# US 12,002,296 B2 · Identification verification system and related methods

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- Number: US 12,002,296 B2
- Document ID: US12002296B2
- Status: Granted
- Kind: B2
- Application number: 18/083,667
- Filed: 2022-12-19
- Published: 2023-04-20
- Granted: 2024-06-04
- Earliest claimed: 2019-06-19
- Assignees: Checkpoint Id, Inc.
- Applicants: Checkpoint Id, Inc.
- Inventors: Ryan Antrim; Andrey Stanovnov
- Web page: https://patentgrep.com/patent/US12002296B2

## CPC

- G06V 40/70: Multimodal biometrics, e.g. combining information from different biometric modalities
- G06F 16/54: Browsing; Visualisation therefor
- G06F 16/583: using metadata automatically derived from the content
- G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints
- G06F 21/33: using certificates
- G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes}
- G06K 19/06037: {multi-dimensional coding}
- G06N 20/00: Machine learning
- G06V 10/98: Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
- G06V 40/172: {Classification, e.g. identification}
- G06V 40/50: Maintenance of biometric data or enrolment thereof
- G06V 40/55: {Performing matching on a personal external card, e.g. to avoid submitting reference information}
- G06V 40/67: {by interactive indications to the user}
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06K: GRAPHICAL DATA READING (image or video recognition or understanding G06V); PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

Another aspect of the present disclosure relates to a method for identification verification. The method may include receiving, from a computing device, a request for identification verification of an individual at a web server. The web server may include an orientation verification module and a facial recognition module. The method may include receiving at a database an identification card image and a picture image. The method may include verifying an orientation of the identification card image is oriented relative to an accepted orientation using the orientation verification module. The method may include, if the identification card image is not oriented relative to the accepted orientation, using the web server, iteratively rotating the identification card image in one or more increments and assessing if the identification card image is oriented at the accepted orientation until the identification card image is oriented at the accepted orientation.

## Claims

### Claim 1

A system configured for identification verification, the system comprising:
one or more processors comprising an image receiving module, a privacy module, a format validation module, a pattern validation module, and a facial recognition module;
wherein the one or more processors are configured by machine-readable instructions to:
receive a first image with the image receiving module, the first image comprising an identification document with a first likeness of an individual;
receive a second image with the image receiving module, the second image comprising a second likeness of the individual;
encrypt or purge one or more pieces of identifying information of the individual in the identification document of the first image using the privacy module;
determine whether the identification document in the first image corresponds with a known form of identification document using the format validation module;
identify at least one element in the identification document and determine whether the at least one element corresponds to at least one authenticity element of the known form of identification document above a predetermined confidence level using the pattern validation module;
determine whether the first likeness corresponds with the second likeness within a predetermined confidence range using the facial recognition module;
transmit a first error message to the remote platform through a telecommunication channel using the pattern validation module if the at least one element corresponds to the at least one authenticity element below the predetermined confidence level; and
transmit a second error message to the remote platform through the telecommunication channel with the facial recognition module if the first likeness is not within the predetermined confidence range of the second likeness.

### Claim 2 (depends on 1)

The system of claim 1, wherein the one or more processors further comprise an orientation verification module, and
wherein the one or more processors are configured by machine-readable instructions to verify whether the first likeness is in a same orientation as the second likeness.

### Claim 3 (depends on 2)

The system of claim 2, wherein the one or more processors are configured by machine-readable instructions to iteratively rotate the first image such that the first likeness is aligned with the second likeness.

### Claim 4 (depends on 1)

The system of claim 1, wherein the one or more processors further comprise a quality verification module and the one or more processors are configured by machine-readable instructions to verify whether the first and second images each meet a predetermined quality threshold and to transmit a third error message to the remote platform through the telecommunication channel with the quality verification module if at least one of the first and second images does not meet the predetermined quality threshold.

### Claim 5 (depends on 1)

The system of claim 1, wherein the one or more processors further comprise a file format module, and
wherein the one or more processors are configured by machine-readable instructions to verify whether the first and second images are each an accepted file type and to transmit a third error message to the remote platform through the telecommunication channel with the file format module if at least one of the first and second images is not the accepted file type.

### Claim 6

A method for verifying the identity of an individual, the method comprising:
receiving a first digital image from a remote platform, the first digital image being in a first orientation and comprising a presented identification document with a first likeness of the individual;
receiving a second digital image from the remote platform, the second digital image being in a second orientation and comprising a second likeness of the individual;
encrypting or purging one or more pieces of identifying information of the individual in the presented identification document in the first digital image;
determining whether the presented identification document in the first digital image corresponds with a predetermined acceptable form of identification;
identifying at least one element in the presented identification document and determining whether the at least one element corresponds to at least one predetermined authenticity element of the predetermined acceptable form of identification above a predetermined confidence level with a processor implementing machine-readable instructions for pattern validation;
determining whether the first likeness matches the second likeness within a predetermined confidence range with the processor implementing machine-readable instructions for facial recognition;
transmit a first output to the remote platform, the first output being indicative of whether the presented identification document represents a valid form of identification and whether the at least one element corresponds to at least one predetermined authenticity element of the predetermined acceptable form of identification above a predetermined confidence level; and
transmit a second output to the remote platform, the second output being indicative of whether the first likeness is within a predetermined confidence range of the second likeness.

### Claim 7 (depends on 6)

The method of claim 6, further comprising determining whether the first orientation corresponds to the second orientation using optical character recognition.

### Claim 8 (depends on 6)

The method of claim 6, further comprising determining whether the first orientation corresponds to the second orientation using facial recognition.

### Claim 9 (depends on 6)

The method of claim 6, further comprising iteratively rotating the first digital image until the first digital image is in the second orientation.