Patent ID: 11915524
Assignee: TATA CONSULTANCY SERVICES LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A system for handwritten signature verification, wherein the system comprises:
a shadow sensing unit comprising a sensor array with a plurality of sensors, an ambient light source and a data acquisition unit; and
a signature verification system;
wherein the shadow sensing unit, providing a shadow sensing mechanism, is configured to:
monitor hand movement associated with a handwritten signature gesture of a subject for a predefined time window;
the signature verification system is configured to:
extract signature data for the subject from the shadow sensing mechanism for the predefined time window at regular predefined time instants, wherein the extracted signature data for the subject is represented as a matrix with each row of the matrix representing signature data corresponding to each time instant and each column representing status of each sensor from the sensor array for corresponding time instant;
pre-processing the extracted signature data by differentiating the matrix row wise and column wise to generate a row difference matrix and a column difference matrix;
determine:
an idle signature time fraction for the extracted signature data of the subject being monitored from the column difference matrix; and
a plurality of signature parameters based on the column difference matrix and the row difference matrix, wherein the plurality of signature parameters comprise a temporal variability for each sensor derived from the column difference matrix, a positional variability for each sensor derived from the row difference matrix and a distance value of a distance parameter derived for each sensor that maximizes an optimization function, wherein the optimization function is defined by the distance parameter, a penalty term, a matching signature covariance matrix, a nonmatching signature covariance matrix and a constant value; and

analyze the idle signature time fraction and the plurality of signature parameters of the subject being monitored based on a Support Vector Machine (SVM) classifier, wherein the SVM classifier performs online classification of the extracted signature data into one of a matching signature class and a non-matching signature class with respect to a subject of interest.