73 results about "Biometric system" patented technology

Facial Comparison Biometrics System: A facial comparison biometrics system, comprising a facial comparison biometrics server (4) and one or more devices (6) arranged to acquire a biometric video stream from a user. The facial comparison biometrics server (4) includes a configurator (8) arranged to issue an acquisition configuration to at least one device (6) and an analyzer (10) arranged to receive and process a biometric video stream from said at least one device (6) in response to an acquisition configuration and to return an injection attack indicator.The facial comparison biometrics server (4) is arranged to determine, for each acquisition configuration, at least one acquisition parameter condition chosen from the group comprising a zoom value, a sharpness value, an exposure value, a white balance value, and a color saturation value, to vary the value of at least one acquisition parameter condition in the acquisition configuration for which it was determined, to measure in the resulting biometric video stream at least one characteristic property of at least one acquisition parameter condition, and to return an injection attack indicator based on the measurement of at least one characteristic property. Fig. 1.

Embodiments described herein provide for a voice biometrics system execute machine-learning architectures capable of passive, active, continuous, or static operations, or a combination thereof. Systems passively and / or continuously, in some cases in addition to actively and / or statically, enrolling speakers as the speakers speak into or around an edge device (e.g., car, television, radio, phone). The system identifies users on the fly without requiring a new speaker to mirror prompted utterances for reconfiguring operations. The system manages speaker profiles as speakers provide utterances to the system. Machine-learning architectures implement a passive and continuous voice biometrics system, possibly without knowledge of speaker identities. The system creates identities in an unsupervised manner, sometimes passively enrolling and recognizing known or unknown speakers. The system offers personalization and security across a wide range of applications, including media content for over-the-top services and IoT devices (e.g., personal assistants, vehicles), and call centers.

The invention is in the area of biometric recognition. It relates to a biometric recognition system for recognizing a user from its hand comprising: a. projector for projecting light onto the hand of the user, b. a camera for recording an image of the hand, and c. a processor configured to i. extract features of the hand of the user for comparing them to reference features, ii. determine from the image if the hand is made of skin, and iii. generating a recognition signal based on the feature comparison and the skin determination.

The methods and system allow for the generation of a signcrypted biometric electronic signature token using a subsequent biometric sample after an enrollment of a biometric reference value in a biometric system. The signcrypted biometric electronic signature token involves simultaneous encryption and digital signature to protect the confidentiality. The system as described herein provides data integrity, origin authentication, and efficiency by performing encryption and digital signature simultaneously. The process allows a signcrypting party to enroll in a biometric service, sign a piece of data or content using a public key, that may be tied to a trusted anchor certificate authority, and submit a biometric sample. Subsequently, the relying party may validate the information on that piece of data or content to confirm the identity of the signcrypting party.

Systems and methods are disclosed for dual, simultaneous, single-session, proximity-based, secure authentication of a Digital Assisted Shopping (DAS) representative and a customer in an unsecured remote location. The method includes installing a mobile banking application on the customer's device and an enterprise application on the DAS representative's device, both with biometric verification. Proximity detection using Bluetooth Low Energy (BLE) initiates a secure session via push notifications. A secure communication channel is established through a secure local handshake, involving encryption key exchange and mutual authentication. The system exchanges data related to customer profiles and financial accounts, continuously monitors geolocation using GPS, Wi-Fi, and cellular data, and performs periodic background biometric re-verifications. AI / ML algorithms analyze customer data to propose financial products and services, which are securely shared with the customer for review and selection. The system facilitates real-time enrollment and transaction processing, terminating the session upon detecting security breaches.

An enrollment assistance device comprising a carrier with a first surface portion for a user device, and a second surface portion for a contactless smartcard; a first wireless power transfer arrangement supported by the carrier and arranged in the first surface portion of the carrier; a second wireless power transfer arrangement supported by the carrier and arranged in the second surface portion of the carrier; and a conductor arrangement supported by the carrier and conductively connecting the first wireless power transfer arrangement and the second wireless power transfer arrangement.

In a biometric identification system, a transparent body can have a curved platen surface. The curved platen surface can be removably contacted by an anatomy of a user. The anatomy can have an anatomical pattern. An illumination source can illuminate the curved platen surface with an illumination beam. The illumination beam can propagate away from the curved platen surface as a return beam having a beam pattern shaped to correspond to the anatomical pattern. An imaging lens can focus the return beam to form a real image of the beam pattern at an image location. Field-curvature-correcting sensor optics can include a sensor. The sensor can sense the real image of the beam pattern at the image location. The field-curvature sensor optics can include a planar sensor and an image-flattener lens. The field-curvature sensor optics can include a curved, convex sensor.

An improved context-aware security system may include an artificial intelligence (Al) reasoning security system. The context-aware security system may be configured to receive security input data from a plurality of input sources, generate a contextual security analysis, identify a security response, and send instructions to a security system output device to execute the security response. The context-aware security system may include a plurality of security input sources configured to provide security inputs and contextual data, including credential readers, physical access controllers, security sensors, environmental sensors, or external information sources. The context-aware security system may include a directive input subsystem configured to receive security directives from an authorized user interface. A plurality of security system output devices may be configured to execute the security response, including credential reading systems, biometric systems, alerting systems, logging systems, or notification systems.

The present disclosure provides a biometric scanning system for generating an image of a user's vasculature. The biometric scanning system comprises a wrist-worn scanning device including NIR sensors for diffuse optical tomography, NIR LEDs, and an NIR camera configured to receive light emitted by the NIR LEDs after having passed through the user. The system processes vascular data collected by the NIR camera and / or the NIR sensors to generate a key corresponding to the user. In conjunction with access control systems, the biometric scanning system facilitates reliable user authentication without storing a root template of that user's vasculature.

A method of a biometric recognition system of performing real-eye detection and associated biometric recognition system are disclosed. The method comprises capturing at least one image comprising a representation of an eye of the individual, which image is captured utilizing polarized light reflected at the eye and received at a polarization-sensitive camera capturing said image, wherein a polarization configuration is selected which produces an iso-chrome pattern of the representation of the eye in the captured image, detecting, from the representation, birefringent features of a cornea of the individual, aligning the detected birefringent cornea features with birefringent cornea features of an expected eye representation, determining, by matching the detected birefringent cornea features with the expected birefringent cornea features, whether the birefringent features are correctly rendered in the captured image, and if so determining that the eye is a real eye.

In various embodiments, enhancements for low-touch biometric systems include obtaining winnowing information when a biometric probe unsuccessfully matches against a subset gallery. The winnowing information is used to obtain biometric data from an associated group of people and the biometric probe is then compared against the biometric data. If this also fails, identity information may be obtained and used to obtain a corresponding biometric template to match the biometric probe against. In some embodiments, enhancements for low-touch biometric systems determining a dominant by selecting the largest live face in an image then performing one or more actions using the dominant. Such one or more actions may include selecting the dominant for capture, performing exposure control and / or gain control on the dominant as opposed to the rest of an image, determining guidance to provide for biometric capture based at least on a position of the dominant, providing such guidance, etc.

User enrollment to a biometric identification system begins with a pre-enrollment process on selected general input devices (GID) such as smartphones. The user may enter identification data such as their name and use a camera of the GID to acquire first image data, such as of their hand. The first image data is processed to determine a first representation. Upon presentation of a hand at a biometric input device, second image data is acquired. The second image data is processed to determine a second representation. If the second representation is deemed to be associated with the first representation, the enrollment process may be completed by storing the second representation for subsequent use.

This specification describes systems and techniques related to spatially configurable localized illumination for biometric authentication systems. In one aspect, during biometric authentication, a biometric authentication system having a biometric authentication manager (104) is configured to receive a user input (110) at a touch-sensitive display (106). In response to and based on the user input (110), the biometric authentication manager (104) determines a shape of a contact area of ​​the user input (110) on the touch-sensitive display (106). Based on the determined shape, the biometric authentication manager (104) alters the brightness of an area of ​​the display (106) to increase light reflection from the user input (110), which is effective to facilitate biometric authentication.

User enrollment in a biometric identification system begins with a pre-enrollment process on a selected generic input device (GID), such as a smartphone. The user enters identifying data, such as their name, and may use the GID's camera to capture first image data, such as of their hand. The first image data is processed to determine a first representation. Upon presenting the hand at the biometric input device, second image data is captured. The second image data is processed to determine a second representation. If the second representation is deemed associated with the first representation, the enrollment process may be completed by saving the second representation for later use.

In a biometric identification system, a transparent body can have a curved platen surface. The curved platen surface can be removably contacted by an anatomy of a user. The anatomy can have an anatomical pattern. An illumination source can illuminate the curved platen surface with an illumination beam. The illumination beam can propagate away from the curved platen surface as a return beam having a beam pattern shaped to correspond to the anatomical pattern. An imaging lens can focus the return beam to form a real image of the beam pattern at an image location. Field-curvature-correcting sensor optics can include a sensor. The sensor can sense the real image of the beam pattern at the image location. The field-curvature sensor optics can include a planar sensor and an image-flattener lens. The field-curvature sensor optics can include a curved, convex sensor.

Systems and methods for a projected dielectric sensor comprising a first conductive path with a first conductive mesh, a second conductive path with a second conductive mesh, and a dielectric gap between them. The dielectric gap functions as an open circuit in a resting state, offering a broader detection range compared to traditional sensors. The sensor includes a power drive connected to the first conductive path and a collector connected to the second conductive path. The first and second conductive meshes include sheets that are positioned longitudinally side-by- side, enhancing sensitivity and simplifying manufacturing. In an example, the sheets are separated by at least 10 cm of dielectric material. The sensor can detect off-axis objects such as conductors, vehicles, humans, and baby seats, making it suitable for various applications including vehicle safety, biometric systems, gesture and mid-air control, and machine learning integration.

A system performs mobile biometric identification system enrollment using a known biometric. The system receives a digital representation of a first biometric for a person. Prior to using the digital representation of the first biometric to identify the person, the system compares a received digital representation of a second biometric for the person to known biometric data for the person. When the digital representation of the first biometric has been thus verified, the system is operative to identify the person using the digital representation of the first biometric.

Provided herein are systems and methods for authenticating a customer for a completing different types of restricted transactions. More specifically, provided herein are biometric authentication systems and processes for completing transactions where the goods and services at issue are subject to one or more transaction conditions, such as age-related restrictions. The systems described herein involve a point-of-interaction device that facilitates biometric authentication by obtaining and verifying an individual's biometric information, such as fingerprints, palm prints, or facial scans. This biometric data is then used to determine whether the individual meets the necessary conditions for the restricted transaction, such as age verification. The system aims to enhance security and efficiency in transactions by eliminating the need for physical cards and reducing the risk of fraud.

The technologies discussed herein relate to a biometrics system comprising one or more processors, computer storage memory having computer-executable instructions, surgically implantable devices, and wearables (e.g., an apparel item configured for an upper torso, an apparel item configured for a lower torso, a sock, a headband, other types of wearables, or one or more combinations thereof) having one or more biometric sensors (e.g., a heart rate sensor, a sweat sensor, a glucose sensor, other types of biometric sensors, or one or more combinations thereof) and one or more sensation devices (e.g., a plurality of visible light sources, a haptic feedback device, other types of sensation devices, or one or more combinations thereof). The wearables may also include one or more environmental sensors. The wearables emulate, transmogrify, or enhance one or more human senses using the one or more sensation devices based on biometric data or environmental data received.

A biometric identification system uses inputs of a user that are acquired using different modalities. A model having an intersection branch is trained to determine an embedding using features present in two or more modalities (an intersection of modalities). A first input acquired using a first modality is processed by the model to determine a first embedding. A second input acquired using a second modality is also processed by the model to determine a second embedding. Comparison of the first embedding and the second embedding may be used to determine if the first input and the second input are associated with the same user.

Face recognition method comprising, in an enrollment phase, capturing a biometric feature e.g. face of user / s uE, and / or extracting therefrom a biometric template for the user, and / or extracting a hash-value from the template and / or deriving a value more stable and / or more deterministic and / or less noisy than the template; and / or hashing and / or saving this value e.g. as hashed and / or subsequently processing a user uL alleging s / he is uE by comparing this value as saved to a value derived from a biometric feature e.g. face captured from user uL.

Systems and methods in accordance with the present disclosure relate to a system to perform automated consent processing for the collection of biometric data. The system can maintain rules associated with a zone within a field of view of the camera system. The system can detect, using image recognition techniques, that an entity has entered the zone. The system can determine if the entity has provided consent for the collection of biometric data within the zone. The system can request the consent according to the rules. The system can collect the biometric data according to at least one of the rules or the consent received from the entity.

A nanocomposite proximity-pressure sensor (NPPS), configured to measure one or more human biometrics, the NPPS including a carbon nanotube-paper (CPC) electrode, a multiwalled carbon nanotubes (MWCNTs) foam, and an auxetic MWCNTs-embedded frame, wherein the auxetic MWCNTs-embedded frame is positioned around the MWCNTs foam, wherein when the auxetic frame is compressed, it expands and exerts a pressure onto the MWCNTs foam.

The present disclosure provides techniques and apparatus for capturing an image of a person's retina fundus, identifying the person, accessing various electronic records (including health records) or accounts or devices associated with the person, determining the person's predisposition to certain diseases, and / or diagnosing health issues of the person. Some embodiments provide imaging apparatus having one or more imaging devices for capturing one or more images of a person's eye(s). Imaging apparatus described herein may include electronics for analyzing and / or exchanging captured image and / or health data with other devices. In accordance with various embodiments, imaging apparatus described herein may be alternatively or additionally configured for biometric identification and / or health status determination techniques, as described herein.

A method is provided for determining correctives to statistical identification variances of a biometric identification system using facial and / or pedestrian recognition. The method includes (a) defining a set of categories, each category having at least one corresponding physical appearance characteristic; (b) extracting, for each individual, at least one physical appearance characteristic from at least one image of the individual; (c) assigning, to each individual, at least one category on the basis of the extracted physical appearance characteristic; (d) distributing, for each category, each individual into two groups according to the failure or success of their identification by the system; and (e) calculating, for each category, a number of individuals to be selected in the group corresponding to the success of the identification such that the relative proportions of individuals in the group corresponding to the failure of the identification are substantially equal between all the criteria relating to said category.

Provided is a method for securing a biometric recognition of a user to be recognized against one or more templates and a non zero integer, corresponding to registered users identities, using a biometric sample of said user, in a biometric recognition system comprising a plurality of computation devices, a global scoring computation device and a recognition device. Each of said templates is split, using an additive splitting modulo a predetermined integer N, into a plurality of template shares stored in said computation devices, with i in [0, n−1] and n a non zero integer. A global scoring is computed for said at least one template by combining said shares of the global scoring computed for said template by said plurality of computation devices according to a formula. Other embodiments disclosed.

The invention discloses a digital tool management method for an electric power warehouse, and the method comprises the following steps: S1, recording tool basic information through an RFID tag, inputting personnel information through a biological recognition system, generating a unique identity identification code, and achieving the digital management of tools and personnel; s2, deploying an intelligent access control system combined with AI face recognition at the entrance of the warehouse, automatically verifying the identity of a person, recording the entering and exiting time, and binding tool information to realize the automation of a tool receiving process; s3, a return detection point is configured, the return state of the tool is monitored through RFID scanning, and reminding and access control limitation are carried out on the tool which is not returned; s4, analyzing tool use behaviors based on an artificial intelligence algorithm, calculating abnormal scores, identifying high-risk users and limiting permissions; s5, performing multi-level reminding by the tool for overdue return, and exciting timely return through an integral reward mechanism; and S6, generating a tool use efficiency report through algorithm optimization and data analysis, and providing support for a management strategy.

A biometric identification system processes input data acquired by input devices to determine embeddings used to identify a user. Different types of input devices or hardware configurations of input devices may produce different output. Each hardware configuration may be associated with respective representation data. A set of transformer networks are used to transform an embedding from one representation data associated with a first type of device or hardware configuration to another. This enables user participation via different configurations of hardware without requiring users to re-enroll for different input devices or hardware configurations. Opportunistic updates are made to the embeddings as embeddings native to a particular configuration of hardware are acquired from the user.

This application provides a biometric system for complex scenarios, relating to the field of biometric technology. By setting up multiple cameras that can be deployed in any area of ​​the monitoring site, the system allows for flexible adjustment of the camera's installation position and number based on the actual layout of the complex scenario and the key monitoring areas. This achieves full coverage of the monitoring site without blind spots, reducing reliance on manual inspections and solving the monitoring challenges of multiple and irregular areas in complex scenarios. It is suitable for rodent monitoring needs in various complex scenarios such as warehousing, agriculture, and urban public facilities. By accessing the video streams from multiple cameras through an edge computing device and running an AI visual analysis model locally, the system enables real-time local analysis of the video streams and identification of specific organisms (mice). This eliminates the need to upload all video streams to the cloud, reducing network bandwidth consumption and mitigating transmission latency issues caused by centralized cloud processing.

The invention discloses a multi-modal biological recognition fusion system, which comprises a multi-modal data acquisition engine, a dynamic cross validation engine and an identity label generation module, and the multi-modal data acquisition engine, the dynamic cross validation engine and the identity label generation module are connected with the dynamic cross validation engine and the identity label generation module. The feature level fusion module is used for realizing dynamic weight distribution and feature level fusion by integrating multi-dimensional biological features such as fingerprints, human faces, irises and voiceprints, and constructing a unique identity binding architecture in a high-security scene; according to the method, the technical bottlenecks of a traditional biological recognition system in the aspects of security boundary, environmental adaptability and anti-attack ability can be broken through by constructing a multi-modal feature dynamic fusion framework and creatively integrating the generative adversarial network, federated learning and edge computing optimization technologies.