A bio-electronic tag-based feature extraction and verification method, a device therefor and a tag. The fingerprint electronic tag includes: a resilient film substrate; an antenna formed by a conductive layer attached to the film substrate, the antenna comprising a fingerprint region which forms a microstrip antenna with a printed fingerprint pattern when the fingerprint electronic tag is attached to a finger; and a protective film covering the antenna and bonded to the film substrate

The invention provides an offline handwriting individual recognition system and method based on two-dimensional dynamic features. The method comprises: obtaining a first handwriting image corresponding to suspicious handwriting and second handwriting images corresponding to a plurality of sample handwriting; pre-processing the first handwriting image and the second handwriting images to obtain a first pre-processed image and second pre-processed images; extracting a first skeleton image and second skeleton images from the first pre-processed image and the second pre-processed images; obtaining a first writing trajectory and second writing trajectories according to the first skeleton image and the second skeleton images; extracting first dynamic features and second dynamic features according to the first writing trajectory and the second writing trajectories; performing processing to obtain a correlation coefficient between the suspicious handwriting and the sample handwriting, and performing processing to obtain an individual recognition result according to the correlation coefficient.

The invention provides an offline handwriting individual recognition system and method based on two-dimensional dynamic features. The method comprises: obtaining a first handwriting image corresponding to suspicious handwriting and second handwriting images corresponding to a plurality of sample handwriting; pre-processing the first handwriting image and the second handwriting images to obtain a first pre-processed image and second pre-processed images; extracting a first skeleton image and second skeleton images from the first pre-processed image and the second pre-processed images; obtaining a first writing trajectory and second writing trajectories according to the first skeleton image and the second skeleton images; extracting first dynamic features and second dynamic features according to the first writing trajectory and the second writing trajectories; performing processing to obtain a correlation coefficient between the suspicious handwriting and the sample handwriting, and performing processing to obtain an individual recognition result according to the correlation coefficient.

Two models are first trained and then test images are applied to the two trained models in an effort to detect signature forgeries. The first model is trained with pairs of signature images and the resultant trained model is capable of detecting blind forgeries. The second model is trained with triplets of signature images and is capable of detecting skilled signature forgeries. After the two models are trained, test images are applied to the models and determinations are made as to whether a blind or skilled forgery is present.

A method is provided for authenticating a user using biometrics and digitized handwritten signature. A verification server uses a data identifier to find a corresponding piece of personal identification data. A user uses a biometric stylus and a handwriting input device to create a handwriting pattern; meanwhile, the biometric stylus acquires fingerprint data of the user. The handwriting input device transmits the fingerprint data and the handwriting pattern to the verification server. The verification server verifies the handwriting pattern and the fingerprint data using a handwriting template and a fingerprint template included in the personal identification data thus found, and obtains user identification data for verifying an identity of the user from the personal identification data when the handwriting pattern and the fingerprint data are successfully verified.

An electronic device may include a display, a memory, and at least one processor operatively connected to the display and the memory. The at least one processor is configured to acquire, based on input of first handwritten information, first personalized feature data corresponding to a first personalized feature from the first handwritten information, acquire, from the first handwritten information, first content data from which the first personalized feature has been removed, encode the first personalized feature data, acquire first masked handwritten information based on the encoded first personalized feature data and the first content data, and provide the first masked handwritten information on the display.

Systems and methods for providing blockchain based checks (BC Checks) that may be redeemed without traditional coordination between financial institutions of participants. Some particular embodiments of the present disclosure enable a recipient of a BC check (the payee) to validate the BC check directly through a blockchain hosted at least in part by the financial institution that issued the checks to the network participant using the BC check as payment (the payer) to the recipient. Some embodiments of the present disclosure further enable the payee to redeem the BC check for fiat currency directly through the payer's financial institution (even if the payee and payer do not share the same financial institution).

The present invention solves the problem by having: a first recording unit which accepts a handwritten electronic signature by a transactor and records the handwritten electronic signature in an electronic document; a second recording unit which records record information including transaction position information at a time that the handwritten electronic signature is recorded, in image data of the electronic document where the handwritten electronic signature is recorded by the first recording unit; and a managing unit which manages the record information recorded by the second recording unit and the image data where the record information is recorded as managing information, while associating the record information with the image data.

A blockchain-based electronic signature method includes: receiving an electronic signature authentication request sent by an electronic signature client, wherein the electronic signature client is bound to one or more legal signature users, and the electronic signature authentication request includes biometric information of a signature user collected by the electronic signature client; in response to the electronic signature authentication request, authenticating whether the signature user is a legal signature user bound to the electronic signature client based on the biometric information; and if yes, returning an authentication result to the electronic signature client, so that the electronic signature client further prompts the signature user to perform an electronic signature operation in response to the authentication result; and receiving an electronic signature submitted by the signature user and collected by the electronic signature client, and publishing the electronic signature to a blockchain.

Disclosed are example embodiments of systems and methods for selecting components for building graph-based learning machines. An example system for selecting components for building graph-based learning machines includes a reference learning machine, one or more test signals, and a component analyzer module. The component analyzer module is configured to analyze, using the one or more test signals, one or more component in the reference machine by ranking different components in the reference learning machine in terms of their efficiency and effectiveness.