Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
Spoken Language Processing: A Guide to Theory, Algorithm, and System Development
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
Gaussian Mixture Models for on-line signature verification
WBMA '03 Proceedings of the 2003 ACM SIGMM workshop on Biometrics methods and applications
Using Adapted Levenshtein Distance for On-Line Signature Authentication
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Local and Global Feature Selection for On-line Signature Verification
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
On-line signature recognition based on VQ-DTW
Pattern Recognition
HMM-based on-line signature verification: Feature extraction and signature modeling
Pattern Recognition Letters
An on-line signature verification system based on fusion of local and global information
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
Generation and evaluation of brute-force signature forgeries
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Eigen-model projections for protected on-line signature recognition
BioID'11 Proceedings of the COST 2101 European conference on Biometrics and ID management
Proceedings of the 2nd Conference on Wireless Health
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We propose a novel approach for on-line signature verification based on building HMM user models by adapting an ergodic Universal Background Model (UBM). State initialization of this UBM is driven by a dynamic signature feature. This approach inherits the properties of the GMM-UBM mechanism, such as minimizing overfitting due to scarcity of user training data and allowing a world-model type of likelihood normalization. This system is experimentally compared to a baseline state-of-the-art HMM-based online signature verification system using two different databases: the well known MCYT-100 corpus and a subset of the signature part of the BIOSECURE-DS2 corpus. The HMM-UBM approach obtains promising results, outperforming the baseline HMM-based system on all the experiments.