CN115527244B - Fingerprint image matching method and device, computer equipment and storage medium - Google Patents
Fingerprint image matching method and device, computer equipment and storage medium Download PDFInfo
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- CN115527244B CN115527244B CN202211496306.1A CN202211496306A CN115527244B CN 115527244 B CN115527244 B CN 115527244B CN 202211496306 A CN202211496306 A CN 202211496306A CN 115527244 B CN115527244 B CN 115527244B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/751—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/98—Detection or correction of errors, e.g. by rescanning the pattern or by human intervention; Evaluation of the quality of the acquired patterns
Abstract
The application provides a fingerprint image matching method, a fingerprint image matching device, computer equipment and a storage medium, wherein the method comprises the following steps: collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified; if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized; performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched; and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result. According to the fingerprint image matching method and device, after image preprocessing is carried out on the collected fingerprint images, the characteristic is extracted to generate the fingerprint template, so that the fingerprint template is matched with a fingerprint library, the efficiency and accuracy of fingerprint image matching are effectively improved, and the rejection rate and the false recognition rate during fingerprint identification of a small area are reduced.
Description
Technical Field
The application relates to the technical field of image processing, in particular to a fingerprint image matching method, a fingerprint image matching device, computer equipment and a storage medium.
Background
With the development and progress of society, personal identity verification is required in more and more use scenes, and fingerprint identification is the most commonly applied personal identity identification method with the highest identification rate and the most easy acceptance. At present, large-area fingerprint identification technology based on traditional minutiae is quite mature, but with the use of fingerprint identification technology in more and more mobile terminal devices in the market, in order to reduce the pressure of storage and calculation amount of the mobile terminal devices and reduce the cost, the terminal devices are more inclined to adopt small-area fingerprint sensors.
However, in the process of research and practice on the prior art, the inventors of the present application found that, when the area of a fingerprint is reduced, on one hand, the amount of information in the fingerprint is reduced, and on the other hand, the overlapped part in the fingerprint comparison is also reduced, which results in an increase in the rejection rate and the false recognition rate of the fingerprint identification of a small area, and this brings a great challenge to the conventional fingerprint identification technology mainly based on minutiae.
The foregoing description is provided for general background information and does not necessarily constitute prior art.
Disclosure of Invention
In view of the above technical problems, the present application provides a fingerprint image matching method, apparatus, computer device and storage medium, which can effectively improve the efficiency and accuracy of fingerprint image matching and reduce the recognition rejection rate and the recognition error rate during small-area fingerprint recognition.
In order to solve the above technical problem, the present application provides a fingerprint image matching method, including the following steps:
collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified;
if the image quality score of the fingerprint image to be identified is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be identified;
performing feature extraction on the fingerprint image to be identified after the image preprocessing to generate a corresponding fingerprint template to be matched;
and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
Optionally, the performing feature extraction on the fingerprint image to be identified after the image preprocessing to generate a corresponding fingerprint template to be matched includes:
extracting fingerprint characteristic points and singular points of the fingerprint image to be identified;
and generating a fingerprint template to be matched corresponding to the fingerprint image to be identified based on the fingerprint feature points and the singular points.
Optionally, the matching the fingerprint template to be matched with a fingerprint template in a fingerprint library includes:
determining a vector line segment pair of the fingerprint template to be matched based on the fingerprint feature points and singular points of the fingerprint image to be identified;
comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template in the fingerprint database;
if the success rate of comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template is greater than a second preset threshold, calculating the central point of the fingerprint template to be matched;
rotating the fingerprint template to be matched based on the central point to align the fingerprint template;
and calculating the proportion of the coincidence area of the fingerprint template to be matched and the fingerprint template, and comparing the fingerprint directions in the coincidence range to generate a corresponding matching result.
Optionally, after the matching is performed on the fingerprint template to be matched and a fingerprint template in a fingerprint database to obtain a matching result, the method further includes:
updating the successfully matched fingerprint template to be matched into the fingerprint database;
and updating the fingerprint template in the fingerprint database based on the matching result.
Optionally, the updating the fingerprint template in the fingerprint database based on the matching result includes:
based on the matching result, searching the characteristic points and singular points which are not in the fingerprint database in the successfully matched fingerprint template to be matched;
restoring the characteristic points and singular points which are not in the fingerprint database into a fingerprint template in the fingerprint database according to the relative position of the vector line segment pair;
searching characteristic points and singular points which are superposed with the fingerprint template of the fingerprint library in the successfully matched fingerprint template to be matched, and updating the fraction of the fingerprint template;
and if the successfully matched fingerprint template to be matched is not completely covered by the fingerprint template of the fingerprint library, updating the directional diagram exceeding the covered part to the fingerprint template.
Optionally, the updating the fingerprint template in the fingerprint database based on the matching result further includes:
searching characteristic points and singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database, and reducing the score of a preset proportion;
and when the scores of the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched are lower than a third preset threshold value, deleting the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database.
Optionally, after the generating of the corresponding to-be-matched fingerprint template, the method further includes:
acquiring a plurality of fingerprint templates to be matched;
matching the fingerprint templates to be matched pairwise;
if any fingerprint template to be matched is successfully matched, expanding the first fingerprint template to be matched, adding the expanded first fingerprint template to the fingerprint library, and deleting the second fingerprint template to be matched;
and if any fingerprint template to be matched except any fingerprint template to be matched fails to be matched with the first fingerprint template to be matched, adding any fingerprint template to be matched except any fingerprint template to be matched into a fingerprint library.
Correspondingly, the application also provides a fingerprint image matching device, which comprises:
the fingerprint identification device comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a fingerprint image to be identified and grading the image quality of the fingerprint image to be identified;
the preprocessing module is used for preprocessing the fingerprint image to be identified if the image quality score of the fingerprint image to be identified is greater than a first preset threshold value;
the template generation module is used for extracting the characteristics of the fingerprint image to be identified after the image preprocessing and generating a corresponding fingerprint template to be matched;
and the matching module is used for matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
An embodiment of the present application further provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the fingerprint image matching method as described above when executing the computer program.
Embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the fingerprint image matching method as described above.
The embodiment of the invention has the following beneficial effects:
as described above, the present application provides a fingerprint image matching method, apparatus, computer device and storage medium, wherein the method includes: collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified; if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized; performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched; and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result. According to the embodiment of the application, the fingerprint template is generated by extracting the characteristics after the acquired fingerprint image is subjected to image preprocessing, so that the fingerprint template is matched with a fingerprint database, and the efficiency and the accuracy of fingerprint image matching are effectively improved; in addition, vector line segments are generated through characteristic points and singular points in the fingerprint images for image matching, the accuracy of fingerprint image matching is further improved, and the fingerprint template is expanded and updated according to the matching result, so that the rejection rate and the false recognition rate in small-area fingerprint identification are reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and, together with the description, serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a first implementation of a fingerprint image matching method provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of step S3 provided in an embodiment of the present application;
fig. 3 is a schematic flowchart of step S4 provided in the embodiment of the present application;
fig. 4 is a schematic flowchart of a second implementation of a fingerprint image matching method provided in an embodiment of the present application;
fig. 5 is a schematic flowchart of step S6 provided in the embodiment of the present application;
FIG. 6 is a schematic flowchart of fingerprint matching provided by an embodiment of the present application;
fig. 7 is a schematic flowchart of registration provided in an embodiment of the present application;
FIG. 8 is a flowchart illustrating a third implementation manner of a fingerprint image matching method according to an embodiment of the present application;
FIG. 9 is a schematic structural diagram of a fingerprint image matching device according to an embodiment of the present application;
FIG. 10 is a schematic structural diagram of a fingerprint image matching system provided in an embodiment of the present application;
FIG. 11 is a schematic structural diagram of a first implementation of a computer device provided by an embodiment of the present application;
fig. 12 is a schematic structural diagram of a second implementation of a computer device provided in an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings. With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element, and further, components, features, elements, and/or steps that may be similarly named in various embodiments of the application may or may not have the same meaning, unless otherwise specified by its interpretation in the embodiment or by context with further embodiments.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein. The word "if," as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination," depending on the context. Also, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, species, and/or groups thereof. As used herein, the terms "or," "and/or," "including at least one of the following," and the like, are to be construed as inclusive or meaning any one or any combination. For example, "includes at least one of: A. b, C "means" any of the following: a; b; c; a and B; a and C; b and C; a and B and C ", further for example," A, B or C "or" A, B and/or C "means" any of the following: a; b; c; a and B; a and C; b and C; a and B and C'. An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.
It should be understood that, although the steps in the flowcharts in the embodiments of the present application are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or at least partially with respect to other steps or sub-steps of other steps.
The words "if", as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (a stated condition or event)" may be interpreted as "upon determining" or "in response to determining" or "upon detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)", depending on the context.
It should be noted that step numbers such as S1 and S2 are used herein for the purpose of more clearly and briefly describing corresponding contents, and do not constitute a substantial limitation on the sequence, and those skilled in the art may perform S2 first and then S1 in the specific implementation, but these should be within the protection scope of the present application.
It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for the convenience of description of the present application, and have no specific meaning in themselves. Thus, "module", "component" or "unit" may be used mixedly.
Before describing the technical solution of the present invention, the related technical terms are briefly explained:
fingerprint template: the original fingerprint is used as a parent, and a plurality of irreversible and unrelated fingerprint sub-books are derived by a certain means, and the sub-books can replace the characteristic information of the fingerprint for identification.
Fingerprint feature points, comprising: end points, fork points, bifurcation points, isolated points, short veins, loop points, bridges; wherein the endpoints indicate the termination of a grain and the cross points indicate where a grain is divided into two or more grains.
Core point (core point): the core point is located at the progressive center of the fingerprint lines.
Triangular point (delta): the triangular point is the central point of the triangular grain region in the fingerprint image, and three fingerprint lines closest to the point form an approximate triangle.
Singular points: the core points and the triangular points are collectively called singular points.
False Acceptance Rate (FAR): refers to the proportion of different fingerprints that have a match score greater than a given threshold when the fingerprint recognition algorithm is tested against a standard fingerprint database, and thus are considered to be the same fingerprint, simply "consider fingerprints that should not match as matching fingerprints".
Rejection Rate (FRR): this is the proportion of fingerprints that are considered to be different, simply "fingerprints that should match each other successfully are considered to be unmatched" when the fingerprint recognition algorithm is tested against a standard fingerprint database, with the match score for the same fingerprint being below a given threshold.
First, an application scenario that can be provided by the application is introduced, for example, a fingerprint image matching method, a fingerprint image matching device, a computer device and a storage medium are provided, so that the efficiency and the accuracy of fingerprint image matching are effectively improved, and the rejection rate and the false recognition rate of small-area fingerprint identification are reduced.
Referring to fig. 1, fig. 1 is a schematic flowchart illustrating a fingerprint image matching method according to an embodiment of the present disclosure. The fingerprint image matching method may specifically include:
s1, collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified.
Specifically, in step S1, a fingerprint image of the user is collected as a fingerprint image to be recognized, and image quality scoring is performed on the fingerprint image to be recognized, so as to determine the quality of the fingerprint image.
And S2, if the image quality score of the fingerprint image to be recognized is greater than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized.
Specifically, for step S2, if the image quality score of the acquired fingerprint image to be recognized is greater than the first preset threshold, the quality of the fingerprint image to be recognized is considered to be qualified, and image preprocessing is performed on the fingerprint image to be recognized, so as to further improve the image quality of the fingerprint image, so as to improve the accuracy and efficiency of subsequent feature extraction, and ensure the reliability when the images are matched; if the image quality score of the acquired fingerprint image to be identified is less than or equal to the first preset threshold value, the quality of the fingerprint image to be identified is considered to be unqualified, and the fingerprint image of the user needs to be acquired again. The image quality scoring method may be to score the image features of the fingerprint image by weight, and is not specifically limited herein.
In a specific embodiment, the image preprocessing in this embodiment mainly aims to filter image noise and enhance the contrast between ridges and valleys, so as to improve the quality of a fingerprint image, change the fingerprint image to be identified into a clear dot line map, and facilitate subsequent extraction of correct fingerprint features. The image preprocessing includes, but is not limited to, smoothing, normalizing, filtering, enhancing, and binarizing, and the like, and is not particularly limited herein.
And S3, performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched.
Specifically, in step S3, feature extraction is mainly performed on the fingerprint image to be recognized after image preprocessing and image quality is improved, various features of the fingerprint in the fingerprint image to be recognized are proposed, and a comprehensive description of the fingerprint is formed, so that a corresponding fingerprint template to be matched is generated.
Optionally, as shown in fig. 2, in some embodiments, step S3 may specifically include:
s31, extracting fingerprint characteristic points and singular points of a fingerprint image to be identified;
and S32, generating a fingerprint template to be matched corresponding to the fingerprint image to be identified based on the fingerprint feature points and the singular points.
In a specific embodiment, feature extraction is carried out on the fingerprint image to be identified, and fingerprint feature points and singular points are extracted, so that the fingerprint template to be matched corresponding to the fingerprint image to be identified is generated based on the fingerprint feature points and the singular points. The fingerprint image comprises fingerprint characteristic points and singular points, wherein the fingerprint characteristic points comprise but are not limited to end points, cross points, branch points, isolated points, short lines, ring points, bridges and the like, the singular points comprise core points and triangular points, the core points are located in the progressive center of fingerprint lines, the triangular points are the central points of triangular line areas in the fingerprint image, and three fingerprint lines closest to the points form an approximate triangle.
And S4, matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
Specifically, in step S4, the obtained fingerprint template to be matched is matched with a plurality of fingerprint templates in the fingerprint database, and whether the fingerprint template to be matched of the current user is matched with the fingerprint database is authenticated, so as to obtain a matching result.
Optionally, as shown in fig. 3, in some embodiments, step S4 may specifically include:
s41, determining a vector line segment pair of the fingerprint template to be matched based on the fingerprint feature points and singular points of the fingerprint image to be identified;
s42, comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template in the fingerprint database;
s43, if the success rate of comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template is greater than a second preset threshold value, calculating the central point of the fingerprint template to be matched;
s44, rotating the fingerprint template to be matched based on the central point to align the fingerprint template;
s45, calculating the proportion of the overlapping area of the fingerprint template to be matched and the fingerprint template, comparing the fingerprint directions within the overlapping range, and generating a corresponding matching result.
In a specific embodiment, fingerprint feature points and singular points of a fingerprint image to be identified are obtained, all the fingerprint feature points and the singular points are connected in pairs until all the fingerprint feature points or the singular points and any other points form line segments, so that vector line segment pairs in a fingerprint template to be matched corresponding to the fingerprint image to be identified are formed, the vector line segment pairs of the fingerprint template to be matched are compared with vector line segments of fingerprint templates in a fingerprint library, a large amount of time spent on repeated alignment and rotation of the fingerprint template is saved, wherein the vector line segment generation mode of the fingerprint template in the fingerprint library is that all the fingerprint feature points and the singular points are connected in pairs, whether the success rate of the comparison of the vector line segment pairs is greater than a second preset threshold (for example, 80%) is judged, if the success rate of the comparison of the fingerprint matching is less than or equal to the second preset threshold, the corresponding feature points are found according to the line segment pairs on the fingerprint template, whether the points successfully matched and the points in the fingerprint library are in the same effective range is checked, if the match is in the same effective range, the mean value of the center points of the fingerprint template is calculated, and the mean value of the center points of the fingerprint template is calculated; rotating and aligning the fingerprint template to be matched and the fingerprint template in the fingerprint library according to the coordinates of the central point, for example, rotating and translating the fingerprint template to be matched, so as to align the fingerprint template in the fingerprint library; updating a directional diagram in the fingerprint template to be matched according to the rotation and offset parameters, wherein the direction of fingerprint lines is stored in each coordinate in the directional diagram; according to the two aligned templates, calculating the overlapping area proportion (the area proportion of the directional diagram overlapping) of the fingerprint template to be matched and the fingerprint template, judging whether the overlapping area proportion is larger than a preset threshold (for example, 70%), if not, the fingerprint matching fails, if so, comparing whether partial fingerprint lines in the overlapping range of the two templates are consistent, if so, judging the fingerprint matching succeeds, otherwise, failing. For example, the area of the coincidence of the directional diagrams is calculated firstly, the consistency of the directions of the fingerprint lines of the two templates is compared under the condition that the coincidence area is larger than 70% of the area of the fingerprints, if the directions of 90% points of the coincidence part are consistent, the fingerprint matching is considered to be successful, and if not, the matching is failed.
Optionally, as shown in fig. 4, in some embodiments, after step S4, the method may further include:
s5, updating the successfully matched fingerprint template to be matched into a fingerprint database;
and S6, updating the fingerprint template in the fingerprint database based on the matching result.
Specifically, after obtaining the matching result of the fingerprint image template, the embodiment further includes: and updating the successfully matched fingerprint template to be matched into a fingerprint library, and updating and expanding the original fingerprint template in the fingerprint library based on the matching result.
Optionally, as shown in fig. 5, in some embodiments, step S6 may specifically include:
s61, searching feature points and singular points which are not in a fingerprint database in the successfully matched fingerprint template to be matched based on the matching result;
s62, restoring the characteristic points and singular points which are not in the fingerprint database into the fingerprint template in the fingerprint database according to the relative positions of the vector line segment pairs;
s63, searching the feature points and the singular points which are successfully matched and coincide with the fingerprint templates of the fingerprint library in the to-be-matched fingerprint template, and updating the scores of the fingerprint templates;
and S64, if the successfully matched fingerprint template to be matched is not completely covered by the fingerprint template of the fingerprint library, updating the directional diagram beyond the covered part to the fingerprint template.
Specifically, after the fingerprint matching is successful, updating the feature points and singular points in the fingerprint database, including adding the feature points and the singular points, updating and replacing the feature points and the singular points, finding out the feature points and the singular points which are not in the fingerprint template of the fingerprint database, and restoring the feature points and the singular points to the fingerprint template in the fingerprint template database according to the relative positions of the vector line segment pairs; scoring the characteristic points according to the initial quality of the characteristic points and the singular points; finding out characteristic points and singular points in the fingerprint template of the fingerprint database of the overlapped part, and updating scores in the fingerprint template of the fingerprint database according to the matching condition of line segment pairs in the fingerprint template to be matched, the characteristic points and the singular points; and when the fingerprint matching is successful, updating the directional diagram in the fingerprint template, and if the fingerprint template to be matched has a part which is not completely covered by the fingerprint template in the fingerprint library, updating the directional diagram of the exceeding part into the fingerprint template in the fingerprint library.
Optionally, as shown in fig. 5, in some embodiments, step S6 may further include:
s65, searching characteristic points and singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database, and reducing the score of a preset proportion;
and S66, when the scores of the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched are lower than a third preset threshold value, deleting the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database.
Specifically, according to the characteristic values and singular points in the fingerprint template to be matched, searching is sequentially carried out in the fingerprint template of the fingerprint database in the corresponding area, and when the characteristic points or the singular points of the template which is not in the fingerprint database are found, the characteristic points or the singular points are added into the fingerprint template database template through the relative positions of vector line segment pairs; when the characteristic points and the singular points of the template in the fingerprint database are found, increasing the fraction of a preset proportion (such as 10 percent) and updating the fraction of the characteristic points or the singular points; when the characteristic points or singular points which do not appear in the fingerprint template to be matched are found, the fraction of a preset proportion (such as 10%) is reduced, and when the fraction is smaller than a third preset threshold (such as 10%), the corresponding characteristic points or singular points in the fingerprint template library are deleted.
It can be seen that, in the embodiment, by providing a matching method for small-area fingerprint images, vector line segments formed by feature points (end points, cross points, bifurcation points, isolated points, short stripes, ring points, bridges) and singular points (core points and triangular points) are used for comparison, so that various information is integrated, and a large number of translation and rotation operations in fingerprint matching are reduced; making a geometric center for the matched point, and aligning the fingerprint template to estimate the area; and updating the singular points of the characteristic points of the overlapped part, and updating the characteristic points and the singular points exceeding the area of the overlapped part to the fingerprint template in the fingerprint library so as to expand the fingerprint template and improve the success probability of fingerprint identification. Therefore, the problem of low success rate of fingerprint identification caused by insufficient small-area fingerprint characteristic information or less fingerprint overlapping part is solved.
As shown in fig. 6, the embodiment of the present application further provides a specific implementation method for fingerprint matching, which includes the specific steps of: generating a vector line segment pair 1 of a singular point of a feature point according to a newly sampled fingerprint template 1, comparing the vector line segment pair 1 with a line segment pair in a fingerprint template library, judging whether the ratio of successful comparison of the vector line segment pair 1 exceeds a threshold, if not, judging that fingerprint matching fails, if so, calculating the physical central points of the feature point and the singular point, finding a corresponding feature point according to the line segment pair on comparison, rotationally aligning the fingerprint template 1 by taking the physical centers of the feature point and the singular point as the central point, calculating the proportion of the overlapping area of the fingerprint template 1 according to the aligned template, judging whether the overlapping part of the fingerprint template 1 exceeds the threshold, if not, judging that fingerprint matching fails, and if so, judging whether the directions of the overlapping part of fingerprint lines of the fingerprint template 1 are consistent; if the fingerprint matching is consistent with the fingerprint matching threshold, judging that the fingerprint matching is successful, and if not, judging that the fingerprint matching is failed.
Optionally, as shown in fig. 7, in some embodiments, after step S3, the method may further include a registration process, and the specific steps are as follows:
s301, acquiring a plurality of fingerprint templates to be matched;
s302, matching every two fingerprint templates to be matched;
s303, if any fingerprint template to be matched is successfully matched, expanding the first fingerprint template to be matched, adding the expanded first fingerprint template to a fingerprint library, and deleting the second fingerprint template to be matched;
s304, if any fingerprint template to be matched except any fingerprint template to be matched fails to be matched with the first fingerprint template to be matched, adding any fingerprint template to be matched except any fingerprint template to be matched into the fingerprint library.
Specifically, after step S3, the present embodiment further includes registering according to the entered fingerprint image, and the specific process includes, first, collecting a plurality of fingerprint images, thereby generating a plurality of fingerprint templates to be matched, performing pairwise matching on the plurality of fingerprint templates to be matched, if the first fingerprint template and the second fingerprint template are successfully matched, expanding the first fingerprint template, deleting the second fingerprint template, entering the expanded first fingerprint template into the fingerprint library, and if the first fingerprint template and the third fingerprint template are unsuccessfully matched, entering the third fingerprint template into the fingerprint library.
As can be seen from the above, the fingerprint image matching method provided in the embodiment of the present application includes: collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified; if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized; performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched; and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result. According to the embodiment of the application, the collected fingerprint image is subjected to image preprocessing, and the characteristics are extracted to generate the fingerprint template, so that the fingerprint template is matched with a fingerprint library, and the efficiency and the accuracy of fingerprint image matching are effectively improved; in addition, by integrating various information in the fingerprint image and generating vector line segments through the characteristic points and the singular points to carry out image comparison, the accuracy of fingerprint image matching is further improved, the fingerprint comparison time is saved, and the fingerprint template is expanded and updated according to the matching result, so that the recognition rejection rate and the recognition error rate in the process of fingerprint identification of a small area are reduced.
As shown in fig. 8, an embodiment of the present application provides a flowchart schematic diagram of a third implementation manner of a fingerprint image matching method, where the specific flowchart includes: firstly, collecting a fingerprint image of a user, then judging the quality of the image, returning to the previous step if the quality is judged to be unqualified, continuously collecting the fingerprint, preprocessing the image of the fingerprint image if the quality is judged to be qualified, and generating a fingerprint template after finishing preprocessing the image; registering a user according to the generated fingerprint template, and inputting the fingerprint template into a fingerprint template database after the registration is successful; and performing characteristic matching according to the generated fingerprint template and a fingerprint template database, outputting a matching result, updating the extended fingerprint template after the matching is successful, and inputting the extended fingerprint template into the fingerprint template database.
Correspondingly, the present application further provides a fingerprint image matching apparatus, please refer to fig. 9, where fig. 9 is a schematic structural diagram of the fingerprint image matching apparatus provided in the present application, and specifically, the fingerprint image matching apparatus may include an acquisition module 100, a preprocessing module 200, a template generating module 300, and a matching module 400.
The system comprises an acquisition module 100, a storage module and a processing module, wherein the acquisition module 100 is used for acquiring a fingerprint image to be identified and scoring the image quality of the fingerprint image to be identified;
the preprocessing module 200 is configured to perform image preprocessing on the fingerprint image to be recognized if the image quality score of the fingerprint image to be recognized is greater than a first preset threshold;
the template generating module 300 is configured to perform feature extraction on the fingerprint image to be identified after image preprocessing, and generate a corresponding fingerprint template to be matched;
the matching module 400 is configured to match the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
Optionally, in some embodiments, the template generating module 300 may specifically include:
the extraction unit is used for extracting fingerprint characteristic points and singular points of the fingerprint image to be identified;
and the template generating unit is used for generating a fingerprint template to be matched corresponding to the fingerprint image to be identified based on the fingerprint characteristic points and the singular points.
Optionally, in some embodiments, the matching module 400 may specifically include:
the vector line segment pair unit is used for determining a vector line segment pair of the fingerprint template to be matched based on the fingerprint feature points and the singular points of the fingerprint image to be identified;
the comparison unit is used for comparing the vector line segments of the fingerprint template to be matched with the vector line segments of the fingerprint template in the fingerprint database;
the central point unit is used for calculating the central point of the fingerprint template to be matched if the success rate of comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template is greater than a second preset threshold;
the aligning unit is used for rotating the fingerprint template to be matched based on the central point so as to align the fingerprint template;
and the matching unit is used for calculating the coincidence area proportion of the fingerprint template to be matched and the fingerprint template, comparing the fingerprint directions in the coincidence range and generating a corresponding matching result.
Optionally, in some embodiments, the fingerprint image matching device may further include:
the first updating module is used for updating the successfully matched fingerprint template to be matched into a fingerprint database;
and the second updating module is used for updating the fingerprint template in the fingerprint database based on the matching result.
Optionally, in some embodiments, the second updating module may specifically include:
the first searching unit is used for searching the characteristic points and the singular points which are not in the fingerprint database in the successfully matched fingerprint template to be matched based on the matching result;
the restoring unit is used for restoring the characteristic points and the singular points which are not in the fingerprint database into the fingerprint template in the fingerprint database according to the relative position of the vector line segment pair;
the second searching unit is used for searching the characteristic points and the singular points which are superposed with the fingerprint template of the fingerprint library in the successfully matched fingerprint template to be matched and updating the scores of the fingerprint template;
and the updating unit is used for updating the directional diagram exceeding the covered part to the fingerprint template if the successfully matched fingerprint template to be matched is not completely covered by the fingerprint template of the fingerprint library.
The third searching unit is used for searching the characteristic points and singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database and reducing the scores of the preset proportion;
and the deleting unit is used for deleting the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database when the scores of the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched are lower than a third preset threshold.
Optionally, in some embodiments, the fingerprint image matching device may further include:
the registration module is used for acquiring a plurality of fingerprint templates to be matched; matching a plurality of fingerprint templates to be matched pairwise; if any fingerprint template to be matched is successfully matched, expanding the first fingerprint template to be matched, adding the expanded first fingerprint template to the fingerprint library, and deleting the second fingerprint template to be matched; and if any fingerprint template to be matched except any fingerprint template to be matched fails to be matched with the first fingerprint template to be matched, adding any fingerprint template to be matched except any fingerprint template to be matched into the fingerprint library.
As can be seen from the above, in the fingerprint image matching device provided in the embodiment of the present application, the acquisition module 100 acquires a fingerprint image to be identified, and performs image quality scoring on the fingerprint image to be identified; the preprocessing module 200 is used for preprocessing the fingerprint image to be recognized if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value; the template generating module 300 is used for extracting the characteristics of the fingerprint image to be identified after image preprocessing and generating a corresponding fingerprint template to be matched; the matching module 400 matches the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result. According to the embodiment of the application, the collected fingerprint image is subjected to image preprocessing, and the characteristics are extracted to generate the fingerprint template, so that the fingerprint template is matched with a fingerprint library, and the efficiency and the accuracy of fingerprint image matching are effectively improved; in addition, by integrating various information in the fingerprint image and generating vector line segments through the characteristic points and the singular points to carry out image comparison, the accuracy of fingerprint image matching is further improved, the fingerprint comparison time is saved, and the fingerprint template is expanded and updated according to the matching result, so that the recognition rejection rate and the recognition error rate in the process of fingerprint identification of a small area are reduced.
As shown in fig. 10, an embodiment of the present application further provides a fingerprint image matching system, including:
and the fingerprint acquisition module is used for acquiring a fingerprint picture and judging the quality of the picture.
The image processing module is used for filtering noise, enhancing the contrast of ridges and valleys, improving the quality of the fingerprint image, changing the fingerprint image into a clear point line graph and facilitating the extraction of correct fingerprint characteristics. The method comprises the steps of smoothing, normalizing, filtering, enhancing, binarizing and the like of the image.
The fingerprint template generating module is used for extracting various characteristics of the fingerprint to form comprehensive description of the fingerprint, namely the fingerprint template.
And the registration module is used for finishing fingerprint input in the using process of the user.
And the fingerprint template matching module is used for finishing fingerprint authentication in the using process of the user.
And the updating fingerprint library module is used for updating the fingerprint template in the fingerprint library according to the matching result.
As shown in fig. 11, the present application further provides a first implementation manner of a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of a fingerprint image matching method when executing the computer program, including: collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified; if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized; performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched; and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
Referring to fig. 12, a second implementation of a computer device is also provided in the embodiments of the present application, where the computer device may be a server, and an internal structure of the computer device may be as shown in fig. 12. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the computer designed processor is used to provide computational and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for storing data such as fingerprint image matching methods and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a fingerprint image matching method. The fingerprint image matching method comprises the following steps: collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified; if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized; performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched; and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implementing a fingerprint image matching method, including the steps of: collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified; if the image quality score of the fingerprint image to be recognized is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be recognized; performing feature extraction on the fingerprint image to be identified after image preprocessing to generate a corresponding fingerprint template to be matched; and matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result.
According to the fingerprint image matching method, the fingerprint template is generated by extracting the characteristics after the acquired fingerprint image is subjected to image preprocessing, so that the fingerprint template is matched with the fingerprint database, and the efficiency and the accuracy of fingerprint image matching are effectively improved; in addition, vector line segments are generated through the characteristic points and the singular points in the fingerprint images for image matching, the accuracy of fingerprint image matching is further improved, and the fingerprint template is expanded and updated according to the matching result, so that the recognition rejection rate and the recognition error rate during small-area fingerprint identification are reduced.
It is to be understood that the foregoing scenarios are only examples, and do not constitute a limitation on application scenarios of the technical solutions provided in the embodiments of the present application, and the technical solutions of the present application may also be applied to other scenarios. For example, as can be known by those skilled in the art, with the evolution of system architecture and the emergence of new service scenarios, the technical solution provided in the embodiments of the present application is also applicable to similar technical problems.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
The steps in the method of the embodiment of the application can be sequentially adjusted, combined and deleted according to actual needs.
The units in the device in the embodiment of the application can be merged, divided and deleted according to actual needs.
In the present application, the same or similar term concepts, technical solutions and/or application scenario descriptions will be generally described only in detail at the first occurrence, and when the description is repeated later, the detailed description will not be repeated in general for brevity, and when understanding the technical solutions and the like of the present application, reference may be made to the related detailed description before the description for the same or similar term concepts, technical solutions and/or application scenario descriptions and the like which are not described in detail later.
In the present application, each embodiment is described with emphasis, and reference may be made to the description of other embodiments for parts that are not described or illustrated in any embodiment.
All possible combinations of the technical features in the embodiments are not described in the present application for the sake of brevity, but should be considered as the scope of the present application as long as there is no contradiction between the combinations of the technical features.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application or portions contributing to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (such as a ROM/RAM, a magnetic disk, and an optical disk) as above, and includes several instructions to enable a terminal device (which may be a mobile phone, a computer, a server, a controlled terminal, or a network device) to execute the method of each embodiment of the present application.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions according to the embodiments of the present application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, digital subscriber line) or wirelessly (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, memory Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The above description is only a preferred embodiment of the present application, and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are included in the scope of the present application.
Claims (6)
1. A fingerprint image matching method is characterized by comprising the following steps:
collecting a fingerprint image to be identified, and grading the image quality of the fingerprint image to be identified;
if the image quality score of the fingerprint image to be identified is larger than a first preset threshold value, performing image preprocessing on the fingerprint image to be identified;
performing feature extraction on the fingerprint image to be identified after the image preprocessing to generate a corresponding fingerprint template to be matched; the method comprises the following steps: extracting fingerprint characteristic points and singular points of the fingerprint image to be identified; generating a fingerprint template to be matched corresponding to the fingerprint image to be identified based on the fingerprint feature points and the singular points;
matching the fingerprint template to be matched with a fingerprint template in a fingerprint database to obtain a matching result; the method comprises the following steps: determining a vector line segment pair of the fingerprint template to be matched based on the fingerprint feature points and singular points of the fingerprint image to be identified; comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template in the fingerprint database; if the success rate of comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template is greater than a second preset threshold, calculating the central point of the fingerprint template to be matched; rotating the fingerprint template to be matched based on the central point to align the fingerprint template; calculating the proportion of the overlapping area of the fingerprint template to be matched and the fingerprint template, and comparing the fingerprint directions within the overlapping range to generate a corresponding matching result;
updating the successfully matched fingerprint template to be matched into the fingerprint library;
updating the fingerprint template in the fingerprint database based on the matching result; the method comprises the following steps: based on the matching result, searching the characteristic points and singular points which are not in the fingerprint database in the successfully matched fingerprint template to be matched; restoring the characteristic points and singular points which are not in the fingerprint database into a fingerprint template in the fingerprint database according to the relative positions of the vector line segment pairs; searching characteristic points and singular points which are superposed with the fingerprint template of the fingerprint library in the successfully matched fingerprint template to be matched, and updating the fraction of the fingerprint template; and if the successfully matched fingerprint template to be matched is not completely covered by the fingerprint template of the fingerprint library, updating the directional diagram exceeding the covered part to the fingerprint template.
2. The fingerprint image matching method of claim 1, wherein the updating the fingerprint template in the fingerprint library based on the matching result further comprises:
searching characteristic points and singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database, and reducing the score of a preset proportion;
and when the scores of the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched are lower than a third preset threshold value, deleting the characteristic points and the singular points which do not appear in the successfully matched fingerprint template to be matched in the fingerprint templates of the fingerprint database.
3. The fingerprint image matching method according to claim 1, wherein after the generating of the corresponding fingerprint template to be matched, the method further comprises:
acquiring a plurality of fingerprint templates to be matched;
matching the fingerprint templates to be matched pairwise;
if any fingerprint template to be matched is successfully matched, expanding the first fingerprint template to be matched, adding the expanded first fingerprint template to the fingerprint library, and deleting the second fingerprint template to be matched;
and if any fingerprint template to be matched except any fingerprint template to be matched fails to be matched with the first fingerprint template to be matched, adding any fingerprint template to be matched except any fingerprint template to be matched into a fingerprint library.
4. A fingerprint image matching device, comprising:
the fingerprint identification device comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a fingerprint image to be identified and grading the image quality of the fingerprint image to be identified;
the preprocessing module is used for preprocessing the fingerprint image to be identified if the image quality score of the fingerprint image to be identified is greater than a first preset threshold value;
the template generation module is used for extracting the characteristics of the fingerprint image to be identified after the image preprocessing and generating a corresponding fingerprint template to be matched; the method comprises the following steps: extracting fingerprint characteristic points and singular points of the fingerprint image to be identified; generating a fingerprint template to be matched corresponding to the fingerprint image to be identified based on the fingerprint feature points and the singular points;
the matching module is used for matching the fingerprint template to be matched with the fingerprint template in the fingerprint database to obtain a matching result; the method comprises the following steps: determining a vector line segment pair of the fingerprint template to be matched based on the fingerprint feature points and singular points of the fingerprint image to be identified; comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template in the fingerprint database; if the success rate of comparing the vector line segment pair of the fingerprint template to be matched with the vector line segment of the fingerprint template is greater than a second preset threshold, calculating the central point of the fingerprint template to be matched; rotating the fingerprint template to be matched based on the central point to align the fingerprint template; calculating the proportion of the overlapping area of the fingerprint template to be matched and the fingerprint template, and comparing the fingerprint directions within the overlapping range to generate a corresponding matching result;
the first updating module is used for updating the successfully matched fingerprint template to be matched into the fingerprint library;
the second updating module is used for updating the fingerprint template in the fingerprint database based on the matching result; the method comprises the following steps: based on the matching result, searching the characteristic points and singular points which are not in the fingerprint database in the successfully matched fingerprint template to be matched; restoring the characteristic points and singular points which are not in the fingerprint database into a fingerprint template in the fingerprint database according to the relative position of the vector line segment pair; searching characteristic points and singular points which are superposed with the fingerprint template of the fingerprint library in the successfully matched fingerprint template to be matched, and updating the fraction of the fingerprint template; and if the successfully matched fingerprint template to be matched is not completely covered by the fingerprint template of the fingerprint database, updating the directional diagram beyond the covered part to the fingerprint template.
5. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the fingerprint image matching method according to any one of claims 1 to 3.
6. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the fingerprint image matching method according to any one of claims 1 to 3.
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