A fingerprint recognition method and electronic device are provided. The fingerprint recognition method includes the steps of obtaining first input data; generating a first waveform diagram corresponding to a first minutia of the first input data; obtaining second input data; generating a second waveform diagram corresponding to a second minutia of the second input data; and comparing the first waveform diagram with the second waveform diagram.

The invention provides a computing device for processing fingerprint template data, wherein the computing device comprises modules configured for generating transformed fingerprint template data from original fingerprint minutiae template data, in which minutiae are represented at least by Cartesian or polar coordinates and an inherent minutiae direction, the computing device being configured to generate for each minutia of the original fingerprint minutiae data corresponding mega-vicinity data. The computing device may further comprise a comparator module being configured to compare two transformed fingerprint template data that comprises, for each minutia, mega-vicinity data of a first fingerprint and a second fingerprint. The computing device may further comprise a biometrics-secret binding module for protecting.

A biometric authentication device includes a memory and a processor coupled to the memory, the processor being configured to execute a process, the process including: storing enrollment biometric information; determining the category of biometric information input in a biometric sensor; comparing input biometric information with each enrollment biometric information that is associated with a category determined in the determining with respect to the input biometric information; and associating, when a first comparison between the input biometric information and the each enrollment biometric information is failed and a second comparison between each enrollment biometric information that is associated with a category determined in the determining with respect to re-input biometric information and the re-input biometric information is succeeded, the each enrollment biometric information having achieved a success of the second comparison with the category determined with respect to the input biometric information.

To extract a fingerprint core for alignment of a fingerprint image for fingerprint matching. The present invention comprises: a core extraction unit which has an endpoint processing function of generating an endpoint image by extracting bifurcations in skeleton image and subjecting the respective bifurcations to endpoint processing; and a skeleton image generation/extraction unit which extracts skeletons of a density-inverted image formed by inverting the density colors of the generated end point image from white to black and vice versa, and performs processing for generating the skeleton image, the core extraction unit being provided with a core determination function of specifying a skeleton pixel having the highest value of a loop score indicating the degree of a bend in a skeleton shape in the density-inverted image, and defining this skeleton pixel as the finger print core.

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 list of possible mated minutiae in a reference fingerprint and a search fingerprint is identified. The list of possible mated minutiae is divided into different groups of mated minutiae using pose grouping based on rigid transformation parameters. For each group, the possible mated minutiae are filtered to get a set of consistent mated minutiae pairs having similar rigid transformation. The topological consistency between groups is determined. If any two groups are topologically consistent to each other, they are merged to form a (virtual) larger group. A non-linear transformation parameters are estimated from the mated minutiae in the merged group. The overall similarity of mated and non-mated minutiae in the overlapping area is determined after non-linear alignment of the two fingerprints, and the maximum similarity is output as the final similarity score between two fingerprints.

A ridge flow based fingerprint image quality determination can be achieved independent of image resolution, can be processed in real-time and includes segmentation, such as fingertip segmentation, therefore providing image quality assessment for individual fingertips within a four finger flat, dual thumb, or whole hand image. A fingerprint quality module receives from one or more scan devices ridge-flow—containing imagery which can then be assessed for one or more of quality, handedness, historical information analysis and the assignment of bounding boxes.

Various examples of systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. Fingerprint liveness may be determined by evaluating pixels of a fingerprint image to identify pores along a ridge segment of the fingerprint image. A circular derivative operator can be used to identify the pores. Liveness of the fingerprint can be determined based upon features of the identified pores.

A biometric system may include an ultrasonic sensor array, a light source system and a control system. Some implementations may include an ultrasonic transmitter. The control system may be capable of controlling the light source system to emit light and of receiving signals from the ultrasonic sensor array corresponding to acoustic waves emitted from portions of a target object in response to being illuminated with the light emitted by the light source system. The control system may be capable of performing a user authentication process that is based, at least in part, on the signals from the ultrasonic sensor array.

A finger guide device that positions a finger (or minutiae containing digit) of a human subject on a fingerprint sensor in a manner optimal for the data capture operation of authentication or identification of said subject wherein a relevant portion of the finger is in alignment with a sensor or scanner. The finger guide device may also be used for enrollment of the initial fingerprint data into the system. The device may contain an outer surface ridge which feels somewhat uncomfortable due to application of a high pressure per square inch on small areas of the finger when the finger is incorrectly positioned to encourage correct placement of the finger. The finger guide device may have a curved inside surface to contour to a wide variety of fingertip shapes and sizes, wherein the sides and front have shorter radii of curvature than the rearward portion of the finger guide device.