Abstract: A system constructs a block direction for a first print and compares the block direction image to a direction image for a second print to determine a similarity measure between the first and second prints. Constructing the block direction image includes: receiving a plurality of minutiae for the first print, with each minutia being associated with a location, a direction and a quality; and for each of the plurality of minutiae, assigning within the block direction image a plurality of corresponding neighboring blocks, and for each neighboring block determining a density rate that is a function of a distance from the neighboring block to the location of the corresponding neighboring minutiae, a block direction that is a function of the density rate and the direction of the corresponding neighboring minutiae, and a block quality that is a function of the density rate and the quality of the corresponding neighboring minutiae.

Abstract: A method for fingerprint record identification includes the steps of: assigning (200) a first number of fingers for a first matching stage and a second number of fingers for a second matching stage; performing (210) the first matching stage of comparing, based on the first number of assigned fingers, a search record to at least a portion of a plurality of file records and generating first matching results of a subset of the at least a portion of the plurality of file records; and performing (220) the second matching stage of comparing, based on the second number of assigned fingers, the search record to at least a portion of the subset and generating second matching results of one of: a strong hit; a weak hit; no hit; and a an ordered portion of the subset.

Abstract: A method is performed in a print identification system to segment a non-segmented slap print image into its finger components. The method includes: receiving, for a hand, a non-segmented slap print image and a corresponding plurality of roll print images each corresponding to a different finger number; comparing the roll print images to the non-segmented slap print image to determine a number of mated minutiae areas on the non-segmented slap print image; detecting a number of print components from the non-segmented slap print image using the plurality of mated minutiae areas; and selecting a number of final print components from the detected print components and assigning finger numbers to the final print components, using the plurality of mated minutiae areas.

Abstract: A system includes an interface receiving a search and file print and a processing device. The processing device performs a method that includes: performing at least one of a first comparison of quality of the search and file prints to a quality threshold, a second comparison of a minutiae matching score for the search and file prints to a minutiae matching score threshold, and a third comparison of a ridge distance of the search and file prints to a ridge distance threshold; determining that a phase correlation between the search and file prints is to be performed based on results of the at least one of the first, second and third comparisons; aligning the search and file prints and performing the phase correlation to calculate a phase correlation score; and modifying the minutiae matching score based on the calculated phase correlation score.

Abstract: A method for comparing a first print image having a first set of minutiae to a second print image having a second set of minutiae, wherein at least a second subset of minutiae from the second set is mated to a first subset of minutiae from the first set, the method that includes the steps of: selecting (350) a first pair of minutiae from the first subset and a second pair of corresponding mated minutiae from the second subset; generating (350) a first segment based on the first pair of minutiae and a second segment based on the second pair of minutiae; generating (360) a first cross-section profile based on the first segment and a second cross-section profile based on the second segment; and computing (365) at least one similarity measure that is indicative of the similarity between the first cross-section profile and the second cross-section profile.

Abstract: A print identification system performs the following: comparing a primary search print to each of a plurality of file print to generate a primary sorted match report having a first set of file IDs each associated with a first match score; applying a decision logic to the first match scores to determine a status of the corresponding file prints a strong match, a possible match or no match to the search print; for each file print identified as a strong match, compare that file print against file prints identified as a possible match or no match to generate a sub-match report including at least a portion of the first set of file IDs each associated with a second match score; and modifying the primary sorted match report based on at least one of the second match scores to generate a final sorted match report.

Abstract: A system includes an interface receiving a search print record including a first direction image of a search print and a file print record including a second direction image of a file print, and a processing device. The processing device performs a method and a computer-readable storage medium stores code for programming a computer to perform the method, which includes: aligning the first and second direction images to identify an overlapping and a non-overlapping area; comparing block direction between the first and second direction images within the overlapping area; performing a rationality analysis on the aligned direction images to at least determine whether one of the direction images and the non-overlapping area of the other direction image are from a different finger; and generating a similarity score based on the block direction comparison and the rationality analysis, which indicates a measure of similarity between the search and file prints.

Abstract: A method for level three feature extraction from a print image extracts features associated with a selected ridge segment using a gray-level image under the guidance of at least one binary image. The level three features are a sequence of vectors each corresponding to a different level three characteristic and each representing a sequence of values at selected points on a print image. The level three features are stored and used for level three matching of two prints. During the matching stage, ridge segments are correlated against each other by shifting or a dynamic programming method to determine a measure of similarity between the print images.

Abstract: A method for comparing a search print image comprising a first plurality of minutiae to a file print image comprising a second plurality of minutiae and the apparatus implementing the method is provided. The method includes the steps of: aligning the search and file print images; obtaining the first and second plurality of minutiae, a first plurality of pseudo-ridges generated from a first direction field of the search print image and a second plurality of pseudo-ridges generated from a second direction field of the file print image; for each aligning of the search and file print images, generating a pseudo-ridge score, and determining a minutiae matching score; and providing, based on the pseudo-ridge and minutiae matching scores, an output that indicates a level of similarity between the search and file print images.

Abstract: A method, apparatus and computer-readable storage element for determining quality of a print image, with the method including the steps of: estimating a centroid point of the physical print; setting dimensions of a quality computation frame based at least on a characteristic of the print image; centering the quality computation frame around the centroid point; determining, within the frame, a set of quality features; and computing a quality measure for the print image based on the set of quality features.

Abstract: Print image processing includes generating a first direction image and a multi-resolution hierarchy tree (MRT) having a plurality of direction measures, and adjusting at least one direction measure based on whether it is associated with a singularity area or a non-singularity area of the MRT, to output a final first direction image used for further print image processing. The MRT direction images include the first direction image having a highest resolution and at least one other direction image having a lower resolution. Each direction measure is determined from a direction measure, in a higher resolution direction image, which is selected based on image quality and distance from the boundary between print areas and non-print areas. Upon determining the final first direction image, a consistency measure can be computed and compared to a consistency metric and the method iteratively performed until the consistency measure satisfies the consistency metric.

Abstract: A method for use in print matching apparatus that includes the steps of: enrolling (200) a print of a user; extracting (210) a set of matching features from the enrolled print; comparing (220) the extracted features of the enrolled print to extracted features of each print in a set of reference prints, wherein each reference print in the set is from a person other than the user, and determining a highest non-matching score; determining (230) at least two minimum and maximum threshold pairs based on characteristics of the print matching apparatus; and storing (240) the matching features of the enrolled print, the highest non-matching score, and the at least two maximum and minimum threshold pairs for use in verifying a subsequently captured print of the user.

Abstract: A method for enrolling biometric images including the steps of: a) capturing (310) a plurality of images for a user into a capture folder; b) selecting (318) one of the plurality of images in the capture folder and removing the selected image from the capture folder to an enroll folder; c) comparing (322) the selected image to each of the remaining images in the capture folder to generate a corresponding similarity score for each of the remaining images; d) determining (326) whether any of the corresponding similarity scores are at least equal to a predetermined score threshold, and removing each image having a corresponding similarity score at least equal to the predetermined score threshold from the capture folder to a delete folder (330); and e) determining (334) whether there is at least one image in the capture folder and if so repeating steps b) through d).

Abstract: A method for comparing a first print image having a first set of minutiae to a second print image having a second set of minutiae, wherein at least a second subset of minutiae from the second set is mated to a first subset of minutiae from the first set, the method that includes the steps of: selecting (350) a first pair of minutiae from the first subset and a second pair of corresponding mated minutiae from the second subset; generating (350) a first segment based on the first pair of minutiae and a second segment based on the second pair of minutiae; generating (360) a first cross-section profile based on the first segment and a second cross-section profile based on the second segment; and computing (365) at least one similarity measure that is indicative of the similarity between the first cross-section profile and the second cross-section profile.