Tracking of feature and stroke positions for off-line signature verification

There are inevitable variations in the signature patterns written by the same person. The variations can occur in the shape or in the relative positions of the characteristic features. In this paper, for the set of training signature samples, one approach is proposed to measure the positional variations of the one-dimension projection profiles of the signature patterns, another approach is proposed to determine the statistical variations in relative stroke positions of the two-dimension signature patterns. Given a signature to be verified, the positional displacements are determined and the authenticity is decided based on the statistics of the training samples. A matrix estimation technique is also proposed to obtain a better estimation of the covariance matrix for dissimilarity computation. Results show that the proposed systems compare favorably with other methods.