Systems and methods for performing fingerprint based user authentication using imagery captured using mobile devices

Inventors

Mather, Jonathan FrancisOthman, AsemTyson, RichardSimpson, Andrew

Assignees

Veridium IP Ltd

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Publication Number

US-12223760-B2

Patent

Publication Date

2025-02-11

Expiration Date


Abstract

Technologies are presented herein in support of a system and method for performing fingerprint recognition. Embodiments of the present invention concern a system and method for capturing a user's biometric features and generating an identifier characterizing the user's biometric features using a mobile device such as a smartphone. The biometric identifier is generated using imagery captured of a plurality of fingers of a user for the purposes of authenticating/identifying the user according to the captured biometrics and determining the user's liveness. The present disclosure also describes additional techniques for preventing erroneous authentication caused by spoofing. In some examples, the anti-spoofing techniques may include capturing one or more images of a user's fingers and analyzing the captured images for indications of liveness.

Core Innovation

A fingerprint recognition approach uses a mobile device having a camera to receive a fingerprint image depicting a fingerprint of a user. The processor identifies a fingertip segment in the received fingerprint image with a finger detection algorithm and enhances the fingerprint image by processing the fingertip segment using an analysis module to enhance detail captured by the mobile device camera.

The enhancement is performed to mimic quality and attributes of fingerprint impression images captured from live scan sensors. The method generates an enhanced fingerprint image suitable for matching with fingerprint impression images captured from live scan sensors, including scaling the enhanced fingerprint image according to a prescribed reference frequency of fingerprint ridges that is an attribute of images stored in the storage medium captured from live scan sensors.

After generating the enhanced fingerprint image, the processor identifies discriminatory fingerprint features from the fingertip segment of the enhanced fingerprint image and stores the enhanced fingerprint image in the storage medium as a representation of the discriminatory features. A system embodiment provides software application instructions executable by the processor to perform receiving, fingertip segment identification, enhancement to mimic live-scan attributes including ridge frequency scaling, discriminatory feature identification, and storing the enhanced fingerprint image.

Claims Coverage

This patent content includes two independent claims (clm-00001 and clm-00012). Both claims share the same core inventive feature set: mobile-camera fingerprint image acquisition, fingertip segmentation, enhancement to mimic live-scan fingerprint impression attributes, ridge-frequency scaling to a reference frequency, identification of discriminatory features, and storing the enhanced representation for matching.

Mobile-device fingerprint image receipt and fingertip segmentation

The processor receives a fingerprint image depicting a fingerprint of the user captured using the camera of the mobile device, and identifies a fingertip segment in the fingerprint image using a finger detection algorithm.

Enhancing fingertip detail to mimic live-scan attributes

The processor enhances the fingerprint image by processing the fingertip segment with an analysis module to enhance detail to mimic a quality and attributes of fingerprint impression images captured from live scan sensors, and generates an enhanced fingerprint image suitable for matching with fingerprint impression images captured from live scan sensors.

Ridge-frequency scaling based on a prescribed reference frequency

The generating step scales the enhanced fingerprint image according to a prescribed reference frequency of fingerprint ridges, where the prescribed reference frequency is an attribute of images stored in the storage medium captured from live scan sensors.

Discriminatory feature identification and storage of an enhanced representation

The processor identifies discriminatory fingerprint features from the fingertip segment of the enhanced fingerprint image and stores the enhanced fingerprint image in the storage medium as a representation of the discriminatory features.

Software application for executing the enhancement workflow on the mobile device

A software application comprising instructions in the form of code stored on the storage medium configures the processor to receive the fingerprint image, identify the fingertip segment, process the fingertip segment to mimic live-scan attributes, scale according to the prescribed reference frequency, identify discriminatory features, and store the enhanced fingerprint image as a representation of those discriminatory features.

Across both independent claims, the main inventive coverage is the mobile-camera capture and fingertip segmentation, followed by generating an enhanced fingerprint image that mimics live-scan fingerprint impression attributes, scaling the ridge frequency to a prescribed reference frequency from stored live-scan images, identifying discriminatory fingerprint features, and storing the enhanced representation for matching.

Stated Advantages

Improved accuracy for fingerprint recognition using multiple fingers is highlighted in the provided description.

Universality that mitigates enrollment failures is highlighted in the provided description.

Resistance to spoofing is highlighted in the provided description.

Documented Applications

Fingerprint recognition performed via a mobile device camera using the enhanced fingerprint image suitable for matching with fingerprint impression images captured from live scan sensors.

Compatibility with legacy fingerprint systems by matching against a database of fingerprint impression images referenced as an IAFIS database.

Optional liveness determination to detect spoof attacks is mentioned in the provided description.

Multimodal extensions are mentioned, including hybrid biometric identifiers (e.g., face/iris) and broader acquisition modes (distance, NIR/IR, fingerprint-on-the-move, super-resolution).

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