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Modeling the Complexity of Signature and Touch-Screen Biometrics using the Lognormality Principle

2020; World Scientific; Linguagem: Inglês

10.1142/9789811226830_0003

1793-0839

Rubén Vera-Rodríguez, Rubén Tolosana, Javier Hernandez‐Ortega, Alejandro Acien, Aythami Morales, Julián Fiérrez, Javier Ortega-García,

Cognitive Computing and Networks

Series in Machine Perception and Artificial IntelligenceThe Lognormality Principle and its Applications in e-Security, e-Learning and e-Health, pp. 65-86 (2020) No AccessChapter 3: Modeling the Complexity of Signature and Touch-Screen Biometrics using the Lognormality PrincipleRuben Vera-Rodriguez, Ruben Tolosana, Javier Hernandez-Ortega, Alejandro Acien, Aythami Morales, Julian Fierrez, and Javier Ortega-GarciaRuben Vera-RodriguezBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spain, Ruben TolosanaBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spain, Javier Hernandez-OrtegaBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spain, Alejandro AcienBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spain, Aythami MoralesBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spain, Julian FierrezBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spain, and Javier Ortega-GarciaBiDA Lab, School of Engineering, Universidad Autonoma de Madrid, Madrid, Spainhttps://doi.org/10.1142/9789811226830_0003Cited by:2 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail Abstract: This paper focuses on modeling the complexity of biomechanical tasks through the usage of the Sigma-LogNormal model of the Kinematic Theory of rapid human movements. The Sigma-LogNormal model has been used for several applications, in particular related to modeling and generating synthetic handwritten signatures in order to improve the performance of automatic verification systems. In this paper we report experimental work for the usage of the Sigma-LogNormal model to predict the complexity of biomechanical tasks on two case studies: 1) on-line signature recognition in order to generate user-based complexity groups and develop specific verification systems for each of them, and 2) detection of age groups (children from adults) using touch screen patterns. The results achieved show the benefits of using the Sigma-LogNormal model for modeling the complexity of biomechanical tasks in the two case studies considered. FiguresReferencesRelatedDetailsCited By 2Introduction to Presentation Attacks in Signature Biometrics and Recent AdvancesCarlos Gonzalez-Garcia, Ruben Tolosana, Ruben Vera-Rodriguez, Julian Fierrez and Javier Ortega-Garcia24 February 2023Child-Computer Interaction With Mobile Devices: Recent Works, New Dataset, and Age DetectionRuben Tolosana, Juan Carlos Ruiz-Garcia, Ruben Vera-Rodriguez, Jaime Herreros-Rodriguez and Sergio Romero-Tapiador et al.1 Oct 2022 | IEEE Transactions on Emerging Topics in Computing, Vol. 10, No. 4 The Lognormality Principle and its Applications in e-Security, e-Learning and e-HealthMetrics History PDF download