutierrez-Rodríguez, Andres Eduardo; Altamirano-Robles, Leopoldo
Fonte: Molecular Diversity Preservation International (MDPI) Publicador: Molecular Diversity Preservation International (MDPI)
Tipo: Artigo de Revista Científica
Publicado em 08/03/2012 EN
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26.37%
Improving fingerprint matching algorithms is an active and important research area in fingerprint recognition. Algorithms based on minutia triplets, an important matcher family, present some drawbacks that impact their accuracy, such as dependency to the order of minutiae in the feature, insensitivity to the reflection of minutiae triplets, and insensitivity to the directions of the minutiae relative to the sides of the triangle. To alleviate these drawbacks, we introduce in this paper a novel fingerprint matching algorithm, named M3gl. This algorithm contains three components: a new feature representation containing clockwise-arranged minutiae without a central minutia, a new similarity measure that shifts the triplets to find the best minutiae correspondence, and a global matching procedure that selects the alignment by maximizing the amount of global matching minutiae. To make M3gl faster, it includes some optimizations to discard non-matching minutia triplets without comparing the whole representation. In comparison with six verification algorithms, M3gl achieves the highest accuracy in the lowest matching time, using FVC2002 and FVC2004 databases.

Analysis of TP53 mutation spectra reveals the fingerprint of the potent environmental carcinogen, aristolochic acid

Hollstein, M; Moriya, M.; Grollman, AP; Olivier, M
Fonte: PubMed Publicador: PubMed
Tipo: Artigo de Revista Científica
EN
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26.19%
Genetic alterations in cancer tissues may reflect the mutational fingerprint of environmental carcinogens. Here we review the evidence that support the role of aristolochic acid (AA) in inducing a mutational fingerprint in the tumor suppressor gene TP53 in urothelial carcinomas of the upper urinary tract (UUT). Exposure to AA, a nitrophenathrene carboxylic acid present in certain herbal remedies and in flour prepared from wheat grain contaminated with seeds of Aristolochia clematitis, has been linked to chronic nephropathy and UUT. TP53 mutations in UUT of individuals exposed to AA reveal a unique pattern of mutations characterised by A to T transversions on the non-transcribed strand, which cluster at hotspots rarely mutated in other cancers. This unusual pattern, originally discovered in UUTs from two different populations, one in Taiwan, and one in the Balkans, has been reproduced experimentally by treating mouse cells that harbour human TP53 sequences with AA. The convergence of molecular epidemiological and experimental data establishes a clear causal association between exposure to the human carcinogen AA and UUT cancer. Despite bans on the sale of herbs containing AA, their use continues, raising global public health concern and an urgent need to identify populations at risk.

The human uterine smooth muscle S-nitrosoproteome fingerprint in pregnancy, labor, and preterm labor

Ulrich, Craig; Quilici, David R.; Schlauch, Karen A.; Buxton, Iain L. O.
Fonte: American Physiological Society Publicador: American Physiological Society
Tipo: Artigo de Revista Científica
EN
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26.07%
Molecular mechanisms involved in uterine quiescence during gestation and those responsible for induction of labor at term are incompletely known. More than 10% of babies born worldwide are premature and 1,000,000 die annually. Preterm labor results in preterm delivery in 50% of cases in the United States explaining 75% of fetal morbidity and mortality. There is no Food and Drug Administration-approved treatment to prevent preterm delivery. Nitric oxide-mediated relaxation of human uterine smooth muscle is independent of global elevation of cGMP following activation of soluble guanylyl cyclase. S-nitrosation is a likely mechanism to explain cGMP-independent relaxation to nitric oxide and may reveal S-nitrosated proteins as new therapeutic targets for the treatment of preterm labor. Employing S-nitrosoglutathione as an nitric oxide donor, we identified 110 proteins that are S-nitrosated in 1 or more states of human pregnancy. Using area under the curve of extracted ion chromatograms as well as normalized spectral counts to quantify relative expression levels for 62 of these proteins, we show that 26 proteins demonstrate statistically significant S-nitrosation differences in myometrium from spontaneously laboring preterm patients compared with nonlaboring patients. We identified proteins that were up-S-nitrosated as well as proteins that were down-S-nitrosated in preterm laboring tissues. Identification and relative quantification of the S-nitrosoproteome provide a fingerprint of proteins that can form the basis of hypothesis-directed efforts to understand the regulation of uterine contraction-relaxation and the development of new treatment for preterm labor.

The Human Urinary Proteome Fingerprint Database UPdb

Husi, Holger; Barr, Janice B.; Skipworth, Richard J. E.; Stephens, Nathan A.; Greig, Carolyn A.; Wackerhage, Henning; Barron, Rona; Fearon, Kenneth C. H.; Ross, James A.
Fonte: Hindawi Publishing Corporation Publicador: Hindawi Publishing Corporation
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
26.19%
The use of human urine as a diagnostic tool has many advantages, such as ease of sample acquisition and noninvasiveness. However, the discovery of novel biomarkers, as well as biomarker patterns, in urine is hindered mainly by a lack of comparable datasets. To fill this gap, we assembled a new urinary fingerprint database. Here, we report the establishment of a human urinary proteomic fingerprint database using urine from 200 individuals analysed by SELDI-TOF (surface enhanced laser desorption ionisation-time of flight) mass spectrometry (MS) on several chip surfaces (SEND, HP50, NP20, Q10, CM10, and IMAC30). The database currently lists 2490 unique peaks/ion species from 1172 nonredundant SELDI analyses in the mass range of 1500 to 150000. All unprocessed mass spectrometric scans are available as “.xml” data files. Additionally, 1384 peaks were included from external studies using CE (capillary electrophoresis)-MS, MALDI (matrix assisted laser desorption/ionisation), and CE-MALDI hybrids. We propose to use this platform as a global resource to share and exchange primary data derived from MS analyses in urinary research.

How integration of global omics-data could help preparing for pandemics – a scent of influenza

Bos, Lieuwe D. J.; de Jong, Menno D.; Sterk, Peter J.; Schultz, Marcus J.
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 22/04/2014 EN
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26.02%
Pandemics caused by novel emerging or re-emerging infectious diseases could lead to high mortality and morbidity world-wide when left uncontrolled. In this perspective, we evaluate the possibility of integration of global omics-data in order to timely prepare for pandemics. Such an approach requires two major innovations. First, data that is obtained should be shared with the global community instantly. The strength of rapid integration of simple signals is exemplified by Google’sTM Flu Trend, which could predict the incidence of influenza-like illness based on online search engine queries. Second, omics technologies need to be fast and high-throughput. We postulate that analysis of the exhaled breath would be a simple, rapid and non-invasive alternative. Breath contains hundreds of volatile organic compounds that are altered by infection and inflammation. The molecular fingerprint of breath (breathprint) can be obtained using an electronic nose, which relies on sensor technology. These breathprints can be stored in an online database (a “breathcloud”) and coupled to clinical data. Comparison of the breathprint of a suspected subject to the breathcloud allows for a rapid decision on the presence or absence of a pathogen.

Minutia Tensor Matrix: A New Strategy for Fingerprint Matching

Fu, Xiang; Feng, Jufu
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 30/03/2015 EN
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26.53%
Establishing correspondences between two minutia sets is a fundamental issue in fingerprint recognition. This paper proposes a new tensor matching strategy. First, the concept of minutia tensor matrix (simplified as MTM) is proposed. It describes the first-order features and second-order features of a matching pair. In the MTM, the diagonal elements indicate similarities of minutia pairs and non-diagonal elements indicate pairwise compatibilities between minutia pairs. Correct minutia pairs are likely to establish both large similarities and large compatibilities, so they form a dense sub-block. Minutia matching is then formulated as recovering the dense sub-block in the MTM. This is a new tensor matching strategy for fingerprint recognition. Second, as fingerprint images show both local rigidity and global nonlinearity, we design two different kinds of MTMs: local MTM and global MTM. Meanwhile, a two-level matching algorithm is proposed. For local matching level, the local MTM is constructed and a novel local similarity calculation strategy is proposed. It makes full use of local rigidity in fingerprints. For global matching level, the global MTM is constructed to calculate similarities of entire minutia sets. It makes full use of global compatibility in fingerprints. Proposed method has stronger description ability and better robustness to noise and nonlinearity. Experiments conducted on Fingerprint Verification Competition databases (FVC2002 and FVC2004) demonstrate the effectiveness and the efficiency.

Quantifying uncertainties in climate system properties using recent climate observations

Fonte: MIT Joint Program on the Science and Policy of Global Change Publicador: MIT Joint Program on the Science and Policy of Global Change
Formato: 15 p.; 289170 bytes; application/pdf
ENG
Relevância na Pesquisa
26.02%
We apply the optimal fingerprint detection algorithm to three independent diagnostics of the recent climate record and derive joint probability density distributions for three uncertain properties of the climate system. The three properties are climate sensitivity, the rate of heat uptake by the deep ocean, and the strength of the net aerosol forcing. Knowing the probability distribution for these properties is essential for quantifying uncertainty in projections of climate change. We briefly describe each diagnostic and indicate its role in constraining these properties. Based on the marginal probability distributions, the 5 to 95% confidence intervals are 1.4 to 7.7K for climate sensitivity and 0.30 to 0.95 W/m^2 for the net aerosol forcing using uniform priors; and 1.3 to 4.2K and 0.26 to 0.88 W/m^2 using an expert prior for climate sensitivity. The oceanic heat uptake is not so well constrained. The uncertainty in the net aerosol forcing in either case is much less than the uncertainty range usually quoted for the indirect aerosol forcing alone.; Includes bibliographical references (p. 8-11).; Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/); Supported in part by NOAA Office of Global Programs (NA06GP0061). Supported in part by the UK Natural Environment Research Council...

Sistema de localización en redes Wi-Fi basado en Fingerprint

Núñez Sobrino, María Ángeles
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/bachelorThesis; info:eu-repo/semantics/masterThesis Formato: application/pdf
SPA
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36.07%
La gran difusión de los sistemas de localización outdoor, y en concreto GPS, que permiten obtener la localización geográfica en un mapa de un determinado dispositivo, han provocado el desarrollo de una demanda de funcionalidades similares a esta tecnología pero válida en el interior de edificios. En esta línea, el presente proyecto aprovecha la tecnología Wi-Fi para desarrollar un sistema de localización cuya funcionalidad sea ubicar a un dispositivo móvil conectado a una red basada en el estándar 802.11. La localización del dispositivo móvil se basa en determinar la posición del punto de acceso (AP) de la red que se encuentre más cerca de éste. Cada punto de acceso se encuentra registrado en una base de datos, en concreto, la información que identifica cada dispositivo, la potencia de la señal recibida (RSSI). Esta es la técnica conocida como Fingerprint, que consiste en la comparación de las señales recibidas en la posición actual que se quiere determinar con las mediciones de las señales recibidas obtenidas previamente de la zona cubierta por el sistema, durante la fase denominada off-line o de entrenamiento. La otra fase del proceso, la que se conoce como real-time, consiste en la localización propiamente dicha del dispositivo...

Constraining climate model properties using optimal fingerprint detection methods

Fonte: MIT Joint Program on the Science and Policy of Global Change Publicador: MIT Joint Program on the Science and Policy of Global Change
Formato: 46 p.; 2080013 bytes; application/pdf
ENG
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36.35%
We present a method for constraining key properties of the climate system that are important for climate prediction (climate sensitivity and rate of heat penetration into the deep ocean) by comparing a model's response to known forcings over the 20th century against climate observations for that period. We use the MIT 2D climate model in conjunction with results from the Hadley Centre's coupled atmosphere-ocean general circulation model (AOGCM) to determine these constraints. The MIT 2D model is a zonally-averaged version of a 3D GCM which can accurately reproduce the global-mean transient response of coupled AOGCMs through appropriate choices of the climate sensitivity and the effective rate of diffusion of heat into the deep ocean. Vertical patterns of zonal mean temperature change through the troposphere and lower stratosphere also compare favorably with those generated by 3-D GCMs. We compare the height-latitude pattern of temperature changes as simulated by the MIT 2D model with observed changes, using optimal fingerprint detection statistics. Interpreted in terms of a linear regression model as in Allen and Tett (1998), this approach yields an objective measure of model-observation goodness-of-fit (via the normalized residual sum of squares). The MIT model permits one to systematically vary the model's climate sensitivity (by varying the strength of the cloud feedback) and rate of mixing of heat into the deep ocean and determine how the goodness-of-fit with observations depends on these factors. This approach provides an efficient framework for interpreting detection and attribution results in physical terms. For the aerosol forcing set in the middle of the IPCC range...

Biometric Fingerprint System to Enable Rapid and Accurate Identification of Beneficiaries

Storisteanu, Daniel Matthew L; Norman, Toby L; Grigore, Alexandra; Norman, Tristram L
Fonte: Global Health: Science and Practice Publicador: Global Health: Science and Practice
Tipo: Artigo de Revista Científica
Publicado em 02/03/2015 EN
Relevância na Pesquisa
36.07%
Inability to uniquely identify clients impedes access to services and contributes to inefficiencies. Using a pocket-sized fingerprint scanner that wirelessly syncs with a health worker's smartphone, the SimPrints biometric system can link individuals' fingerprints to their health records. A pilot in Bangladesh will assess its potential.

SVM-Based Synthetic Fingerprint Discrimination Algorithm and Quantitative Optimization Strategy

Chen, Suhang; Chang, Sheng; Huang, Qijun; He, Jin; Wang, Hao; Huang, Qiangui
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 27/10/2014 EN
Relevância na Pesquisa
26.26%
Synthetic fingerprints are a potential threat to automatic fingerprint identification systems (AFISs). In this paper, we propose an algorithm to discriminate synthetic fingerprints from real ones. First, four typical characteristic factors—the ridge distance features, global gray features, frequency feature and Harris Corner feature—are extracted. Then, a support vector machine (SVM) is used to distinguish synthetic fingerprints from real fingerprints. The experiments demonstrate that this method can achieve a recognition accuracy rate of over 98% for two discrete synthetic fingerprint databases as well as a mixed database. Furthermore, a performance factor that can evaluate the SVM's accuracy and efficiency is presented, and a quantitative optimization strategy is established for the first time. After the optimization of our synthetic fingerprint discrimination task, the polynomial kernel with a training sample proportion of 5% is the optimized value when the minimum accuracy requirement is 95%. The radial basis function (RBF) kernel with a training sample proportion of 15% is a more suitable choice when the minimum accuracy requirement is 98%.

Beyond a warming fingerprint: individualistic biogeographic responses to heterogeneous climate change in California

Rapacciuolo, Giovanni; Maher, Sean P; Schneider, Adam C; Hammond, Talisin T; Jabis, Meredith D; Walsh, Rachel E; Iknayan, Kelly J; Walden, Genevieve K; Oldfather, Meagan F; Ackerly, David D; Beissinger, Steven R
Fonte: Blackwell Publishing Ltd Publicador: Blackwell Publishing Ltd
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
26.3%
Understanding recent biogeographic responses to climate change is fundamental for improving our predictions of likely future responses and guiding conservation planning at both local and global scales. Studies of observed biogeographic responses to 20th century climate change have principally examined effects related to ubiquitous increases in temperature – collectively termed a warming fingerprint. Although the importance of changes in other aspects of climate – particularly precipitation and water availability – is widely acknowledged from a theoretical standpoint and supported by paleontological evidence, we lack a practical understanding of how these changes interact with temperature to drive biogeographic responses. Further complicating matters, differences in life history and ecological attributes may lead species to respond differently to the same changes in climate. Here, we examine whether recent biogeographic patterns across California are consistent with a warming fingerprint. We describe how various components of climate have changed regionally in California during the 20th century and review empirical evidence of biogeographic responses to these changes, particularly elevational range shifts. Many responses to climate change do not appear to be consistent with a warming fingerprint...

Fingerprint Verification Using Local Interest Points and Descriptors

Devia, Christ; Loncomilla, Patricio; Ruiz del Solar, Javier
Fonte: Springer-Verlag Publicador: Springer-Verlag
Tipo: Artículo de revista
EN
Relevância na Pesquisa
36.19%
A new approach to automatic fingerprint verification based on a general- purpose wide baseline matching methodology is here proposed. The approach is not based on the standard ridge-minutiae-based framework. Instead of detecting and matching the standard structural features, local interest points are detected in the fingerprints, then local descriptors are computed in the neighborhood of these points, and afterwards these descriptors are compared using local and global matching procedures. Then, a final verification is carried out by a Bayes classifier. The methodology is validated using the FVC2004 dataset, where competitive results are obtained.; This research was funded by Millennium Nucleus Center for Web Research, Grant P04-067-F, Chile.

A New Approach for Fingerprint Verification Based on Wide Baseline Matching Using Local Interest Points and Descriptors

Devia, Christ; Loncomilla, Patricio; Ruiz del Solar, Javier
Fonte: Springer-Verlag Publicador: Springer-Verlag
Tipo: Artículo de revista
EN
Relevância na Pesquisa
36.34%
In this article is proposed a new approach to automatic fingerprint verification that is not based on the standard ridge-minutiae-based framework, but in a general-purpose wide baseline matching methodology. Instead of detecting and matching the standard structural features, in the proposed approach local interest points are detected in the fingerprint, then local descriptors are computed in the neighborhood of these points, and afterwards these descriptors are compared using local and global matching procedures. The final verification is carried out by a Bayes classifier. It is important to remark that the local interest points do not correspond to minutiae or singular points, but to local maxima in a scale-space representation of the fingerprint images. The proposed system has 4 variants that are validated using the FVC2004 test protocol. The best variant, which uses an enhanced fingerprint image, SDoG interest points and SIFT descriptors, achieves a FRR of 20.9% and a FAR of 5.7% in the FVC2004-DB1 test database, without using any minutia or singular points’ information.; This research was funded by Millenium Nucleus Center for Web Research, Grant P04-067-F, Chile.

Deep Representations for Iris, Face, and Fingerprint Spoofing Detection

Menotti, David; Chiachia, Giovani; Pinto, Allan; Schwartz, William Robson; Pedrini, Helio; Falcao, Alexandre Xavier; Rocha, Anderson
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.07%
Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or "spoofed") and, despite the recent advances in spoofing detection, current solutions often rely on domain knowledge, specific biometric reading systems, and attack types. We assume a very limited knowledge about biometric spoofing at the sensor to derive outstanding spoofing detection systems for iris, face, and fingerprint modalities based on two deep learning approaches. The first approach consists of learning suitable convolutional network architectures for each domain, while the second approach focuses on learning the weights of the network via back-propagation. We consider nine biometric spoofing benchmarks --- each one containing real and fake samples of a given biometric modality and attack type --- and learn deep representations for each benchmark by combining and contrasting the two learning approaches. This strategy not only provides better comprehension of how these approaches interplay, but also creates systems that exceed the best known results in eight out of the nine benchmarks. The results strongly indicate that spoofing detection systems based on convolutional networks can be robust to attacks already known and possibly adapted...

Doppler Peaks in the Angular Power Spectrum of the Cosmic Microwave Background: A Fingerprint of Topological Defects

Durrer, Ruth; Gangui, Alejandro; Sakellariadou, Mairi
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.02%
The Doppler peaks (Sacharov peaks) in the angular power spectrum of the cosmic microwave background anisotropies, are mainly due to coherent oscillations in the baryon radiation plasma before recombination. Here we present a calculation of the Doppler peaks for perturbations induced by global textures and cold dark matter. We find that the height of the first Doppler peak is smaller than in standard cold dark matter models, and that its position is shifted to $\ell\sim 350$. We believe that our analysis can be easily extended to other types of global topological defects and general global scalar fields.; Comment: 10pp, LaTeX, 2 PostScript figures included. Final version to appear in Phys. Rev. Letters

Fingerprint Verification based on Gabor Filter Enhancement

Lavanya, B N; Raja, K B; Venugopal, K R
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 04/12/2009
Relevância na Pesquisa
26.19%
Human fingerprints are reliable characteristics for personnel identification as it is unique and persistence. A fingerprint pattern consists of ridges, valleys and minutiae. In this paper we propose Fingerprint Verification based on Gabor Filter Enhancement (FVGFE) algorithm for minutiae feature extraction and post processing based on 9 pixel neighborhood. A global feature extraction and fingerprints enhancement are based on Hong enhancement method which is simultaneously able to extract local ridge orientation and ridge frequency. It is observed that the Sensitivity and Specificity values are better compared to the existing algorithms.; Comment: 7 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS November 2009, ISSN 1947 5500, http://sites.google.com/site/ijcsis/

Global Variational Method for Fingerprint Segmentation by Three-part Decomposition

Thai, Duy Hoang; Gottschlich, Carsten
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 18/05/2015
Relevância na Pesquisa
26.47%
Verifying an identity claim by fingerprint recognition is a commonplace experience for millions of people in their daily life, e.g. for unlocking a tablet computer or smartphone. The first processing step after fingerprint image acquisition is segmentation, i.e. dividing a fingerprint image into a foreground region which contains the relevant features for the comparison algorithm, and a background region. We propose a novel segmentation method by global three-part decomposition (G3PD). Based on global variational analysis, the G3PD method decomposes a fingerprint image into cartoon, texture and noise parts. After decomposition, the foreground region is obtained from the non-zero coefficients in the texture image using morphological processing. The segmentation performance of the G3PD method is compared to five state-of-the-art methods on a benchmark which comprises manually marked ground truth segmentation for 10560 images. Performance evaluations show that the G3PD method consistently outperforms existing methods in terms of segmentation accuracy.