Title :
A client-entropy measure for On-line Signatures
Author :
Salicetti, Sonia Garcia ; Houmani, Nesma ; Dorizzi, Bernadette
Author_Institution :
Dept. EPH, Inst. TELECOM, Evry
Abstract :
In this article, we propose an original way to characterize information content in online signatures through a client-entropy measure based on local density estimation by a hidden Markov model. We show that this measure can be used to categorize signatures in visually coherent classes that can be related to complexity and variability criteria. Besides, the generated categories are coherent across four different databases: BIOMET, MCYT-100, BioSecure data subsets DS2 and DS3. This measure allows a comparison of databases in terms of clientspsila signatures according to their information content.
Keywords :
computational complexity; entropy; handwriting recognition; hidden Markov models; client-entropy measure; complexity criteria; handwriting recognition; hidden Markov model; local density estimation; online signature; variability criteria; visually coherent class; Density measurement; Entropy; Handwriting recognition; Hidden Markov models; Humans; Personal digital assistants; Random variables; Spatial databases; Telecommunications; Visual databases; On-line signature; complexity; entropy; signature categorization; variability;
Conference_Titel :
Biometrics Symposium, 2008. BSYM '08
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2566-2
Electronic_ISBN :
978-1-4244-2567-9
DOI :
10.1109/BSYM.2008.4655527
