DocumentCode :
741951
Title :
Preprocessing and Feature Selection for Improved Sensor Interoperability in Online Biometric Signature Verification
Author :
Tolosana, Ruben ; Vera-Rodriguez, Ruben ; Ortega-Garcia, Javier ; Fierrez, Julian
Author_Institution :
ATVS-Biometric Recognition Group, Univ. Autonoma de Madrid, Madrid, Spain
Volume :
3
fYear :
2015
fDate :
7/7/1905 12:00:00 AM
Firstpage :
478
Lastpage :
489
Abstract :
Due to the technological evolution and the increasing popularity of smartphones, people can access an application using authentication based on biometric approaches from many different devices. Device interoperability is a very challenging problem for biometrics, which needs to be further studied. In this paper, we focus on interoperability device compensation for online signature verification since this biometric trait is gaining a significant interest in banking and commercial sector in the last years. The proposed approach is based on two main stages. The first one is a preprocessing stage where data acquired from different devices are processed in order to normalize the signals in similar ranges. The second one is based on feature selection taking into account the device interoperability case, in order to select to select features which are robust in these conditions. This proposed approach has been successfully applied in a similar way to two common system approaches in online signature verification, i.e., a global features-based system and a time functions-based system. Experiments are carried out using Biosecure DS2 (Wacom device) and DS3 (Personal Digital Assistant mobile device) dynamic signature data sets which take into account multisession and two different scenarios emulating real operation conditions. The performance of the proposed global features-based and time functions-based systems applying the two main stages considered in this paper have provided an average relative improvement of performance of 60.3% and 26.5% Equal Error Rate (EER), respectively, for random forgeries cases, compared with baseline systems. Finally, a fusion of the proposed systems has achieved a further significant improvement for the device interoperability problem, especially for skilled forgeries. In this case, the proposed fusion system has achieved an average relative improvement of 27.7% EER compared with the best performance of time functions-based system. These results- prove the robustness of the proposed approach and open the door for future works using devices as smartphones or tablets, commonly used nowadays.
Keywords :
feature extraction; feature selection; handwriting recognition; open systems; smart phones; EER; Wacom device; banking sector; biometric approach; biometric trait; biosecure DS2 dynamic signature dataset; biosecure DS3 dynamic signature dataset; commercial sector; device interoperability; equal error rate; feature selection; global feature-based system; improved sensor interoperability; interoperability device compensation; online biometric signature verification; personal digital assistant mobile device; random forgeries; smartphones; time function-based system; Biometrics; Device interoperabillity; Feature recognition; Fusion; Online services; Sensors; Signature verification; Biosecure; DTW; Device interoperability; fusion; global features based system; global features-based system; on-line signature; time functions based system; time functions-based system;
fLanguage :
English
Journal_Title :
Access, IEEE
Publisher :
ieee
ISSN :
2169-3536
Type :
jour
DOI :
10.1109/ACCESS.2015.2431493
Filename :
7104071
Link To Document :
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