The Government of the United States of America, As Represented by the Secretary of Homeland Security

Arun Vemury

Daniel A Boyd

John J Howard

Jerry L Tipton

Yevgeniy B Sirotin

Cynthia M Cook

Jason Lim

Chang Ellison

Kelli L Biegger

Brandon P Gutierrez

William Washington

Nathan Grebasch

In an example, a method includes receiving, by an election office system from a voter device, a request for a voting ballot for an election, part or all of voter ID information associated with a first mobile identification credential which the voter device received from a first authorizing party system (APS), and consented data indication which indicates the part or all of voter ID information that is authorized by the voter device for release by the first APS to the election office system, the part or all of voter ID information to be verified to the election office system by the first APS; and using the verified part or all of voter ID information to verify or not verify an identity of the voter. The identity of the voter is to be verified before the election office system grants the request to provide the voting ballot to the voter.

Voter identification using mobile identification credential

Aspects of the present invention relate to machines, systems, and methods for detecting a morphed image on an ID card associated with a user. The invention may comprise a plurality of security kiosks, a user database, morphed image detection logic, surveillance cameras, a surveillance database, surveillance similarity logic, user identification logic, message logic, and detainment logic. The machines, systems, and methods may assist an operator in controlling access of an individual using an ID bearing a morphed image.

Morphed image detection logic and surveillance systems

Systems and methods for providing exception failover augmented, homomorphic encrypted (HE) distributing, end-to-endpoint persistent encryption, and distributed HE domain non-decrypting, privacy-protective biometric processing are provided. Some configurations may include generating HE biometric feature data, based on homomorphic encrypting the biometric feature data. Some configurations determine an exception status of the HE biometric feature data between exception and non-exception. Systems and methods may include performing a HE domain, non-decrypting biometric classifying of the HE biometric feature data.

Biometric identification using homomorphic primary matching with failover non-encrypted exception handling

Systems and methods for measuring skin tone. A camera and computer may measure skin tone health of a face dataset and color quality of a single face image. The computer and camera may measure skin tone across wide sample of volunteers, express skin tone in CIELCH coordinates; and identify the range of observed lightness, chromaticity, and hue values in the population to determine a sample set. The computer and camera may be configured to match the image to a coordinate system of lightness, chromaticity, and hue in the sample set. If a match is not possible, the computer may be configured to select a coordinate closest to the measured lightness, chromaticity, and hue.

Methods and systems for establishing accurate phenotype metrics

In examples, a relative skin reflectance of a captured image of a subject is quantified. Based on the relative skin reflectance, the captured image is determined as suitable or not suitable for biometric identification. When the captured image is determined not suitable, a remedial capture setting is calculated and provided to an image capturing resource. Another captured image of the subject, captured under the remedial capture setting, is received from the image capturing resource. The relative skin reflectance of the another captured image is quantified and based thereon, there is a determining of whether the another captured image is suitable or is not suitable.

Skin reflectance image correction in biometric image capture

Systems and methods for secure distribution of biometric matching processing are provided. Certain configurations include homomorphic encrypting of captured biometric information. In some configurations, the biometric information is classified without decryption between a first identity class and a second identity class. The biometric information may be formed as a feature vector. A homomorphic encrypted feature vector may be formed by homomorphic encrypting of the biometric information.

Third party biometric homomorphic encryption matching for privacy protection

Collection, validation, accuracy checking, and matching of information for individuals, e.g., in-scope people entering/exiting a country is described. The systems, techniques, devices, methods, and approaches described herein can be used to collect biographic, biometric, and travel information for persons who enter a country with the expectation that the person will eventually exit. The system and method described herein include structures and procedures for determining whether the individual, based on his/her information, meets a predefined criterion that is associated with predefined procedures, e.g., special precautions are to be implemented. This document also describes how information for an individual can be matched with an existing record in order to ensure accurate recordkeeping.

Selective biometric access control

A system for generating a privacy protected image. The system may have a detection logic and obscuring logic configured to detect one or more identity-correlated object categories. The system may provide automatic selection of a type of obscuring to be used based on the detected category; wherein said automatic selection includes automatically selecting among a plurality of different, category specific types of reversible obscuring. The detection logic and obscuring logic may include an automatic category-specific selecting between irreversible obscuring and reversible obscuring. The system may comprise a privacy protected image output logic configured to generate the privacy protected image.

Growing community of inventors

North Bethesda, MD, United States of America

Arun Vemury