Oscar Miguel‐Hurtado

European Space Agency

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Richard Guest

University of Southampton

Ramón Blanco-Gonzalo

European Space Agency

Raúl Sánchez-Reillo

Universidad Carlos III de Madrid

Judith Liu‐Jimenez

Universidad Carlos III de Madrid

Sarah V. Stevenage

University of Southampton

Chiara Lunerti

Vicomtech

Luis Mengibar-Pozo

Universidad Carlos III de Madrid

Greg J. Neil

Southampton Solent University

Sue Black

Simon Fraser University

Aitor Mendaza-Ormaza

Universidad Carlos III de Madrid

Cooperative Institutions

Universidad Carlos III de Madrid

University of Kent

European Space Agency

University of Southampton

Universidad de Granada

Instituto Andaluz de Ciencias de la Tierra

Universitat Politècnica de Catalunya

Universidad Politécnica de Madrid

Cidete (Spain)

Kent State University

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A new approach to automatic signature complexity assessment

Oscar Miguel‐Hurtado Richard Guest Thomas Chatzisterkotis

Understanding signature complexity has been shown to be a crucial facet for both forensic and biometric appbcations. The signature complexity can be defined as the difficulty that forgers have when imitating the dynamics (constructional aspects) of other users signatures. Knowledge of complexity along with others facets such stability and signature length can lead to more robust and secure automatic signature verification systems. The work presented in this paper investigates the creation of a novel mathematical model for the automatic assessment of the signature complexity, analysing a wider set of dynamic signature features and also incorporating a new layer of detail, investigating the complexity of individual signature strokes. To demonstrate the effectiveness of the model this work will attempt to reproduce the signature complexity assessment made by experienced FDEs on a dataset of 150 signature samples.

Signature (topology)

Signature recognition

10.1109/ccst.2016.7815678

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Citations (4)

Analysis on the resolution of the different signals in an on-line handwritten signature verification system applied to portable devices

Aitor Mendaza-Ormaza Oscar Miguel‐Hurtado Raúl Sánchez-Reillo Jaime Uriarte-Antonio

Nowadays, the use of portable devices with touch screens has reached an extended use among the population. With this technology, it is possible to incorporate to such devices the possibility of using handwritten signature to authenticate the user. In order to study the possibilities to carry on this authentication, a previous analysis has been carried out in this paper to evaluate how an already implemented on-line signature authentication algorithm will work in portable devices. Signature database signals have been re-scaled to emulate signals taken from a portable device, emulating two technologies, capacitive and resistive screens. For this, using only 3 of the 5 standard signals captured by graphic tablets: X, Y and P. Support Vector Machines have been used as an algorithm to test against the modified database, and results show good performance of the algorithms, obtaining rates around EER=3%, showing that the algorithms will give good results implemented in real smart phones.

Signature (topology)

Line (geometry)

Handwriting Recognition

Resistive touchscreen

10.1109/ccst.2010.5678732

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Citations (6)

On-Line Signature Verification by Dynamic Time Warping and Gaussian Mixture Models

Oscar Miguel‐Hurtado Luis Mengibar-Pozo Michael G. Lorenz Judith Liu‐Jimenez

Handwriting signature is the most diffuse mean for personal identification. Lots of works have been carried out to get reasonable errors rates within automatic signature verification on-line. Most of the algorithms that have been used for matching work by features extraction. This paper deals with the analysis of discriminative powers of the features that can be extracted from an on-line signature, how it's possible to increase those discriminative powers by dynamic time warping as a step in the preprocessing of the signal coming from the tablet. Also it will be covered the influence of this new step in the performance of the Gaussian mixture models algorithm, which has been shown as a successfully algorithm for on-line automatic signature verification in recent studies. A complete experimental evaluation of the algorithm base on dynamic time warping and Gaussian Mixture Models has been conducted on 2500 genuine signatures samples and 2500 skilled forgery samples from 100 users. Those samples are included at the public access MCyT-Signature-Corpus Database.

Signature (topology)

Dynamic Time Warping

Discriminative model

Signature recognition

Handwriting

Image warping

Handwriting Recognition

Line (geometry)

10.1109/ccst.2007.4373463

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Citations (43)

Usability evaluation of biometrics in mobile environments

Ramón Blanco-Gonzalo Luis Diaz-Fernandez Oscar Miguel‐Hurtado Raúl Sánchez-Reillo

Actual trends in HCI tend to move systems to mobile environments. Moreover, biometrics is a technology that is entering maturity, getting involved in several security architectures nowadays. Thus, migrating biometrics to mobile scenarios is a trending topic in the research community. Nevertheless, in this kind of systems, usability has been put aside in the intent of produce better performance and it could involve undesirable results. In this work a behavioural biometric modality (handwritten signature recognition) is tested in mobile environments, in order to obtain a complete usability evaluation. Users signed in an iPad with different styluses in different scenarios, correlating performance results with several usability parameters (gathered through video, notes and forms) and obtaining interesting outcomes.

10.1109/hsi.2013.6577812

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Interaction evaluation of a mobile voice authentication system

Oscar Miguel‐Hurtado Ramón Blanco-Gonzalo Richard Guest Chiara Lunerti

Biometric recognition is nowadays widely used in smartphones, making the users' authentication easier and more transparent than PIN codes or patterns. Starting from this idea, the EU project PIDaaS aims to create a secure authentication system through mobile devices based on voice and face recognition as two of the most reliable and user-accepted modalities. This work introduces the project and the first PIDaaS usability evaluation carried out by means of the well-known HBSI model In this experiment, participants interact with a mobile device using the PIDaaS system under laboratory conditions: video recorded and assisted by an operator. Our findings suggest variability among sessions in terms of usability and feed the next PIDaaS HCI design.

Modalities

10.1109/ccst.2016.7815697

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Citations (14)

Embedded System for Biometric Online Signature Verification

IEEE Transactions on Industrial Informatics (2013)

Mariano López-García Rafael Ramón Ramos Lara Oscar Miguel‐Hurtado Enrique Cantó

This paper describes the implementation on field-programmable gate arrays (FPGAs) of an embedded system for online signature verification. The recognition algorithm mainly consists of three stages. First, an initial preprocessing is applied on the captured signature, removing noise and normalizing information related to horizontal and vertical positions. Afterwards, a dynamic time warping algorithm is used to align this processed signature with its template previously stored in a database. Finally, a set of features are extracted and passed through a Gaussian Mixture Model, which reveals the degree of similarity between both signatures. The algorithm was tested using a public database of 100 users, obtaining high recognition rates for both genuine and forgery signatures. The implemented system consists of a vector floating-point unit (VFPU), specifically designed for accelerating the floating-point computations involved in this biometric modality. Moreover, the proposed architecture also includes a microprocessor, which interacts with the VFPU, and executes by software the rest of the online signature verification process. The designed system is capable of finishing a complete verification in less than 68 ms with a clock rated at 40 MHz. Experimental results show that the number of clock cycles is accelerated by a factor of ×4.8 and ×11.1, when compared with systems based on ARM Cortex-A8 and when substituting the VFPU by the Floating-Point Unit provided by Xilinx, respectively.

Signature (topology)

Coprocessor

Signature recognition

Clock rate

10.1109/tii.2013.2269031

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Citations (54)

Predicting sex as a soft-biometrics from device interaction swipe gestures

Pattern Recognition Letters (2016)

Oscar Miguel‐Hurtado Sarah V. Stevenage Chris Bevan Richard Guest

Touch and multi-touch gestures are becoming the most common way to interact with technology such as smart phones, tablets and other mobile devices. The latest touch-screen input capacities have tremendously increased the quantity and quality of available gesture data, which has led to the exploration of its use in multiple disciplines from psychology to biometrics. Following research studies undertaken in similar modalities such as keystroke and mouse usage biometrics, the present work proposes the use of swipe gesture data for the prediction of soft-biometrics, specifically the user's sex. This paper details the software and protocol used for the data collection, the feature set extracted and subsequent machine learning analysis. Within this analysis, the BestFirst feature selection technique and classification algorithms (naïve Bayes, logistic regression, support vector machine and decision tree) have been tested. The results of this exploratory analysis have confirmed the possibility of sex prediction from the swipe gesture data, obtaining an encouraging 78% accuracy rate using swipe gesture data from two different directions. These results will hopefully encourage further research in this area, where the prediction of soft-biometrics traits from swipe gesture data can play an important role in enhancing the authentication processes based on touch-screen devices.

SwIPe

Keystroke logging

Feature (linguistics)

10.1016/j.patrec.2016.04.024

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Citations (40)

Hardware/Software Codesign for an Iris Biometric Search Engine

Judith Liu‐Jimenez Oscar Miguel‐Hurtado Almudena Lindoso Belen Fernandez‐Saavedra

Many airports are employing Biometric Technology to check the user identity nowadays. Till nowadays, the use of Biometric in this situation is restricted to verification, i.e., the user at the same time he/she provides his/her Biometric data, provides also his/her identity. However, in some cases, it is needed to search among all users stored in the database for the identity of the user. For this purpose, search engines are used. In this paper, authors propose an architecture for a Biometric search engine. The architecture proposal performs part of the algorithm using dedicated hardware and dataflow control is done by a microprocessor, obtaining with this configuration high speed and reliability.

Iris Recognition

10.1109/eurcon.2007.4400454

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Citations (4)

Analysis of handwritten signature performances using mobile devices

Aitor Mendaza-Ormaza Oscar Miguel‐Hurtado Ramón Blanco-Gonzalo Francisco-Jose Diez-Jimeno

This paper continue our previous work on on-line signature verification on portable devices. A database has been collected which contains data for 25 users, with 28 genuine and 25 skilled forged signatures per user, in 5 different devices. 4 portable devices of different sizes and screen technologies (capacitive and resistive) have been used. The 5 ^th device is a traditional digital pen tablet, to use as a baseline for results comparison. Two different algorithms, DTW and SVM, have been used to asses the performance of the signals captured on portable devices. Two main experiments using both algorithms and the 5 sub-databases have been done. The first experiment uses each database independently. The user model is created and tested with signatures of the same database. The second experiment creates the user model using signatures acquired with the digital pen tablet. Results of the first experiment achieve good error rates for random forgeries.

Signature (topology)

Handwriting Recognition

Resistive touchscreen

10.1109/ccst.2011.6095930

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Citations (15)

User-Interaction Evaluation of a Mobile Authentication System

Richard Guest Oscar Miguel‐Hurtado

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