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.

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.

The present disclosure relates to a fingerprint identification method, device, an electronic apparatus and a storage medium. The fingerprint identification method includes: capturing a fingerprint by a fingerprint sensor, identifying matching pairs of minutiae between the captured fingerprint and a reference fingerprint; calculating a first matching result based on the minutia matching pairs; identifying minutia surrounding features for each minutia of the captured fingerprint in the minutia matching pairs; determining, for each minutia in the minutia matching pairs, whether the minutia surrounding features of the captured fingerprint match with minutia surrounding features of the reference fingerprint; calculating a second matching result based on the determination; and generating an identification result based on the first matching result and the second matching result.

A method and an apparatus for recognizing different users in a household without having the users to register or enroll their biometric features are provided. The apparatus may leverage sensors integrated with a remote control device or connected to a media device and create pseudo-identity of a user when the user is consuming the content services from media device. When pseudo-identity is created, user's content preference, user's viewing habit, and user's viewing behavior with respect to the content, may be associated with more than one pseudo-identity to better identify the same user. In subsequent usage, personalized services, such as personalized guide & programs, user-selected preferences, targeted advertisement, or content recommendation, may be provided by service provider to user in a subtle and natural manner.

Methods and systems for of generating reporting data in an automated, efficient, and risk-free fashion relating to an identification match relating to a probe image are disclosed. Methods include automatically capturing a comparison area in the probe image and a comparison area of a candidate image based on examiner input; facilitating a determination of whether a similarity or a dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image; automatically recording metadata based on the determination of whether the similarity or the dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image and updating an audit log; and generating a report comprising the metadata.

A fingerprint verification method includes selecting one or more first fingerprint groups from among a plurality of fingerprint groups based on an input fingerprint image, each fingerprint group of the plurality of fingerprint groups including partial fingerprint images; and determining whether verification is successful based on the input fingerprint image and each of the partial fingerprint images included in the one or more first fingerprint groups.

A method to authenticate a user by means of a fingerprint sensor, which is capable of simultaneously acquiring the fingerprints of a hand, the method comprising: an enrollment process (100), during which the features of first fingerprints (Ei) of the fingers of the hand are acquired (101-103), a variation model (Gij) indicating a plausible mutual position variation for each pair of first fingerprints (Ei, Ej) is determined (104) based on the respective features and stored (105); and a comparison process (200), during which features of successive fingerprints (Ei, Ej) of the fingers of the hand are acquired (201-203), a degree of similarity between each one of the first fingerprints (Ei) and each one of the successive fingerprints (Ck) is determined (204) based on a comparison of the respective features, a degree of plausibility of mutual position of pairs of fingerprints (<Ei, Cki>, <Ej, Ckj>) of a set (P) of pairs of fingerprints, each comprising one of the first fingerprints (Ei) and that of the successive fingerprint (Cki) offering the highest degree of similarity, is determined (207, 208) based on the features of the pairs of fingerprints and on the variation model (Gij) of the first fingerprints (Ei, Ej) of the pairs of fingerprints, the user is recognized (209-211) and the variation models (Gij) are updated (212) based on the degrees of similarity and on the mutual position plausibility degrees.

The present disclosure teaches a method of utilizing image “match points” to measure and detect changes in a physical object. In some cases “degradation” or “wear and tear” of the physical object is assessed, while in other applications this disclosure is applicable to measuring intentional changes, such as changes made by additive or subtractive manufacturing processes, which may, for example, involve adding a layer or removing a layer by machining. A system may include a scanner, and a digital fingerprinting process, coupled to an object change computer server. The server is coupled to a datastore that stores class digital fingerprints, selected object digital fingerprints collected over time, match measurements, and deterioration metrics.

Various example embodiments are directed to a fingerprint authentication method and a fingerprint authentication device. The fingerprint authentication method includes acquiring target fingerprint data of a user using at least one fingerprint sensor, determining a preliminary authentication result of the target fingerprint data based on at least one historical fingerprint data stored in memory, performing a matching check on the preliminary authentication result, and determining a final authentication result of the target fingerprint data based on results of the matching check.

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.