A sensor acquires the same type of biometric information from plural fingers in association with an ID. A processor generates feature data used for verification from the biometric information, and generates characteristic data used for calculation of similarity between the plural fingers from the biometric information. Next, the processor compares the characteristic data and calculates the similarity between the plural fingers. The processor determines whether the feature data is registrable based on the similarity, and a memory stores the feature data in association with the ID when the feature data is registrable.

In some aspects, the present disclosure provides a method for managing a command queue in a universal flash storage (UFS) host device. The method includes determining to power on a first subsystem of a system-on-a-chip (SoC), wherein the determination to power on the first subsystem is made by a second subsystem of the SoC based on detection of user identity data contained in a first image frame during an initial biometric detection process. In certain aspects, the second subsystem is configured to operate independent of the first subsystem and control power to the first subsystem. In certain aspects, the second subsystem includes a second optical sensor, a set of ambient sensors, and a second processor configured to detect, via a set of ambient sensors, an event comprising one or more of an environmental event outside of the device or a motion event of the device.

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.

The present disclosure relates to secure storage of a detailed set of elements relating to fingerprint features for a finger and to a method for authenticating a candidate fingerprint of a finger using said detailed set of elements, allowing for improved security and user convenience.

The present disclosure relates to a method and an apparatus for detecting pressure. The method includes: acquiring, via a fingerprint recognition sensor, a plurality of successive fingerprint images; recognizing sweat pores in the plurality of successive fingerprint images; determining a feature of the recognized sweat pores in the plurality of successive fingerprint images; and determining a changing trend of pressure applied on the fingerprint recognition sensor over time based on a changing trend of the feature of the recognized sweat pores across the plurality of successive fingerprint images.

A biometric recognition apparatus and fingerprint feature extraction method can automatically optimize parameters used for extracting a feature template from a biometric image. The biometric recognition apparatus includes: a teacher data generation unit that generates a genuine pair and an imposter pair of first and second biometric images; a learning data generation unit that uses a plurality of different temporary parameters to extract feature templates from the first biometric image and the second biometric image; and an optimum solution determination unit that calculates a score separation degree on the temporary parameter basis based on a first score representing a similarity degree of a pair of the feature templates extracted from the genuine pair and a second score representing a similarity degree of a pair of the feature templates extracted from the imposter pair and determines the temporary parameter based on a level of the score separation degree.

Disclosed is a system and method for rapid noise-robust friction ridge impression minutiae extraction from digital signal using fully convolutional feed-forward neural network. The proposed neural network based system outperforms classical approaches and other neural network based systems for minutiae extraction in both speed and accuracy. The minutiae extracted using the system can be used at least for tasks such as biometric identity verification, identification or dactyloscopic analysis.

A computer-implemented method for a gesture-based user interface and a gesture-based user interface system are described. The method comprises receiving image data from a multi-aperture image sensor in said electronic device, said image sensor being configured to simultaneously expose an image sensor to at least a first part of the electromagnetic (EM) spectrum using a first aperture and at least a second part of the EM spectrum using one or more second apertures; determining sharpness information in at least one area of said image data associated with at least part of an object imaged by said first aperture and said one or more second apertures onto the image plane of said image sensor; generating depth information on the basis of at least part of said sharpness information; and, recognizing on the basis of said depth information, at least part of a gesture associated with a movement of said object.

The present disclosure provides a fingerprint identification method and apparatus, a storage medium, and a terminal. The fingerprint identification method includes: collecting a to-be-identified fingerprint image of a to-be-identified fingerprint; identifying whether the to-be-identified fingerprint belongs to a first type of fingerprint; calculating an image correlation between the to-be-identified fingerprint image and a standard fingerprint image, when it's determined that the to-be-identified fingerprint belongs to the first type of fingerprint; calculating a feature point matching result between the to-be-identified fingerprint image and the standard fingerprint image when it's determined that the to-be-identified fingerprint does not belong to the first type of fingerprint; and determining whether the to-be-identified fingerprint is consistent with the standard fingerprint; wherein the standard fingerprint image is a fingerprint image collected from a standard fingerprint. The solution provided by the present disclosure can effectively improve the accuracy of fingerprint identification.

The present invention describes a method and the system for matching fingerprint images obtained from different fingerprint image capturing devices and implemented in an electronic device. Specifically, the method has steps of identifying minutiae and then identifying core point of the fingerprint images. Thereafter, a line of symmetry is determined and minutiae are identified by matching ridge count, location angle and orientation angle of a first image of the fingerprint images with a second image of the fingerprint images is identified. Thereafter, prominent minutiae from the candidate minutiae having three adjacent minutiae with same local structure are identified. Out of scope minutiae are eliminated by non-linear registration of fingerprint images based on ridge-count and position angle. Thereafter, matching score is generated based on number of candidate minutiae, prominent minutiae and common overlapped minutiae after non-linear registration of the second fingerprint image in comparison with the first fingerprint image for authentication.