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.

A synthesizing apparatus comprises: an input part that inputs a plurality of feature point sets that are respectively extracted by a plurality of methods from an input image having a curved stripes pattern formed by ridges; and a synthesizing part that synthesizes the plurality of feature point sets by executing a logical operation on the plurality of feature point sets. The synthesizing part can execute a logical OR operation on the plurality of feature point sets. The synthesizing part can also execute a logical AND operation on the plurality of feature point sets.

A computer-implemented method for generating a representation for a fingerprint includes receiving, by a computer processor, an image of a given fingerprint. The method extracts particular attributes for the given fingerprint from the image using a first neural network. The first neural network is trained to identify particular attributes in fingerprints and constructs a first feature vector from the extracted particular attributes, where the first feature vector has a first fixed length. The method includes extracting textural features of the given fingerprint from the image using a second neural network, where the second neural network is trained to identify textural features that are not limited to particular attributes and constructing a second feature vector from the extracted textural features, where the second feature vector has a second fixed length. The method includes concatenating the first feature vector with the second feature vector to form a representation for the given fingerprint.

The present invention generally relates to a method for transitioning a device controller comprised with an electronic device from an at least partly inactive mode to an at least partly active mode, the electronic device further comprising a pre-processing module and a fingerprint sensor configured to acquire image data. The invention also relates to a corresponding electronic device and to a computer program product.

The present application concerns the visual identification of materials or documents for tracking or authentication purposes. It describes methods to automatically authenticate an object by comparing some object images with reference images, the object images being characterized by the fact that visual elements used for comparison are non-disturbing for the naked eye. In some described approaches it provides the operator with visible features to locate the area to be imaged. It also proposes ways for real-time implementation enabling user friendly detection using mobile devices like smart phones

A synthesizing apparatus comprises: an input part that inputs a plurality of feature point sets that are respectively extracted by a plurality of methods from an input image having a curved stripes pattern formed by ridges; and a synthesizing part that synthesizes the plurality of feature point sets by executing a logical operation on the plurality of feature point sets. The synthesizing part can execute a logical OR operation on the plurality of feature point sets. The synthesizing part can also execute a logical AND operation on the plurality of feature point sets.

A method for fingerprint enrollment according to an embodiment includes extracting fingerprint feature points of a fingerprint image, fragmenting the fingerprint image in units of each fingerprint feature point, to obtain a feature fragment corresponding to each fingerprint feature point, and determining, according to whether the feature fragment meets an enrollment condition, whether the fingerprint enrollment is completed. Each fingerprint image can be fully utilized, so that the count of presses on the fingerprint sensor by a user of fingerprint enrollment is reduced, and the enrollment experience of the user is improved.

Provided are an information processing apparatus, an information processing method, and a storage medium capable of acquiring feature information relating to sweat gland pores that can realize highly accurate identification of an individual. The information processing apparatus includes: a sweat gland pore extraction unit that extracts sweat gland pores from an image including a skin marking; and an information acquisition unit that acquires sweat gland pore information including position information about the sweat gland pore and directional information about the sweat gland pore for each of the sweat gland pores.

Provided is a method for determining a match between a candidate fingerprint and a reference fingerprint characterized by minutiae local features. The method includes extracting several minutiae from the candidate fingerprint, computing from said extracted minutiae a plurality of minutiae local features of the candidate fingerprint, computing a first global matching score between the candidate fingerprint and the reference fingerprint based on the first similarity scores of said matching local feature pairs; computing a second global matching score between the candidate fingerprint and the reference fingerprint based on said computed second similarity scores; and determining a match between the candidate fingerprint and the reference fingerprint comprising: comparing the first and second global matching scores and, comparing the first matching score to a matching threshold. Other embodiments disclosed.

A minutia features generation apparatus comprises: an input part to input an image formed as a curved stripe pattern by a ridge line(s); a generation part to generate a skeleton image formed by extracting a skeleton(s) from the image; an extraction part to extract a plurality of minutiae from the skeleton image; and a calculation part configured to calculate a relation minutia feature(s) representing relationship between a first minutia and a second minutia among the plurality of minutiae, wherein the calculation part calculates as one of the relation minutia features defined by a crossing count of the skeleton(s) and a straight line connecting from the second minutia to a nearest neighbor point which is a point on a trace line traced by tracing starting from the first minutia, which point is located at a shortest line distance from the second minutia.