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One of the most challenging problems in online signature verification is to select the best features to model the signatures. A widely used technique to address this problem is to combine different feature sets selected by different criteria. In this paper, the combination of three different feature sets, viz., an automatically selected feature set, a feature set relevant to Forensic Handwriting Experts...
This paper evaluates the feasibility of using only Forensic Handwriting Experts (FHEs) based features for automatic online signature verification. Both, global features and features based on the wavelet representation of the time functions associated with the signing process, which are relevant to FHEs, are considered in this paper. Two combination approaches of global and time function FHE based...
In this paper, feature combinations associated with the most commonly used time functions related to the signing process are analyzed, in order to provide some insight on their actual discriminative power for online signature verification. A consistency factor is defined to quantify the discriminative power of these different feature combinations. A fixed-length representation of the time functions...
In this paper, orthogonal polynomials series are used to approximate the time functions associated to the signatures. The coefficients in these series expansions, computed resorting to least squares estimation techniques, are then used as features to model the signatures. Different combinations of several time functions (pen coordinates, incremental variation of pen coordinates and pen pressure),...
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