A method of recognizing individuals by means of at least one processor executing a recognition algorithm comprising the steps of: detecting biometric characteristics of a finger of a candidate for recognition while writing a signature by pressing the finger against a signature surface; encoding both the written signature and also the biometric characteristics in order to form signature data and biometric data of the candidate; and using the algorithm to compare the signature data and the biometric data of the candidate with signature data and fingerprint biometric data belonging to at least one individual and stored on a data medium.

The present invention provides a computer implemented method, a system, and a computer program product for verifying a writing of a user. In an exemplary embodiment, the present invention includes in response to receiving a writing on a pressure sensing touchpad logically coupled a computer system, recording a position and a pressure of one or more points of the writing via a pressure sensing touchscreen, executing a set of logical operations normalizing the writing, comparing the normalized writing to one or more stored writing parameters, executing a set of logical operations determining the normalized writing is within a tolerance of writing parameter deviation limits, thereby verifying the writing, and in response to determining the writing is within the tolerance of writing parameter deviation limits, storing, by the computer system, a value indicating that the writing is valid.

Handwriting verification methods and related computer systems, and handwriting-based user authentication methods and related computer systems are disclosed. A handwriting verification method comprises obtaining a handwriting test sample containing a plurality of available parameters, extracting geometric parameters, deriving geometric features comprising an x-position value and a y-position value for each of a plurality of feature points in the test sample, performing feature matching between geometric features of the test sample and a reference sample, determining a handwriting verification result based at least in part on the feature matching, and outputting the handwriting verification result. Techniques and tools for generating and preserving electronic handwriting data also are disclosed. Raw handwriting data is converted to a streamed format that preserves the original content of the raw handwriting data. Techniques and tools for inserting electronic handwriting data into a digital image also are disclosed.

Embodiments of the invention are generally directed to systems, methods, devices, and machine-readable mediums for implementing gesture-based signature authentication. In one embodiment, a method may involve recording a first gesture-based signature and storing the recorded first gesture-based signature. Then the method compares the first gesture-based signature with a second gesture-based signature. Then the method verifies the first gesture-based signature as authentic when the first gesture-based signature is substantially similar to the second gesture-based signature.

An authentication device includes an operation panel, a registered handwriting procedure acquiring portion, a long-pressing detecting portion, a handwriting detecting portion, and a handwriting authentication portion. The registered handwriting procedure acquiring portion acquires information of a registered handwriting procedure from a storage portion in which the information of the registered handwriting procedure has been stored, which represents a handwriting procedure including a trajectory of a handwriting operation performed on the operation panel and at least one of a time, a speed, and a number of strokes of the handwriting operation. The handwriting detecting portion detects the handwriting procedure in the handwriting operation performed on the operation panel, during a period in which the long-pressing operation is continuously detected. The handwriting authentication portion determines whether the detected handwriting procedure satisfies a predetermined approximation condition with respect to the acquired registered handwriting procedure, thereby determining whether authentication has succeeded or failed.

Methods and systems for adaptive, template-independent handwriting extraction from images using machine learning models and without manual localization or review. For example, the system may receive an input image, wherein the input image comprises native printed content and handwritten content. The system may process the input image with a model to generate an output image, wherein the output image comprises extracted handwritten content based on the native handwritten content. The system may process the output image to digitally recognize the extracted handwritten content. The system may generate a digital representation of the input image, wherein the digital representation comprises the native printed content and the digitally recognized extracted handwritten content.

Methods and systems are provided for implementing training of learning models, including obtaining a pre-trained weight set for a learning model on a sample dataset and on a first loss function; selecting at least two tasks having heterogeneous features to be computed by a reference model; obtaining a reference dataset for the at least two tasks; designating a second loss function for feature embedding between the heterogeneous features of the at least two tasks; training the learning model on the first loss function and training the reference model on the second loss function, in turn; and updating the weight set based on a feature embedding learned by the learning model and a feature embedding learned by the reference model, in turn. Methods and systems of the present disclosure may alleviate computational overhead incurred by executing the learning model and loading different weight sets at a central network of the model.

A document management system performs name matching operations to validate an identity claimed by a recipient of a document. To validate a claimed identity the document management system compares name data obtained from an identity data source with name data corresponding to a recipient entity of a document to determine whether name features of the identity source name data match recipient name data. The name matching operations may include applying a set of name matching rules to the identity source name data and the recipient name data to determine whether features that differ between the identity source name data and the recipient name data are acceptable alternative representations. Responsive to successfully validating the identity, the system may authorize the recipient to perform actions on the document. Identity source name data may be received from a variety of identity data sources, such as an identity document or a trusted service provider.

Embodiments of the invention are generally directed to systems, methods, devices, and machine-readable mediums for implementing gesture-based signature authentication. In one embodiment, a method may involve recording a first gesture-based signature and storing the recorded first gesture-based signature. Then the method compares the first gesture-based signature with a second gesture-based signature. Then the method verifies the first gesture-based signature as authentic when the first gesture-based signature is substantially similar to the second gesture-based signature.

A marking analysis system includes a marking data storage unit to store a plurality of marking data indicating a plurality of positions marked by a user in a book so as to correspond respectively to a plurality of users, a marking distribution analysis unit that analyzes the marking data and calculates a marking frequency for each of a plurality of unit areas in the book, and generates marking distribution characteristic data indicating a distribution of the marking frequency with respect to a position in the unit area, a marking distribution characteristic data storage unit to store the marking distribution characteristic data, and a similar user retrieval unit that, when determining that the distribution of the marking frequency indicated by the marking distribution characteristic data of a target user selected as a processing target and the distribution of the marking frequency indicated by the marking distribution characteristic data of another user are similar, extracts the another user as a similar user who is similar to the target user.