Biometric Hash based on Statistical Features of Online Signatures
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Communications of the ACM - Multimodal interfaces that flex, adapt, and persist
Biometric User Authentication for IT Security: From Fundamentals to Handwriting (Advances in Information Security)
Personal verification using palmprint and hand geometry biometric
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Multimodal biometrics for voice and handwriting
CMS'05 Proceedings of the 9th IFIP TC-6 TC-11 international conference on Communications and Multimedia Security
Evaluation of Fusion for Similarity Searching in Online Handwritten Documents
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
Interacting with Computers
Security-relevant challenges of selected systems for multi-user interaction
AMR'09 Proceedings of the 7th international conference on Adaptive multimedia retrieval: understanding media and adapting to the user
Comparative study on fusion strategies for biometric handwriting
Proceedings of the thirteenth ACM multimedia workshop on Multimedia and security
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In this paper, a comparison of an existing multi-algorithmic and a new multi-semantic fusion approach for biometric online handwriting user verification is presented. First, in order to improve the authentication performance of a biometric online handwriting system four classification algorithms are combined using several weighting strategies for matching score level fusion. Second, based on the best two algorithms and the best weighting strategy found during the test of the multi-algorithmic approach, a new multi-semantic fusion approach using a pair wise combination of four semantics on matching score level is proposed. As semantics we understand alternative handwritten contents (e.g. symbols) in addition to signatures. We show that both fusion approaches, multi-algorithmic and multi-semantic, can lead to a fusion result which is better than the result of the best single algorithm or semantics involved. While the improvement for the multi-algorithmic system yields 19%, we observe more than 57% for the multi-semantic approach.