Abstract: In some implementations, a method includes: receiving, from the camera, a sample image that includes a fingerprint and a mensuration reference device, where the sample image is associated with a resolution; identifying (i) a plurality of edge candidate groups within the sample image, and (ii) a set of regularity characteristics associated with each of the plurality of edge candidate groups; determining that the associated set of regularity characteristics indicates the mensuration reference device; identifying a ruler candidate group, from each of the plurality of edge candidate groups, based at least on determining that the associated set of regularity characteristics indicates the mensuration reference device; computing a scale associated with the sample image based at least on extracting a set of ruler marks from the identified ruler candidate group; and generating, based at least on the scale associated with the sample image, a scaled image.

Abstract: In some implementations, a computer-implemented method includes: obtaining a captured image including, (i) a latent fingerprint to be captured, and (ii) a template, surrounding the latent fingerprint, that contains plurality of symbols; extracting, using an image processing technique, one or more characteristics for each of the plurality of symbols; calculating a resolution for the captured image based at least on the extracted one or more characteristics for each of the plurality of symbols; generating a reconstructed desired image, based at least on (i) the calculated resolution of the captured image, and (ii) the one or more extracted characteristics for each of the plurality of symbols; and providing the reconstructed desired image to a fingerprint identification system to perform a particular fingerprint operation.

Abstract: A fingerprint matching system for fingerprint matching using virtual minutiae includes a fingerprint scanning device, including (i) an interface to a fingerprint scanner, and (ii) a sensor associated with the fingerprint scanner, configured to identify a match between a search fingerprint representing a fingerprint of a subject and a reference fingerprint from among a plurality of reference fingerprints representing fingerprints of a plurality of historical subjects; a database containing the plurality of reference fingerprints representing fingerprints of the plurality of historical subjects; and a computing device in communication with said database and said fingerprint scanning device.

Abstract: In one aspect, methods that use a novel representation, referred to as an octant feature vector (OFV), are used for matching distorted fingerprints. For instance, a feature-based matcher for distorted fingerprint matching may use a two-step local and global matching scheme to compare a set of feature vectors that are derived from minutiae of a reference fingerprint and a search fingerprint. The relative geometric relationships between the reference minutia and nearest minutiae may be derived and encoded into a feature vector based on orientation difference. The OFV is invariant to the rigid transformations and is insensitive to nonlinear distortions since the relative geometric relationships are independent from the rigid transformation.

Abstract: In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

Abstract: In some implementations, a computer-implemented method may include: identifying one or more neighboring minutiae within a particular octant neighborhood for the octant feature vector for each minutia included in a list of minutiae associated with a search fingerprint; computing, for each minutia included in the list of minutiae, a direction difference between each minutia included in the list of minutiae, and each of the one or more neighboring minutiae identified for the octant feature vector for each minutia included in the list of minutiae; computing, for each minutia included in the list of minutiae, a minutia quality confidence; and computing a fingerprint quality confidence.

Abstract: An automated digital processing system and method for characterizing the probability of a finger print match for at least one finger including a means for providing at least a plurality of match scores for at least one finger; a means for providing a finger index; a means for providing a number of fingers used in the search; a means for providing a number of times a finger index appears in a subset of probable matches; and a means for providing a number of records in the database. At least two record identification metrics are calculated and a means for calculating a match credibility metric of the calculated record identification metrics is provided based on a function of at least one of: the number of fingers used in the search, the first record identification metric, and the second record identification metric. A means for providing a user with at least one of the record identification metrics is further provided.

Abstract: A system and method for automated print identification is described. In particular, the method includes providing an active search record, arranging the prints of the active search record according to print quality to generate a filtered active file database, providing the filtered active file database as the input to a match algorithm, detecting a print correlation corresponding to a print contained in the active file database, determining if a print match has been made, determining the strength of a match if a print match has been made, and determining the active search file record to be added into the active database or the matched active file records to be updated.

Abstract: A system and a method for minutiae record matching is claimed that includes the processing a first plurality of ordered minutiae match values with weighting values corresponding to a function of at least the number of minutiae in the corresponding latent print and the corresponding print in the tenprint for a given unweighted match value to define a second plurality of weighted match values. The second plurality of weighted match values may be further normalized based at least on the highest unweighted match value to generated a third plurality of weighted match values.

Abstract: A system and a method for segmenting slap fingerprints is described. The method includes providing a print image, optionally pre-processing the print image, detecting at least a plurality of image components of the print image, determining at least one segmentation boundary for the print image, and computing the convex hull of the image components. The orientation, relative orientation and placement of the image components are detected. The zone lines of each component are found and zone areas are defined. The components under the top component of each zone are deleted. The finger numbers are assigned in accordance with the anchor print component, the geometrical relationship among the components. The slap print image is segmented in accordance with the segmentation boundary and its neighboring boundaries.

Abstract: A method for segmenting a fingerprint image having a plurality of pixel includes the steps of: estimating the direction (400) of at least a portion of the plurality of pixels to generate a directional image from said fingerprint image; determining (500) at least one foreground component image of the directional image; calculating (800) a vertical projection profile of the at least one foreground component image; calculating (800) a horizontal projection profile of the at least one foreground component image; determining (1000) a plurality of segmentation edges based on the vertical and horizontal projection profiles; and segmenting (1100) a region of the fingerprint image based on the plurality of segmentation edges, whereby the region is included within the segmentation edges.

Abstract: Fingerprint image processing methods for fingerprint security systems, for example, in wireless communications devices, including capturing fingerprint images (320), identifying features from images (330), matching the identified features with reference features (340), and providing access to the device based upon feature matching (350) results. In one embodiment, minutiae features are extracted from the image and matched to reference minutiae features.

Abstract: A system and a method for segmenting slap fingerprints is described. The method includes providing a print image, optionally pre-processing the print image, detecting at least a plurality of image components of the print image, determining at least one segmentation boundary for the print image, and computing the convex hull of the image components. The orientation, relative orientation and placement of the image components are detected. The zone lines of each component are found and zone areas are defined. The components under the top component of each zone are deleted. The finger numbers are assigned in accordance with the anchor print component, the geometrical relationship among the components. The slap print image is segmented in accordance with the segmentation boundary and its neighboring boundaries.

Abstract: A system and a method for minutiae record matching is claimed that includes the processing a first plurality of minutiae match values having a first ordered series with at least a second plurality of weighting values corresponding to a function of the number of minutiae matched for each minutiae match record to define a third plurality of weighted match values. The obtained weighted match value are sorted to provide a fourth plurality of weighted match values having a second ordered series. The inventive minutiae matching system is also described.

Abstract: An automated digital processing system and method for characterizing the probability of a finger print match for at least one finger including a means for providing at least a plurality of match scores for at least one finger; a means for providing a finger index; a means for providing a number of fingers used in the search; a means for providing a number of times a finger index appears in a subset of probable matches; and a means for providing a number of records in the database. At least two record identification metrics are calculated and a means for calculating a match credibility metric of the calculated record identification metrics is provided based on a function of at least one of: the number of fingers used in the search, the first record identification metric, and the second record identification metric. A means for providing a user with at least one of the record identification metrics is further provided.