Analyse de la qualité des signatures manuscrites en-ligne par la mesure d'entropie

Cette thèse s'inscrit dans le contexte de la vérification d'identité par la signature manuscrite en-ligne. Notre travail concerne plus particulièrement la recherche de nouvelles mesures qui permettent de quantifier la qualité des signatures en-ligne et d'établir des critères automatiques de fiabilité des systèmes de vérification. Nous avons proposé trois mesures de qualité faisant intervenir le concept d entropie. Nous avons proposé une mesure de qualité au niveau de chaque personne, appelée Entropie personnelle , calculée sur un ensemble de signatures authentiques d une personne. L originalité de l approche réside dans le fait que l entropie de la signature est calculée en estimant les densités de probabilité localement, sur des portions, par le biais d un Modèle de Markov Caché. Nous montrons que notre mesure englobe les critères habituels utilisés dans la littérature pour quantifier la qualité d une signature, à savoir: la complexité, la variabilité et la lisibilité. Aussi, cette mesure permet de générer, par classification non supervisée, des catégories de personnes, à la fois en termes de variabilité de la signature et de complexité du tracé. En confrontant cette mesure aux performances de systèmes de vérification usuels sur chaque catégorie de personnes, nous avons trouvé que les performances se dégradent de manière significative (d un facteur 2 au minimum) entre les personnes de la catégorie haute Entropie (signatures très variables et peu complexes) et celles de la catégorie basse Entropie (signatures les plus stables et les plus complexes). Nous avons ensuite proposé une mesure de qualité basée sur l entropie relative (distance de Kullback-Leibler), dénommée Entropie Relative Personnelle permettant de quantifier la vulnérabilité d une personne aux attaques (bonnes imitations). Il s agit là d un concept original, très peu étudié dans la littérature. La vulnérabilité associée à chaque personne est calculée comme étant la distance de Kullback-Leibler entre les distributions de probabilité locales estimées sur les signatures authentiques de la personne et celles estimées sur les imitations qui lui sont associées. Nous utilisons pour cela deux Modèles de Markov Cachés, l'un est appris sur les signatures authentiques de la personne et l'autre sur les imitations associées à cette personne. Plus la distance de Kullback-Leibler est faible, plus la personne est considérée comme vulnérable aux attaques. Cette mesure est plus appropriée à l analyse des systèmes biométriques car elle englobe en plus des trois critères habituels de la littérature, la vulnérabilité aux imitations. Enfin, nous avons proposé une mesure de qualité pour les signatures imitées, ce qui est totalement nouveau dans la littérature. Cette mesure de qualité est une extension de l Entropie Personnelle adaptée au contexte des imitations: nous avons exploité l information statistique de la personne cible pour mesurer combien la signature imitée réalisée par un imposteur va coller à la fonction de densité de probabilité associée à la personne cible. Nous avons ainsi défini la mesure de qualité des imitations comme étant la dissimilarité existant entre l'entropie associée à la personne à imiter et celle associée à l'imitation. Elle permet lors de l évaluation des systèmes de vérification de quantifier la qualité des imitations, et ainsi d apporter une information vis-à-vis de la résistance des systèmes aux attaques. Nous avons aussi montré l intérêt de notre mesure d Entropie Personnelle pour améliorer les performances des systèmes de vérification dans des applications réelles. Nous avons montré que la mesure d Entropie peut être utilisée pour : améliorer la procédure d enregistrement, quantifier la dégradation de la qualité des signatures due au changement de plateforme, sélectionner les meilleures signatures de référence, identifier les signatures aberrantes, et quantifier la pertinence de certains paramètres pour diminuer la variabilité temporelle.This thesis is focused on the quality assessment of online signatures and its application to online signature verification systems. Our work aims at introducing new quality measures quantifying the quality of online signatures and thus establishing automatic reliability criteria for verification systems. We proposed three quality measures involving the concept of entropy, widely used in Information Theory. We proposed a novel quality measure per person, called "Personal Entropy" calculated on a set of genuine signatures of such a person. The originality of the approach lies in the fact that the entropy of the genuine signature is computed locally, on portions of such a signature, based on local density estimation by a Hidden Markov Model. We show that our new measure includes the usual criteria of the literature, namely: signature complexity, signature variability and signature legibility. Moreover, this measure allows generating, by an unsupervised classification, 3 coherent writer categories in terms of signature variability and complexity. Confronting this measure to the performance of two widely used verification systems (HMM, DTW) on each Entropy-based category, we show that the performance degrade significantly (by a factor 2 at least) between persons of "high Entropy-based category", containing the most variable and the least complex signatures and those of "low Entropy-based category", containing the most stable and the most complex signatures. We then proposed a novel quality measure based on the concept of relative entropy (also called Kullback-Leibler distance), denoted Personal Relative Entropy for quantifying person's vulnerability to attacks (good forgeries). This is an original concept and few studies in the literature are dedicated to this issue. This new measure computes, for a given writer, the Kullback-Leibler distance between the local probability distributions of his/her genuine signatures and those of his/her skilled forgeries: the higher the distance, the better the writer is protected from attacks. We show that such a measure simultaneously incorporates in a single quantity the usual criteria proposed in the literature for writer categorization, namely signature complexity, signature variability, as our Personal Entropy, but also the vulnerability criterion to skilled forgeries. This measure is more appropriate to biometric systems, because it makes a good compromise between the resulting improvement of the FAR and the corresponding degradation of FRR. We also proposed a novel quality measure aiming at quantifying the quality of skilled forgeries, which is totally new in the literature. Such a measure is based on the extension of our former Personal Entropy measure to the framework of skilled forgeries: we exploit the statistical information of the target writer for measuring to what extent an impostor s hand-draw sticks to the target probability density function. In this framework, the quality of a skilled forgery is quantified as the dissimilarity existing between the target writer s own Personal Entropy and the entropy of the skilled forgery sample. Our experiments show that this measure allows an assessment of the quality of skilled forgeries of the main online signature databases available to the scientific community, and thus provides information about systems resistance to attacks. Finally, we also demonstrated the interest of using our Personal Entropy measure for improving performance of online signature verification systems in real applications. We show that Personal Entropy measure can be used to: improve the enrolment process, quantify the quality degradation of signatures due to the change of platforms, select the best reference signatures, identify the outlier signatures, and quantify the relevance of times functions parameters in the context of temporal variability.EVRY-INT (912282302) / SudocSudocFranceF

Entwicklungsanalyse für das Medium Print am Beispiel der BILD-Zeitung

nicht vorhandenIn recent years the degree of sophistication regarding news outlets’ distribution channels has grown exponentially, due to the advancement of current technologies. This bachelor thesis takes aim at these alterations in the media landscape, in order to analyze the economic and social impact on the print newspaper market. As a subject of my analysis I will utilize the Bild Zeitung and will attempt to highlight the evolution at the core of that segment. Subse-quently I will dissect future consumption potential of non digital media alongside its digital substitutional goods

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008Comment: Published at IEEE Transactions on Pattern Analysis and Machine Intelligence journa

The Multiscenario Multienvironment BioSecure Multimodal Database (BMDB)

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1 over the Internet, 2 in an office environment with desktop PC, and 3 in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008

Yager & Dunstone’s representation of the Biometric Menagerie [12,13].

<p>Yager & Dunstone’s representation of the Biometric Menagerie [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151691#pone.0151691.ref012" target="_blank">12</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151691#pone.0151691.ref013" target="_blank">13</a>].</p

Doddington’s representation of the Biometric Menagerie [11].

<p>Doddington’s representation of the Biometric Menagerie [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0151691#pone.0151691.ref011" target="_blank">11</a>].</p

A new protocol for multi-biometric systems' evaluation maintaining the dependencies between biometric scores

International audienceWe address the problem of measuring the dependency of multibiometric systems' scores, using Kolmogorov-Smirnov and Mutual Information criteria, and studying the validity of performance evaluation on chimeric persons. On the NIST-BSSR1 database, we formalize a common assumption in the literature: for independent scores, multibiometric systems can be evaluated on "random chimeric" persons. We show that this is not valid for dependent scores and propose a novel protocol for building "cluster-based chimeric" persons maintaining the level of dependency between scores. Finally, we show that performance evaluation for dependent modalities on such persons is equivalent to that obtained on "real" persons

On Hunting Animals of the Biometric Menagerie for Online Signature

<div><p>Individuals behave differently regarding to biometric authentication systems. This fact was formalized in the literature by the concept of Biometric Menagerie, defining and labeling user groups with animal names in order to reflect their characteristics with respect to biometric systems. This concept was illustrated for face, fingerprint, iris, and speech modalities. The present study extends the Biometric Menagerie to online signatures, by proposing a novel methodology that ties specific quality measures for signatures to categories of the Biometric Menagerie. Such measures are combined for retrieving <i>automatically</i> writer categories of the extended version of the Biometric Menagerie. Performance analysis with different types of classifiers shows the pertinence of our approach on the well-known MCYT-100 database.</p></div

Enhancing Security on Touch-Screen Sensors with Augmented Handwritten Signatures

We aim at enhancing personal identity security on mobile touch-screen sensors by augmenting handwritten signatures with specific additional information at the enrollment phase. Our former works on several available and private data sets acquired on different sensors demonstrated that there are different categories of signatures that emerge automatically with clustering techniques, based on an entropy-based data quality measure. The behavior of such categories is totally different when confronted to automatic verification systems in terms of vulnerability to attacks. In this paper, we propose a novel and original strategy to reinforce identity security by enhancing signature resistance to attacks, assessed per signature category, both in terms of data quality and verification performance. This strategy operates upstream from the verification system, at the sensor level, by enriching the information content of signatures with personal handwritten inputs of different types. We study this strategy on different signature types of 74 users, acquired in uncontrolled mobile conditions on a largely deployed mobile touch-screen sensor. Our analysis per writer category revealed that adding alphanumeric (date) and handwriting (place) information to the usual signature is the most powerful augmented signature type in terms of verification performance. The relative improvement for all user categories is of at least 93% compared to the usual signature

Ensuring public order in a municipality

<p>Performance on “Worms”, “Doves” and “Chameleons”, with the global classifier.</p