20 results about "Minutiae" patented technology

A system and a method for verifying authenticity of a physical copy and a digital copy of a document are disclosed. The method comprises registering a document in a repository by storing details related to the document in a location of the repository. A symbology for the document is generated. The symbology is an identifier of the location of the repository comprising the document. The symbology is associated with either a physical or a digital copy of the document. The digital copy of the document is printed to generate a printed copy. The printed copy or the physical copy of the document is scanned to generate a scanned image. The document and the details related to the document present at the location of the repository are accessed. The scanned image is compared with the document stored in the repository to determine the authenticity of either the physical copy or the digital copy of the document.

The present invention discloses a fingerprint recognition method based on the fusion of global features and local minutiae features. The present invention comprises the following steps: (1) batch image input and preprocessing; (2) feature extraction using a CvT model network; (3) obtaining minutiae information of the fingerprint image using a CNN convolutional neural network; (4) performing minutiae screening on the obtained minutiae score map by setting a threshold, and finally obtaining minutiae information; (5) performing a test, and performing image similarity evaluation on the trained student network using the obtained global feature map and minutiae information. The present invention aims to achieve high-precision fingerprint recognition by realizing the complementarity of global and local fingerprint information through the fusion of fingerprint global features and minutiae local features.

This application relates to a fingerprint minutiae feature map encoding and retrieval method based on SimCLR. The method includes: obtaining a fingerprint minutiae visualization image from fingerprint minutiae data, training a feature map encoding model based on the SimCLR model framework with the image training set of the fingerprint minutiae visualization image to obtain a trained image encoder, then obtaining a fingerprint minutiae visualization image from the fingerprint minutiae data of the fingerprint to be retrieved, inputting it into the trained image encoder to obtain a query image encoding, comparing it with the image encodings of the fingerprint minutiae data in the database, and screening out the fingerprints in the database that may have the same relationship with the fingerprint to be retrieved. The present invention can reduce the image storage features, reduce the interference of redundant information, quickly and accurately screen out most of the images in the database that clearly do not have the same relationship with the query fingerprint image, and greatly shorten the retrieval time of the database.

The application discloses a high-low precision mixed multi-dimensional feature fusion fingerprint retrieval method. The method comprises the following steps: pre-processing minutia point data and constructing a fingerprint minutia point image; constructing an ORB fast fingerprint retrieval model based on multi-dimensional feature fusion; locating and correcting the fingerprint image detail feature points, and integrating multi-dimensional features such as direction angle and response size; generating feature point descriptors through scale pyramid transformation, center and direction angle calculation, extraction of binary descriptors and filtering of low correlation pixel blocks; matching the fingerprints by using the feature point descriptors; and for the higher precision fingerprint screening requirement, a rotation translation transformation difference method is proposed to improve the accuracy. The method has the beneficial effects that the matching and retrieval problem of the fingerprint minutia points is converted into the matching and retrieval problem of the image feature points, large-scale fingerprint retrieval is performed under the setting of low space-time complexity, and an improved strategy is proposed to realize high-low precision mixed fingerprint retrieval.

The present invention discloses a large-scale fingerprint retrieval method based on point cloud registration, which can efficiently and accurately retrieve the input fingerprints to be retrieved and obtain the fingerprint library sample set most likely to have an "identical" matching relationship. The overall solution can be divided into three levels: a preliminary screening level, a fine registration level, and a robust optimization level. The three levels are interdependent, processed serially, screened layer by layer, and none of them can be missing, jointly constituting a complete fingerprint retrieval algorithm. After inputting the fingerprints to be retrieved, the preliminary screening level uses global features to complete a rapid large-scale preliminary screening. The fine registration level uses local registration to achieve further screening and provides the matching relationship between minutiae points for the robust optimization level. The robust optimization level judges the correctness of the minutiae point matching relationship according to geometric consistency test and the maximum clique algorithm, and outputs the retrieval result using the comprehensive matching score.

The invention discloses a partial fingerprint identification method based on multistage feature fusion, and relates to the field of image processing and mode identification, and the method comprises the steps: carrying out the preprocessing of an input fingerprint image, and obtaining a preprocessed fingerprint image; based on the preprocessed fingerprint image, first-level curvature features, second-level minutia features and third-level ridge line shape features are extracted; retrieving and classifying the fingerprint template library through the first-level curvature features to obtain a candidate fingerprint set; on the basis of the candidate fingerprint set, performing minutia point matching and ridge line shape matching through the second-level minutia point features and the third-level ridge line shape features to obtain minutia point matching scores and ridge line shape matching scores; and calculating a final matching score in combination with adaptive weight fusion to obtain a fingerprint matching judgment result. According to the method, the efficiency and precision of partial fingerprint identification and the adaptability to images with different qualities are improved by fusing multi-level features such as curvature, minutiae and ridge line shapes and adopting an adaptive weighting strategy.

A method for detecting finger forgery attacks based on OCT volume data, comprising: detecting the number of minutiae of internal and external fingerprints and the number of subcutaneous sweat glands; setting the minutiae number thresholds num1, num2, the sweat gland number threshold num3, the internal and external fingerprint matching score threshold t, and the coincidence rate n between the position of subcutaneous sweat glands and the internal fingerprint ridge lines; if the number of internal fingerprint minutiae is more than num1 and the number of external fingerprint minutiae is more than num2, then calculate the internal and external fingerprint matching score; if the number of internal fingerprint minutiae is less than num1, directly determine it as a finger forgery attack; if the number of sweat glands is less than num3, directly determine it as a finger forgery attack; if the number of sweat glands is more than num3, if the internal and external fingerprint matching score is higher than t, the system directly passes the detection; if the number of sweat glands is less than num3 and at the same time the number of internal fingerprint minutiae is less than num1, enter the next step; calculate the coincidence rate between the position of subcutaneous sweat glands and the internal fingerprint ridge lines; if the coincidence rate is higher than the set value n, pass the detection, otherwise determine it as a finger forgery attack.

A method and apparatus for verifying a ridge line in a fingerprint image are provided. The method comprises the steps that a middle pixel in pixels on a connecting line of a first pixel and a second pixel is determined, and the first pixel and the second pixel are intersection point pixels of the connecting line between the ridge line and two detail feature points in the fingerprint image at the edge of the ridge line; and determining whether the ridge line corresponds to an actual ridge line based on pixels from the middle pixel in a first direction and / or pixels from the middle pixel in a second direction, the first direction and the second direction being two opposite extension directions of the ridge line.

The present application relates to the fingerprint identification technical field, especially a kind of fingerprint image periodic noise removal method, device and computer readable storage medium, the present application is directed to fixed period, random phase's fingerprint periodic noise, by pre-acquiring noise period and in the frequency domain only acts on fixed frequency point, not with the phase change trap wave filter mask, realize the phase robust noise stable suppression, while accurate keep ridge and minutia, with the advantages of low computational complexity, adapt embedded terminal, improve the identification accuracy of low-quality fingerprint image and robustness.

The application discloses a method for reducing fingerprint identification and forgery by using ORB image local features, comprising the following steps: S1, extracting minutia points of a to-be-matched fingerprint image; S2, marking a region around the minutia points of the to-be-matched fingerprint image, and extracting ORB key points of the marked region; S3, calculating minutia point pairs of the to-be-matched fingerprint image, and judging whether the calculated minutia point pairs are within a preset minutia point pair range; if not, the to-be-matched fingerprint image fails to match; if yes, step S4 is performed; S4, matching the ORB key points of the to-be-matched fingerprint image according to the calculated minutia point pairs, and judging whether the number of the matched ORB key points is greater than or equal to a preset ORB key point matching number; if not, the to-be-matched fingerprint image fails to match; if yes, step S5 is performed; and S5, the to-be-matched fingerprint image succeeds in matching.

The present invention provides a fully automatic fingerprint minutiae feature extraction method and system, including: Step S1: forming a fingerprint minutiae extraction network D based on fingerprint prior knowledge and a fingerprint minutiae prediction network; Step S2: preprocessing a fingerprint image to obtain a preprocessed fingerprint image; Step S3: training the fingerprint minutiae extraction network D with the preprocessed fingerprint image to obtain a trained fingerprint minutiae extraction network D; Step S4: preliminarily predicting a fingerprint minutiae point set with the trained fingerprint minutiae extraction network D; Step S5: eliminating fingerprint redundant points from the preliminarily predicted fingerprint minutiae point set by applying non-maximum suppression based on the general intersection over union to obtain a final accurate fingerprint minutiae point set.

The embodiment of the application provides a kind of based on optimal transmission's fingerprint minutia matching method and device.The method includes: obtaining the minutia set of first fingerprint and second fingerprint, and constructs the node feature including position, direction and local structure information;Based on node feature, the matching cost function considering embedding similarity, spatial distance, direction consistency and minutia quality is established, and the minutia matching cost matrix is formed;On the basis of the cost matrix, introduce absorption bucket mechanism to process missing or false minutia, construct extended optimal transport model, and adopt iterative normalization algorithm to solve optimal transport matching matrix;Finally, according to the matching matrix, the fingerprint similarity score is calculated and the matching result is output.The application can effectively overcome the comparison problem of incomplete and deformed fingerprints, improve the accuracy and robustness of on-site fingerprint identification.

Systems and methods for encoding data in a machine-readable image (e.g., an artificial fingerprint) are disclosed. The methods include segmenting a plurality of bits included in a bit stream to be encoded into a plurality of blocks such that each block includes two or more of the plurality of bits. The plurality of blocks are used to generate a minutiae template comprising a plurality of minutiae points each of which is representative of a local ridge discontinuity in a fingerprint, and is associated with a location and an orientation. An artificial fingerprint is generated from the minutiae template, and stored in association with the bit stream. The artificial fingerprint encodes the bit stream and comprises a plurality of ridges and a plurality of valleys.

The application discloses a fingerprint minutia point marking method and device and electronic equipment, and the method comprises the following steps: acquiring a to-be-marked fingerprint image, and searching for a marked fingerprint image of the same finger from a preset fingerprint image database according to finger information of the to-be-marked fingerprint image; mapping the minutia point information that has been marked in the marked fingerprint image to the to-be-marked fingerprint image; generating a new marked fingerprint image based on the mapped to-be-marked fingerprint image, and storing the new marked fingerprint image in the fingerprint image database. The technical scheme provided by the application can improve the efficiency and accuracy of fingerprint minutia point marking.

A fingerprint recognition system for recognizing fingerprints includes a processor operatively configured for executing digital instructions, and digital storage media operatively connected to the processor and configured for storing instructions configured for directing the processor to carry out the steps of enhancing at least one or more fingerprint images, extracting minutia features from the enhanced fingerprint images, and encoding the fingerprint extracted minutia features as a digital fingerprint.

The application discloses a kind of based on optical coherence tomography's fingerprint extraction method and related equipment, comprising: by the mode of optical correlation tomography, the three-dimensional image of fingertip is obtained, according to preset image reconstruction mode, three-dimensional image is reconstructed, obtains N layer two-dimensional subsurface fingerprint image, respectively to each layer subsurface fingerprint image is extracted, and the feature map corresponding to each layer subsurface fingerprint image is obtained, and all feature maps are weighted fusion, and obtain fusion feature map, based on fusion feature map, determine the position map and direction map of each minutia point of fingerprint, and the position map and direction map of each minutia point are as target fingerprint information, improve the quality of extracted fingerprint minutia 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.

Method for comparing two dactylograms from the lists of their minutiae, said method takes, as input data, a first source matrix MS1 of the coordinates of each minutiae of a first list L1 of minutiae of a first dactylogram and a second source matrix MS2 of the coordinates of each minutiae of a second list L2 of minutiae of a second dactylogram, and provides, as output data, a correspondence score between the two lists L1, L2 of minutiae.