Impact of time variability in off-line writer identification and verification

Abstract

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. F. Alonso-Fernández, J. Fiérrez, A. Gilpérez, J Ortega-García, "Impact of time variability in off-line writer identification and verification" in 6th International Symposium on Image and Signal Processing and Analysis (ISPA), Salzburg (Austria), 2009, pp. 540 - 545One of the biggest challenges in person recognition using biometric systems is the variability in the acquired data. In this paper, we evaluate the effects of an increasing time lapse between reference and test biometric data consisting of static images of handwritten signatures and texts. We use for our experiments two recognition approaches exploiting information at the global and local levels, and the BiosecurlD database, containing 3,724 signature images and 532 texts of 133 individuals acquired in four acquisition sessions distributed along a 4 months time span. We report results of the recognition systems working both in verification (one-to-one) and identification (one-to-many) mode. The results show the extent of the impact that the time separation between samples under comparison has on the recognition rates, being the local approach more robust to the time lapse than the global one. We also observe in our experiments that recognition based on handwritten texts provides higher accuracy than recognition based on signatures.This work has been supported by Spanish MCYT TEC2006-13141-C03-03 project