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.

The present invention provides a matching result display device, a matching result display method, a program, and a recording medium, which allow, at the time of displaying feature points of objects determined as matching on the basis of matching result information provided by a matching system, visual check of the displayed feature points to be performed easily. The matching result display device according to the present invention includes: a feature point acquiring unit that acquires a plurality of feature points common to at least two pieces of image data to be matched against each other; a display position setting unit that sets display positions of corresponding symbols to be assigned to the feature points common to the at least two pieces of image data in such a manner that, when the same corresponding symbols are assigned to corresponding feature points, respectively, a display line connecting each feature point and the corresponding symbol assigned thereto on each of the at least two piece of image data does not overlap with display lines connecting other feature points and corresponding symbols assigned thereto, respectively; and a display unit that provides the corresponding symbols at the display positions and displays the feature points and the corresponding symbols assigned thereto in a state where they are connected with display lines, respectively.

Techniques for client side multi-factor password generation include randomly removing one or more features of a record of a fingerprint image of a user and creating a distorted record of the fingerprint image by merging the record with a user input code using an encryption technique, the distorted record being reversible using the user input code. The distorted record for authentication of the user is registered.

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.

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.

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 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.

An information processing apparatus includes: a memory; and a processor coupled to the memory and configured to: calculate a positional difference and a degree of similarity in feature value between each feature point in a verification image captured by an imaging device and each of a plurality of feature points in a registered image registered in advance; and match the verification image against the registered image by using the degree of similarity to a feature point having the degree of similarity that is second highest or lower for each feature point in the registered image in a case where a positional difference from a feature point having the degree of similarity that is highest in the verification image is greater than a threshold value.

Biometric recognition systems and methods are described, including a biometric recognition system including a user system with a biometric able to scan a finger and provide an image. From the image, a plurality of features may be extracted to create at least one fingerprint feature vector using a convolutional neural network.

A striped pattern image examination support apparatus includes a feature extraction part, a central line collation part, and a display part. The feature extraction part extracts, from each of a first striped pattern image and a second striped pattern image, at least central lines and feature points, as a feature of each of the first striped pattern image and the second striped pattern image. The central line collation part performs collation of the respective central lines of the first striped pattern image and the second striped pattern image, and computes corresponding central lines between the first striped pattern image and the second striped pattern image. The display part determines a display form of each of the central lines based on the computed corresponding central lines and superimposes and displays the central lines on each of the first striped pattern image and the second striped pattern image, according to the determined display form.