Signature verification based on topological stochastic models

A non-transitory computer-readable medium storing instructions that, when executed by a processor, programs the processor to:

• access an input image of a signee to be authenticated;
• identify a topological stochastic model (TSM) trained to authenticate signatures from the signee, the TSM comprising an aggregate vector of eigenvalues that is aggregated from vectors of eigenvalues corresponding to respective authentic signatures of a signee;
• obtain a binary image of the input image;
• split the binary image into a plurality of partitions;
• assign a symbol to each partition of the plurality of partitions;
• identify pixel coordinates in the binary image that include at least a portion of the input image;
• determine a sequence of symbols representing a topological traversal path of the signature based on the identified pixel coordinates in the binary image, the sequence of symbols corresponding to the partitions that correspond to the identified pixel coordinates;
• determine an input stochastic transition matrix based on the sequence;
• generate an input vector of eigenvalues based on the input stochastic transition matrix;
• determine a distance between the input vector of eigenvalues and the aggregate vector of eigenvalues of the TSM;
• and
• determine whether the input image is authentic based on the distance.

A method of training a topological stochastic model (TSM) for signature verification, comprising:

• accessing, by a computing device, a first sample of an authentic signature of a person and a second sample of the authentic signature of the person;
• generating, by the computing device, a first vector of eigenvalues for the first authentic signature based on TSM feature extraction on the first authentic signature;
• generating, by the computing device, a second vector of eigenvalues for the second authentic signature based on TSM feature extraction on the second authentic signature;
• aggregating, by the computing device, the first vector of eigenvalues and the second vector of eigenvalues;
• and
• generating, by the computing device, an aggregate vector of eigenvalues based on the aggregating, wherein the aggregate vector of eigenvalues is used as an authentication model against which an input image is authenticated.