An electronic device with a display and a fingerprint sensor displays a fingerprint enrollment interface and detects, on the fingerprint sensor, a plurality of finger gestures performed with a finger. The device collects fingerprint information from the plurality of finger gestures performed with the finger. After collecting the fingerprint information, the device determines whether the collected fingerprint information is sufficient to enroll a fingerprint of the finger. When the collected fingerprint information for the finger is sufficient to enroll the fingerprint of the finger, the device enrolls the fingerprint of the finger with the device. When the collected fingerprint information for the finger is not sufficient to enroll the fingerprint of the finger, the device displays a message in the fingerprint enrollment interface prompting a user to perform one or more additional finger gestures on the fingerprint sensor with the finger.

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.

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.

Provided are an information processing apparatus, an information processing method, and a storage medium capable of drawing a fine ridge line with high accuracy. The information processing apparatus includes: an information acquisition unit that acquires sweat gland pore information including position information about a sweat gland pore extracted from an image including a skin marking and directional information about the sweat gland pore for each of the sweat gland pores; and a ridge line drawing unit that draws a quasi ridge line based on the sweat gland pore information.

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.

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 of enrolling an authorised user onto a biometrically-authorisable device having an on-board fingerprint sensor. The method including capturing a representation of a fingerprint of the authorised user using a fingerprint sensor on an enrolment terminal that is separate from the biometrically-authorisable device, the fingerprint sensor of the enrolment terminal being larger than the fingerprint sensor of the biometrically-authorisable device, generating a number of fingerprint templates from the captured fingerprint representation, wherein each fingerprint template defines an area of the fingerprint corresponding to the size of the fingerprint sensor of the biometrically-authorisable device, and transmitting the fingerprint templates for storage on the biometrically-authorisable device.

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.