G06V30/418

Systems and methods for digital identity verification

Systems and methods for digital identity verification are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for digital identify verification may include: (1) receiving, from a user electronic device or at a website, an image of an identity document for a user, the identity document comprising an image of the user; (2) processing the identity document with at least one business-specific rule; (3) extracting identity information from the identity document; (4) determining a match rate of the image of the user on the identity document to a captured image; (5) assigning a verification score to the user based on extracted identity information and the match rate; and (6) publishing the verification score to at least one system.

COMPUTER-IMPLEMENTED METHOD FOR COPY PROTECTION, DATA PROCESSING DEVICE AND COMPUTER PROGRAM PRODUCT
20220415111 · 2022-12-29 ·

A computer-implemented method for preventing unauthorized processing of a digital representation of at least a portion of a document, a device for data processing, and a computer program product are provided, wherein in particular the document is a banknote. The method comprises providing data, wherein the data is based on the digital representation of at least a portion of a test element. The digital representation may be an image file corresponding to the at least one portion of the test element. The method also involves analyzing the data with regard to data representing at least one characterizing feature of the at least one portion of the document. The method further comprises activating prohibiting means if the data being based on the digital representation of the at least one portion of the test element is similar to the data representing the at least one characterizing feature. The prohibiting means prohibit the data being based on the digital representation of the at least one portion of the test element to be further processed, in particular comprising copying and/or transmitting and/or printing and/or reproducing the data. Alternatively, the prohibiting means amend the data such that the data is prevented from being transmitted and/or printed and/or reproduced and/or further amended by data processing devices.

COMPUTER-IMPLEMENTED METHOD FOR COPY PROTECTION, DATA PROCESSING DEVICE AND COMPUTER PROGRAM PRODUCT
20220415111 · 2022-12-29 ·

A computer-implemented method for preventing unauthorized processing of a digital representation of at least a portion of a document, a device for data processing, and a computer program product are provided, wherein in particular the document is a banknote. The method comprises providing data, wherein the data is based on the digital representation of at least a portion of a test element. The digital representation may be an image file corresponding to the at least one portion of the test element. The method also involves analyzing the data with regard to data representing at least one characterizing feature of the at least one portion of the document. The method further comprises activating prohibiting means if the data being based on the digital representation of the at least one portion of the test element is similar to the data representing the at least one characterizing feature. The prohibiting means prohibit the data being based on the digital representation of the at least one portion of the test element to be further processed, in particular comprising copying and/or transmitting and/or printing and/or reproducing the data. Alternatively, the prohibiting means amend the data such that the data is prevented from being transmitted and/or printed and/or reproduced and/or further amended by data processing devices.

OFFICIAL DOCUMENT PROCESSING METHOD, DEVICE, COMPUTER EQUIPMENT AND STORAGE MEDIUM
20220414345 · 2022-12-29 ·

The application belongs to the field of big data, and particularly relates to an official document processing method, device, computer equipment and storage medium. The method includes the following steps of: performing format analysis on the to-be-reviewed official document, then acquiring the to-be-reviewed official document of standard file type, and identifying all file components and contents in the to-be-reviewed official document of standard file type; performing text format detection, text content detection and frame layout detection synchronously by a preset text processing model, obtaining a format detection result, a content detection result and a layout detection result; generating a detected error content according to the format detection result, content detection result and layout detection result, calling out a standard writing rule corresponding to the detected error content, marking the detected error content and the standard writing rule in the to-be-reviewed official document.

OFFICIAL DOCUMENT PROCESSING METHOD, DEVICE, COMPUTER EQUIPMENT AND STORAGE MEDIUM
20220414345 · 2022-12-29 ·

The application belongs to the field of big data, and particularly relates to an official document processing method, device, computer equipment and storage medium. The method includes the following steps of: performing format analysis on the to-be-reviewed official document, then acquiring the to-be-reviewed official document of standard file type, and identifying all file components and contents in the to-be-reviewed official document of standard file type; performing text format detection, text content detection and frame layout detection synchronously by a preset text processing model, obtaining a format detection result, a content detection result and a layout detection result; generating a detected error content according to the format detection result, content detection result and layout detection result, calling out a standard writing rule corresponding to the detected error content, marking the detected error content and the standard writing rule in the to-be-reviewed official document.

Semantic Difference Characterization for Documents

A computer implemented method determines differences between documents. The method includes parsing a first document and a second document into respective distinct instances of content. The distinct instances of content are classified into different categories. Category specific matching algorithms are applied to each of the respective instances of content to determine a similarity score for each of the respective instances of content. Semantic differences between the first document and the second document are analyzed as a function of the similarity scores. A characterization of the semantic differences is generated.

VALIDATING IDENTIFICATION DOCUMENTS

The method, system, and non-transitory computer-readable medium embodiments described herein are directed to verifying identification documents. In various embodiments, a server may receive a first image of a front-side of an identification document. The server may extract a first feature of the front-side of the identification document from the first image using optical character recognition (OCR) and identify a first environmental feature from the first image. The server may receive a second image of a backside of the identification document and identify a second feature of the backside of the identification document from the second image. The server may also identify a second environmental feature from the second image. The server may verify the identification document by confirming that the first feature matches the second feature and the first environmental feature matches the second environmental feature.

DATA CLASSIFICATION BASED ON RECURSIVE CLUSTERING
20220414369 · 2022-12-29 ·

Methods and systems are presented for providing a machine learning model framework configured to perform complex data classifications. Upon receiving a request for classifying data, the data is recursively assigned to one or more clusters. During each iteration of clustering assignment, a set of clusters is selected based on a previously assigned cluster for the data, and the data is then assigned to a particular cluster from the selected set of clusters. The machine learning model framework also includes a plurality of machine learning models configured to perform simple data classifications. A particular machine learning model is selected from the plurality of machine learning model based on the one or more clusters to which the document is assigned. The particular machine learning model is then used to classify the document.

Methods and apparatus to determine the dimensions of a region of interest of a target object from an image using target object landmarks
11538235 · 2022-12-27 · ·

Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

Methods and apparatus to determine the dimensions of a region of interest of a target object from an image using target object landmarks
11538235 · 2022-12-27 · ·

Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.