The present disclosure provides for methods for signature and identity verification and authentication. The system may comprise a plurality of visual capture devices, virtual data, and a plurality of virtual databases. The plurality of visual capture devices may capture a photo or video of the signee, the signature, a witness, or a combination thereof. The system may comprise a plurality of auxiliary authentication components for recording data such as the date, time, and location of the signature verification, as non-limiting examples. The virtual data may comprise visual data and other metadata. The method may comprise uploading the virtual data collected during the signature verification to a blockchain, where a signature authentication may occur or be recorded. Auxiliary authentication devices may include a plurality of audio capture devices, a plurality of geospatial capture devices, such as accelerometers or GPS, a plurality of pressure sensors, or any combination thereof, as non-limiting examples.

The present embodiments provide an environment where a user first creates or imports a document comprising of fields to be completed by one or more users. All users who have view-only access or can act on a document are considered to be “in the workflow.” All users in the workflow (except view-only users) can take actions in the document by editing, adding or entering values or signatures in those fields. When the document is complete, a computing device adds an encrypted token visualization element to the document that uniquely identifies and secures the document. Thereafter, a copy of the original document, all attachments, authentication, security and validation information, and all other relevant information about the document and users will be available to view in the chain of custody and audit trail by the authorized users by scanning the token visualization element within the platform (web application or mobile application).

A system for extraction and verification of handwritten signatures from arbitrary documents. The system comprises one or more computing devices configured to: receive a digital image of a document; perform a dilating transformation via convolution matrix on the digital image to obtain a modified image; determine a plurality of regions of connected markings in the digital image; based at least in part on a pixel density or proximity to an anchor substring of each region, determine whether any region contains any handwritten signature; extract first image data of the region containing a handwritten signature from the digital image; retrieve second image data of a confirmed example signature for a purported signer of the handwritten signature; and based on a comparison of the first image data with the second image data, forward a determination of whether the first image data and second image data are similar.

A method for extracting signatures and assigning signatory name attributions to the extracted signature images from unstructured digital documents is provided. The method includes: receiving a document that includes a signature; detecting a first region within the document in which the signature is present; applying a region-based convolutional neural network to the detected first region in order to demarcate a boundary that surrounds the detected first region; detecting a second region within the document in which a name that relates to the signature is present, by scanning the document to obtain a set of text words and then applying a named entity recognition (NER) machine learning algorithm to determine which text words are names; and assigning a signatory name attribution to the name that is present in the second region, based on a calculated distance between the name and the demarcated boundary.

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.

An electronic device is provided which includes a light emitting module that radiates infrared light, a window disposed on the light emitting module and having a specific refractive index with respect to the infrared light, wherein the window includes a refraction part that totally reflects the infrared light inside the window in correspondence with the specific refractive index, and a fingerprint sensor disposed under the window and obtaining a fingerprint of a user based on a user input on the window by using scattered light of the infrared light.

A biometric registration and/or verification system and method may comprise: a biometric sensor for capturing biometric data; a data entry device, a computer processor for receiving captured biometric data and entered data; and a database storing records thereof. The identifying biometric data may be related to the entered data in the database record. The biometric data is tested for satisfying a predetermined quality standard before being utilized, e.g., stored in the database record and/or compared.

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.

The technology described herein generates a unique identifier for a visual media that comprises pre-printed visual indications on the visual media and a user's handwritten signature. The location of the signature on the visual media can be determined by including preprinted fiducial marks on the visual media. The fiducial markers act as landmarks that allow the size and location of the signature to be determined in absolute terms. The unique identifier is then stored in computer memory on a user-experience server. The user-experience server can associate the unique identifier with a digital asset, such as an image or video, designated by the user. When the unique identifier is provided to the user-experience server a second time, the digital asset can be retrieved and output to the computing device that provided the unique identifier.

A system is provided for generating an online biometrically accurate electronic signature. The system includes a computer interface module which records movement of a cursor on a computer screen and outputs the recorded data. A signature generation module which receives the recorded data and generates a graphical image based upon the recorded data.