Title :
Dynamic signatures representation using the minimum jerk principle
Author :
Canuto, J. ; Dorizzi, Bernadette ; Montalvao, J.
Author_Institution :
Electron. & Phys. Dept. (EPH), Telecom SudParis, Evry, France
Abstract :
In this paper, we propose to use the minimum jerk principle for representing on-line signatures. We briefly describe the minimum jerk model and the automatic procedure we propose for its implementation with signatures. Results on the MCYT-100 signature database are analysed regarding reconstruction error, residual analysis and stability. These results show that, despite its simplicity, the proposed model agrees with previous works on signature modelling and entropy-based signature categorization. Finally, possible applications and future works are suggested.
Keywords :
bioelectric phenomena; entropy; handwriting recognition; information services; iterative methods; medical signal processing; minimax techniques; neurophysiology; physiological models; signal denoising; signal reconstruction; MCYT-100 signature database; automatic procedure; dynamic signatures representation; entropy-based signature categorization; minimum jerk model; minimum jerk principle; online signature representation; reconstruction error; residual analysis; residual stability; signal to noise ratio; signature modelling; Databases; Entropy; Hidden Markov models; Polynomials; Signal to noise ratio; Standards; Trajectory;
Conference_Titel :
Biosignals and Biorobotics Conference (BRC), 2013 ISSNIP
Conference_Location :
Rio de Janerio
Print_ISBN :
978-1-4673-3024-4
DOI :
10.1109/BRC.2013.6487464