Verification of normalized online signatures without calculating dynamic features

Objectives. Study of the method of verification of the authenticity of a human signature made on a tablet with a stylus and given three parameters: coordinates X , Y and pressure on the tablet P . Methods. N genuine dynamic human signatures are given. Data describing different signatures made by one person always have a different number of points. The main variants of normalization of the original signature data are investigated. A model of an individual image of human signatures is built without calculating dynamic features. The method of dynamic time transformation (DTW) is used to compare similar data of different signatures. The results of this transformation are DTW-distances between the data of pairs of signatures. These distances serve as coordinates of a point in the feature space describing the similarity of a pair of signatures. A set of such points represents a model describing the similarity of genuine human signatures. The parameters of the signature being verified are compared with each of the N authentic signatures used to build the model for their proximity to the model. If more than half of these pairs are further from the model than a certain threshold T , the signature is considered fake. Results. As a result of comparative experiments, a variant of normalization of initial data of dynamic human signatures was found, which allows verification of such signatures without calculating additional features usually calculated from the initial data X , Y , P . Conclusion. Experiments to generate individual signature models for each of 230 people from the publicly available MCYT dynamic signature database (a subset of the DeepSignDB database) and verify the authenticity of 11,500 signatures made on behalf of these people showed a verification accuracy of 99.82 %. Half of them were genuine, half were fake.