Abstract
The paper presents experimental method for the extraction of handwritten signature features with the aim of incorporating them in the offline signature recognition system. The algorithm uses view-based approach and searches for the extreme values with the threshold value being applied. This investigation is a continuation of previous work extended with experiments on classification of resulted feature vectors. The classification of feature vectors is conducted by means of Dynamic Time Warping (DTW) algorithm. Experiments were carried out with the standard DTW algorithm with window and slope constraints.
This work is supported by the Rector of Bialystok University of Technology (grant number W/WI/3/4).
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References
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Saeed, K., Adamski, M. (2006). Experimental Algorithm for Characteristic Points Evaluation in Static Images of Signatures. In: Saeed, K., Pejaś, J., Mosdorf, R. (eds) Biometrics, Computer Security Systems and Artificial Intelligence Applications. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-36503-9_9
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DOI: https://doi.org/10.1007/978-0-387-36503-9_9
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