A method and system of signature verification that includes receiving a signature-in-question, extracting at least one of an image of the signature-in-question and a trajectory of the signature-in-question from the received signature-in-question, accessing a reference signature, extracting at least one of a reference image and a reference trajectory from the accessed reference signature, comparing the at least one of the image of the signature-in-question and trajectory of the signature-in-question to the at least one of the reference image and reference trajectory, and determining whether signature-in-question is authentic based on the comparison.

Methods, systems, and computer program products are provided for signature verification. Signature verification may be provided for target signatures using genuine signatures. A signature verification model pipeline may extract features from a target signature and a genuine signature, encode and submit both to a neural network to generate a similarity score, which may be repeated for each genuine signature. A target signature may be classified as genuine, for example, when one or more similarity scores exceed a genuine threshold. A signature verification model may be updated or calibrated at any time with new genuine signatures. A signature verification model may be implemented with multiple trainable neural networks (e.g., for feature extraction, transformation, encoding, and/or classification).

A method for identifying or for verifying the identity of a user, using a plurality, of previously acquired reference signature vectors, a handwritten signature of the user and at least one additional item of handwritten information linked to the user that arc affixed beforehand to an in particular mobile digital sensor, in which method: a) said handwritten signature of the user and said at least one additional item of information are fused in order to generate at least one test signature vector, b) said at least one test signature vector is compared with a plurality of said reference signature vectors, and c) a likelihood score is generated on the basis at least of this comparison in order to identify or to verify the identity of the user.

Provided are a method and an apparatus for user authentication based on face recognition and handwritten signature verification, by which authentication accuracy in user authentication using a handwritten signature is further increased. The method including: receiving a handwritten signature of a user; acquiring a face image of the user who inputs the handwritten signature, simultaneously with the receiving of the handwritten signature; determining whether the user is a legitimate user, on the basis of characteristics information of the face image; adjusting a reference value for verification based on characteristics information of the handwritten signature, according to a result of determination based on the characteristics information of the face image; determining whether the user is the legitimate user, on the basis of the characteristics information of the received handwritten signature and the adjusted reference value.

Security on an information handling system may be improved by using a stylus. A stylus provides unique information about a user that may not be acquired by an information handling system through other methods. For example, a user's handwriting is often unique to that user and may provide a security check on the information handling system to confirm the user's identity. Further, the stylus is usually held in the user's hand and may be used to check the user's fingerprint to confirm the user's identity. These authentication techniques, including fingerprinting and handwriting, may be used to maintain persistent authentication while the user is using the stylus. As the user continues to interact with the information handling system with the stylus, the stylus continues to receive the user's fingerprint and handwriting, which may be checked to confirm the user of the information handling system is still the expected user.

Methods, systems, and computer program products are provided for signature verification. Signature verification may be provided for target signatures using genuine signatures. A signature verification model pipeline may extract features from a target signature and a genuine signature, encode and submit both to a neural network to generate a similarity score, which may be repeated for each genuine signature. A target signature may be classified as genuine, for example, when one or more similarity scores exceed a genuine threshold. A signature verification model may be updated or calibrated at any time with new genuine signatures. A signature verification model may be implemented with multiple trainable neural networks (e.g., for feature extraction, transformation, encoding, and/or classification).

Techniques for detecting counterfeit checks include using sensors to determine correspondence between items detected on a check using machine vision. Correspondence between different items on a received check is used to generate a check score, which is compared to a risk-based threshold to determine how a transaction involving the check should be handled.

A method for enhancing efficiency of a computerized electronic signature system by facilitating collection of signatures from multiple signatories is described. The method may initially involve verifying an identity of a first signatory by receiving data from the first signatory electronically, providing a document to the first signatory, receiving a first electronic signature on the document from the first signatory, and receiving a selection from the first signatory of a second signatory to sign the document as a witness. The method may then involve verifying an identity of the second signatory by receiving data from the second signatory electronically, providing the document to the second signatory, receiving a second electronic signature from the second signatory, providing a completed document, including the first signature and the second signature, and notifying the first signatory and the second signatory that the completed document is completed.

A writing pen, a signature recognition method, and a signature recognition system are provided. A non-writing end of the writing pen is equipped with a motion sensing device. The writing pen records a motion trajectory of the non-writing end when the writing pen writes on a plane writing trajectory generating device. When the motion trajectory and/or a plane writing trajectory pass a comparison, a signature comparison device determines that a signature is from a specific person.

A system, method, and computer program product for verifying signatures. The system includes at least one processing component, at least one memory component, and a reference storage comprising a set of reference signatures. The system also includes a model generator configured to generate a signature model based on the set of reference signatures. Further, the system includes a verification component configured to receive a signature, and determine whether the signature is valid.