On-line signature recognition through the combination of real dynamic data and synthetically generated static data

This is the author’s version of a work that was accepted for publication in Pattern Recognition . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition , 48, 9 (2005) DOI: 10.1016/j.patcog.2015.03.019On-line signature verification still remains a challenging task within biometrics. Due to their behavioral nature (opposed to anatomic biometric traits), signatures present a notable variability even between successive realizations. This leads to higher error rates than other largely used modalities such as iris or fingerprints and is one of the main reasons for the relatively slow deployment of this technology. As a step towards the improvement of signature recognition accuracy, the present paper explores and evaluates a novel approach that takes advantage of the performance boost that can be reached through the fusion of on-line and off-line signatures. In order to exploit the complementarity of the two modalities, we propose a method for the generation of enhanced synthetic static samples from on-line data. Such synthetic off-line signatures are used on a new on-line signature recognition architecture based on the combination of both types of data: real on-line samples and artificial off-line signatures synthesized from the real data. The new on-line recognition approach is evaluated on a public benchmark containing both real versions (on-line and off-line) of the exact same signatures. Different findings and conclusions are drawn regarding the discriminative power of on-line and off-line signatures and of their potential combination both in the random and skilled impostors scenarios.M. D.-C. is supported by a PhD fellowship from the ULPGC and M.G.-B. is supported by a FPU fellowship from the Spanish MECD. This work has been partially supported by projects: MCINN TEC2012-38630- C04-02, Bio-Shield (TEC2012-34881) from Spanish MINECO, BEAT (FP7-SEC-284989) from EU, CECABANK and Cátedra UAM-Telefónic

Fuzzy Vault scheme based on fixed-length templates applied to dynamic signature verification

As a consequence of the wide deployment of biometrics-based recognition systems, there are increasing concerns about the security of the sensitive information managed. Various techniques have been proposed in the literature for the biometric templates protection (BTP), having gained great popularity the crypto-biometric systems. In the present paper we propose the implementation of a Fuzzy Vault (FV) scheme based on fixed-length templates with application to dynamic signature verification (DSV), where only 15 global features of the signature are considered to form the templates. The performance of the proposed system is evaluated using three databases: a proprietary collection of signatures, and the publicly available databases MCYT and BioSecure. The experimental results show very similar verification performance compared to an equivalent unprotected system.This work was supported by the Spanish National Cybersecurity Institute (INCIBE) through the Excellence of Advanced Cybersecurity Research Teams Program

Enhancing Face Recognition with Deep Learning Architectures: A Comprehensive Review

The progression of information discernment via facial identification and the emergence of innovative frameworks has exhibited remarkable strides in recent years. This phenomenon has been particularly pronounced within the realm of verifying individual credentials, a practice prominently harnessed by law enforcement agencies to advance the field of forensic science. A multitude of scholarly endeavors have been dedicated to the application of deep learning techniques within machine learning models. These endeavors aim to facilitate the extraction of distinctive features and subsequent classification, thereby elevating the precision of unique individual recognition. In the context of this scholarly inquiry, the focal point resides in the exploration of deep learning methodologies tailored for the realm of facial recognition and its subsequent matching processes. This exploration centers on the augmentation of accuracy through the meticulous process of training models with expansive datasets. Within the confines of this research paper, a comprehensive survey is conducted, encompassing an array of diverse strategies utilized in facial recognition. This survey, in turn, delves into the intricacies and challenges that underlie the intricate field of facial recognition within imagery analysis

A study of the effects of ageing on the characteristics of handwriting and signatures

The work presented in this thesis is focused on the understanding of factors that are unique to the elderly and their use of biometric systems. In particular, an investigation is carried out with a focus on the handwritten signature as the biometric modality of choice. This followed on from an in-depth analysis of various biometric modalities such as voice, fingerprint and face. This analysis aimed at investigating the inclusivity of and the policy guiding the use of biometrics by the elderly. Knowledge gained from extracted features of the handwritten signatures of the elderly shed more light on and exposed the uniqueness of some of these features in their ability to separate the elderly from the young. Consideration is also given to a comparative analysis of another handwriting task, that of copying text both in cursive and block capitals. It was discovered that there are features that are unique to each task. Insight into the human perceptual capability in inspecting signatures, in assessing complexity and in judging imitations was gained by analysing responses to practical scenarios that applied human perceptual judgement. Features extracted from a newly created database containing handwritten signatures donated by elderly subjects allowed the possibility of analysing the intra-class variations that exist within the elderly population

Recent developments in the study of rapid human movements with the kinematic theory: Applications to handwriting and signature synthesis

International audienceHuman movement modeling can be of great interest for the design of pattern recognition systems relying on the understanding of the fine motor control (such as on-line handwriting recognition or signature verification) as well as for the development of intelligent systems involving in a way or another the processing of human movements. In this paper, we briefly list the different models that have been proposed in order to characterize the handwriting process and focus on a representation involving a vectorial summation of lognormal functions: the Sigma-lognormal model. Then, from a practical perspective, we describe a new stroke extraction algorithm suitable for the reverse engineering of handwriting signals. In the following section it is shown how the resulting representation can be used to study the writer and signer variability. We then report on two joint projects dealing with the automatic generation of synthetic specimens for the creation of large databases. The first application concerns the automatic generation of totally synthetic signature specimens for the training and evaluation of verification performances of automatic signature recognition systems. The second application deals with the synthesis of handwritten gestures for speeding up the learning process in customizable on-line recognition systems to be integrated in electronic pen pads

Usability in biometric recognition systems

Mención Internacional en el título de doctorBiometric recognition, which is a technology already mature, grows nowadays in several contexts, including forensics, access controls, home automation systems, internet, etc. Now that technology is moving to mobile scenarios, biometric recognition is being also integrated in smartphones, tablets and other mobile devices as a convenient solution for guaranteeing security, complementing other methods such as PIN or passwords. Nevertheless, the use of biometric recognition is not as spread as desired and it is still unknown for a wide percentage of the population. It has been demonstrated [1] that some of the possible reasons for the slow penetration of biometrics could be related to usability concerns. This could lead to various drawbacks like worst error rates due to systems misuses and it could end with users rejecting the technology and preferring other approaches. This Thesis is intended to cover this topic including a study of the current state of the art, several experiments analysing the most relevant usability factors and modifications to a usability evaluation methodology. The chosen methodology is the H-B interaction, carried out by Fernandez-Saavedra [2], based on the ISO/IEC 19795 [3], the HBSI [4], the ISO 9241-210 [5] and on Common Criteria [6]. Furthermore, this work is focused on dealing with accessibility concerns in biometric recognition systems. This topic, usually included into the usability field, has been addressed here separately, though the study of the accessibility has followed the same steps as the usability study: reviewing the state of the art, pointing and analysing the main influential factors and making improvements to the state of the art. The recently published standard EN 301 549 – “Accessibility requirements suitable for public procurement of ICT products and services in Europe” [7] has been also analysed. These two topics have been overcome through the well-known user-centric-design approach. In this way, first the influential factors have been detected. Then, they have been isolated (when possible) and measured. The results obtained have been then interpreted to suggest new updates to the H-B interaction. This 3-steps approach has been applied cyclically and the factors and methodology updated after each iteration. Due to technology and usability trends, during this work, all the systems/applications developed in the experiments have been thought to be mobile directly or indirectly. The biometric modalities used during the experiments performed in this Thesis are those pointed as suitable for biometric recognition in mobile devices: handwritten recognition signature, face and fingerprint recognition. Also, the scenarios and the applications used are in line with the main uses of biometrics in mobile environments, such as sign documents, locking/unlocking devices, or make payments. The outcomes of this Thesis are intended to guide future developers in the way of designing and testing proper usable and accessible biometrics. Finally, the results of this Thesis are being suggested as a new International Standard within ISO/IEC/JTC1/SC37 – Biometric Recognition, as standardization is the proper way of guaranteeing usability and accessibility in future biometric systems. The contributions of this Thesis include: • Improvements to the H-B interaction methodology, including several usability evaluations. • Improvements on the accessibility of the ICT (Information and Communications Technology) products by means of the integration of biometric recognition systems • Adaptation and application of the EN 301 549 to biometric recognition systems.El reconocimiento biométrico, que es una tecnología ya madura, crece hoy en día en varios contextos, incluyendo la medicina forense, controles de acceso, sistemas de automatización del hogar, internet, etc. Ahora que la tecnología se está moviendo a los escenarios móviles, el reconocimiento biométrico está siendo también integrado en los teléfonos inteligentes, tabletas y otros dispositivos móviles como una solución conveniente para garantizar la seguridad, como complemento de otros métodos de seguridad como el PIN o las contraseñas. Sin embargo, el uso del reconocimiento biométrico es todavía desconocido para un amplio porcentaje de la población. Se ha demostrado [1] que algunas de las posibles razones de la lenta penetración de la biometría podrían estar relacionadas con problemas de usabilidad. Esto podría dar lugar a diversos inconvenientes, ofreciendo un rendimiento por debajo de lo esperado debido al mal uso de los sistemas y podría terminar con los usuarios rechazando la tecnología y prefiriendo otros enfoques. Esta tesis doctoral trata este tema incluyendo un estudio del estado actual de la técnica, varios experimentos que analizan los factores de usabilidad más relevantes y modificaciones a una metodología de evaluación de la usabilidad, la "H-B interaction" [2] basada en la ISO / IEC 19795 [3], el HBSI [4], la ISO 9241 [5] y Common Criteria [6]. Además, este trabajo se centra también en los problemas de accesibilidad de los sistemas de reconocimiento biométrico. Este tema, que por lo general se incluye en el campo de la usabilidad, se ha tratado aquí por separado, aunque el estudio de la accesibilidad ha seguido los mismos pasos que el estudio de usabilidad: revisión del estado del arte, análisis de los principales factores influyentes y propuesta de cambios en la metodología H-B interaction. Han sido también analizados los requisitos de accesibilidad para las Tecnologías de la Información y la Comunicación (TIC) en Europa, bajo la norma EN 301 549 [7]. Estos dos temas han sido estudiados a través de un enfoque centrado en el usuario (User Centric Design - UCD). De esta manera, se han detectado los factores influyentes. A continuación, dichos factores han sido aislados (cuando ha sido posible) y medidos. Los resultados obtenidos han sido interpretados para sugerir nuevos cambios a la metodología H-B interaction. Este enfoque de 3 pasos se ha aplicado de forma cíclica a los factores y a la metodología después de cada iteración. Debido a las tendencias tecnológicas y de usabilidad, durante este trabajo, todos los sistemas / aplicaciones desarrolladas en los experimentos se han pensado para ser móviles, directa o indirectamente. Las modalidades utilizadas durante los experimentos realizados en esta tesis doctoral son las que se señalaron como adecuados para el reconocimiento biométrico en dispositivos móviles: la firma manuscrita, la cara y el reconocimiento de huellas dactilares. Además, los escenarios y las aplicaciones utilizadas están en línea con los principales usos de la biometría en entornos móviles, como la firma de documentos, el bloqueo / desbloqueo de dispositivos, o hacer pagos. Los resultados de esta tesis tienen como objetivo orientar a los futuros desarrolladores en el diseño y evaluación de la usabilidad y la accesibilidad en los sistemas de reconocimiento biométrico. Por último, los resultados de esta tesis doctoral se sugerirán como un nuevo estándar de ISO / IEC / JTC1 / SC37 - Biometric Recognition, ya que la normalización es la manera adecuada de garantizar la usabilidad y la accesibilidad en los futuros sistemas biométricos. Las contribuciones de esta tesis incluyen: • Mejora de la metodología de evaluación H-B interaction, incluyendo varias evaluaciones de usabilidad. • Mejora de la accesibilidad de los sistemas de información / electrónicos mediante la integración de sistemas biométricos y varias evaluaciones. • Adaptación y aplicación de la norma de accesibilidad EN 301 549 al campo de los sistemas biométricos.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Patrizio Campisi.- Secretario: Enrique Cabellos Pardo.- Vocal: Marcos Faundez Zanu

Revisiting Actor Programming in C++

The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model. In this paper, we report on designing and building CAF, the "C++ Actor Framework". CAF targets at providing a concurrent and distributed native environment for scaling up to very large, high-performance applications, and equally well down to small constrained systems. We present the key specifications and design concepts---in particular a message-transparent architecture, type-safe message interfaces, and pattern matching facilities---that make native actors a viable approach for many robust, elastic, and highly distributed developments. We demonstrate the feasibility of CAF in three scenarios: first for elastic, upscaling environments, second for including heterogeneous hardware like GPGPUs, and third for distributed runtime systems. Extensive performance evaluations indicate ideal runtime behaviour for up to 64 cores at very low memory footprint, or in the presence of GPUs. In these tests, CAF continuously outperforms the competing actor environments Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.Comment: 33 page