title: Unconstrained and contactless hand geometry biometrics.
abstract: This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.
authors.affiliation: Group of Biometrics, Biosignals and Security, Universidad Politécnica de Madrid, Campus de Montegancedo s/n, 28223 Pozuelo de Alarcón, Madrid, Spain. alberto@cedint.upm.es
authors.forename: Alberto
authors.initials: A
authors.lastname: de-Santos-Sierra
authors.forename: Carmen
authors.initials: C
authors.lastname: Sánchez-Ávila
authors.forename: Gonzalo Bailador
authors.initials: GB
authors.lastname: Del Pozo
authors.forename: Javier
authors.initials: J
authors.lastname: Guerra-Casanova
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D056667:Biometric Identification / Q000379:methods*; D016208:Databases, Factual; D003661:Decision Support Techniques; D006225:Hand / Q000033:anatomy & histology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine