CN110348377B - Fingerprint identification method and equipment - Google Patents
Fingerprint identification method and equipment Download PDFInfo
- Publication number
- CN110348377B CN110348377B CN201910616537.3A CN201910616537A CN110348377B CN 110348377 B CN110348377 B CN 110348377B CN 201910616537 A CN201910616537 A CN 201910616537A CN 110348377 B CN110348377 B CN 110348377B
- Authority
- CN
- China
- Prior art keywords
- fingerprint
- identified
- image
- matching
- algorithm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
-
- 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
- G06V40/1347—Preprocessing; Feature extraction
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Human Computer Interaction (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Collating Specific Patterns (AREA)
Abstract
The method comprises the steps of obtaining a fingerprint image to be identified, extracting characteristic points of the fingerprint image to be identified to obtain at least two characteristic points to be identified and position information of each characteristic point to be identified; matching the fingerprint image to be identified with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be identified based on the at least two characteristic points to be identified and the position information of each characteristic point to be identified; and calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized, so that more intelligent fingerprint recognition is realized, the problems of fingerprint damage and unclear fingerprint are solved, the accuracy of fingerprint recognition is improved, and the error recognition rate is reduced.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a fingerprint identification method and apparatus.
Background
In the prior art, the fingerprint identification passing rate of the old and the children is not high in the fingerprint identification of the intelligent lock. There are the following reasons: the fingerprint skin of the old is dry and the condition of deformity often occurs, so that the fingerprint characteristics are not obvious; the fingerprint of child is shallow to cause the fingerprint unclear, leads to the fingerprint characteristic point few, is difficult to extract, can't realize the effective identification of fingerprint. Therefore, how to effectively identify fingerprints is an urgent problem to be solved in the industry.
Disclosure of Invention
An object of the present application is to provide a fingerprint identification method and apparatus, so as to solve the problems of difficult extraction of feature points and low fingerprint identification rate caused by incomplete fingerprint and unclear fingerprint lines in the fingerprint identification process in the prior art.
According to an aspect of the present application, there is provided a fingerprint identification method including: the method comprises the following steps:
acquiring a fingerprint image to be identified, and extracting feature points of the fingerprint image to be identified to obtain at least two feature points to be identified and position information of each feature point to be identified;
matching the fingerprint image to be identified with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be identified based on the at least two characteristic points to be identified and the position information of each characteristic point to be identified;
and calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized.
Further, the fingerprint identification method further includes:
the fingerprint template library is preset and comprises at least one fingerprint template image, and each fingerprint template image comprises at least two fingerprint characteristic points and position information of each fingerprint characteristic point.
Further, in the fingerprint identification method, based on the at least two feature points to be identified and the position information of each feature point to be identified, matching the fingerprint image to be identified with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be identified includes:
respectively carrying out feature point matching on the at least two feature points to be identified and each fingerprint feature point in the corresponding fingerprint template image to obtain matching feature points which are matched with the corresponding fingerprint feature points in the at least two feature points to be identified;
carrying out position matching on the position information of the matching characteristic points and the position information of the fingerprint characteristic points corresponding to the matching characteristic points, and counting the number of the matching characteristic points which are not matched with the position information of the fingerprint characteristic points;
and determining a matching result of the fingerprint images to be identified based on the number.
Further, in the fingerprint identification method, determining a matching result of the fingerprint image to be identified based on the number includes:
presetting a preset quantity threshold of the characteristic points to be identified, which are not matched with the position information of the fingerprint characteristic points in the fingerprint template image;
and determining a matching result of the fingerprint images to be identified based on the number and the preset number threshold.
Further, in the fingerprint identification method, invoking a corresponding identification algorithm based on the matching result to perform fingerprint identification on the fingerprint image to be identified includes:
if the matching result is that the number is larger than or equal to the preset number threshold, calling an image algorithm to perform fingerprint identification on the fingerprint image to be identified;
and if the matching result is that the number is smaller than the preset number threshold, calling a characteristic point algorithm to perform fingerprint identification on the fingerprint image to be identified.
Further, in the fingerprint identification method, the invoking of the image algorithm to perform fingerprint identification on the fingerprint image to be identified includes:
and calling a binarization algorithm, a filtering algorithm and the image algorithm to perform fingerprint identification on the fingerprint image to be identified.
Further, in the fingerprint identification method, the invoking of the image algorithm to perform fingerprint identification on the fingerprint image to be identified includes:
and calling a multi-direction filtering algorithm and the image algorithm to perform fingerprint identification on the fingerprint image to be identified.
According to another aspect of the present application, there is also provided a computer readable medium having computer readable instructions stored thereon, which, when executed by a processor, cause the processor to implement the method of any one of the above.
According to another aspect of the present application, there is also provided a computer-readable medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement a method as in any one of the above.
Compared with the prior art, the method and the device have the advantages that the fingerprint image to be identified is obtained, the characteristic points of the fingerprint image to be identified are extracted, and the at least two characteristic points to be identified and the position information of each characteristic point to be identified are obtained; matching the fingerprint image to be identified with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be identified based on the at least two characteristic points to be identified and the position information of each characteristic point to be identified; and calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized. The fingerprint identification method and the fingerprint identification device have the advantages that the fingerprint images to be identified are matched with the corresponding fingerprint template images through the at least two characteristic points to be identified extracted from the fingerprint images to be identified and the position information of each characteristic point to be identified, and the corresponding identification algorithm is called according to the matching result to realize the fingerprint identification of the fingerprint images to be identified, so that the fingerprint identification is more intelligent, the corresponding identification algorithm is called to carry out the fingerprint identification on the fingerprint images to be identified according to different matching results caused by the problems of damage, clearness and the like of the fingerprints, the error identification rate of the fingerprint identification is reduced, and the accuracy rate of the fingerprint identification is further improved.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 illustrates a flow diagram of a method of fingerprint identification in accordance with an aspect of the subject application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
Fig. 1 is a schematic flow chart of a fingerprint identification method according to an aspect of the present application, and is applied to a terminal for identifying a fingerprint, where the terminal may be a fingerprint identifier, a fingerprint identification lock, a mobile device, and other devices that need to identify a fingerprint, and a fingerprint identification area is provided in the terminal for collecting or inputting one or more fingerprints. The method comprises a step S1, a step S2 and a step S3, wherein the method specifically comprises the following steps:
step S1, acquiring a fingerprint image to be identified, and extracting feature points of the fingerprint image to be identified to obtain at least two feature points to be identified and position information of each feature point to be identified. Here, the identification fingerprint image includes, but is not limited to, fingerprint images of elderly people, children, adults, and the like.
For example, when a fingerprint of a user needs to be identified, the fingerprint of the user can be input through a fingerprint identification area set by the terminal so as to acquire and obtain a to-be-identified fingerprint image of the user; then, in the process of extracting the feature points of the fingerprint image to be identified, the information of the feature points of the fingerprint image to be identified, such as end points, bifurcation points and the like, which is used for indicating the feature points of the fingerprint image to be identified, is extracted by judging the direction of the fingerprint image to be identified on a ridge line structure, so as to obtain at least two feature points to be identified of the fingerprint image to be identified, and the position information of each feature point to be identified is determined at the same time, so that the feature points to be identified of the fingerprint image to be identified are extracted.
Step S2, matching the fingerprint image to be recognized with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be recognized based on the at least two feature points to be recognized and the position information of each feature point to be recognized. Here, the process of matching the fingerprint image to be recognized with the corresponding fingerprint template image includes feature point matching and position matching.
And step S3, calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized. The identification algorithm can include, but is not limited to, an image algorithm and a feature point algorithm, and it is ensured that two identification algorithms for identifying the fingerprint, namely the image algorithm and the feature point algorithm, are simultaneously stored in the terminal, so that the feature point algorithm and the image algorithm are integrated and stored in the terminal, when the fingerprint lines of the fingerprint image to be identified are clear and the fingerprint image effect is good, the feature point algorithm can be correspondingly called to identify the fingerprint image to be identified, and the error identification rate is reduced; when the fingerprint lines of the fingerprint image to be recognized are not clear enough and are damaged, the image algorithm can be correspondingly called to recognize the fingerprint image to be recognized, so that the recognition rate of the fingerprint image to be recognized is improved.
The steps S1 to S3 are performed to match the fingerprint image to be recognized with the corresponding fingerprint template image through at least two feature points to be recognized extracted from the fingerprint image to be recognized and the position information of each feature point to be recognized, and call the corresponding recognition algorithm according to the matching result to realize the fingerprint recognition of the fingerprint image to be recognized, so that the fingerprint recognition is more intelligent, and the corresponding recognition algorithm is called to perform the fingerprint recognition on the fingerprint image to be recognized according to different matching results caused by the problems of fingerprint breakage, unclear problems and the like, thereby reducing the false recognition rate of the fingerprint recognition and further improving the accuracy of the fingerprint recognition.
Another embodiment of the present application provides a fingerprint identification method, further including:
the fingerprint template library is preset and comprises at least one fingerprint template image, and each fingerprint template image comprises at least two fingerprint characteristic points and position information of each fingerprint characteristic point. Here, the fingerprint template library may be a fingerprint template image obtained by the terminal by acquiring fingerprints of one or more users, or may be a fingerprint template image obtained by entering fingerprints of one or more users in a fingerprint identification area provided in the terminal, and the fingerprint template library may include fingerprint template images corresponding to users of different age groups, or may include fingerprint template images corresponding to different users, so as to ensure that the fingerprint template library stores a variety of at least one fingerprint template image that can be called by the terminal for fingerprint matching after acquiring various fingerprint images to be identified. Certainly, the more the number of the fingerprint template images of various types of users (such as the elderly, children, adults and the like) in the fingerprint template library is preset, the wider the types are, the more the accuracy of fingerprint identification of the fingerprint images to be identified subsequently can be improved, and the improvement of the fingerprint identification passing rate can be facilitated.
Next to the above embodiment of the present application, the step S2, based on the at least two feature points to be recognized and the position information of each feature point to be recognized, matches the fingerprint image to be recognized with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be recognized, specifically including:
respectively carrying out feature point matching on the at least two feature points to be identified and each fingerprint feature point in the corresponding fingerprint template image to obtain matching feature points which are matched with the corresponding fingerprint feature points in the at least two feature points to be identified;
carrying out position matching on the position information of the matching characteristic points and the position information of the fingerprint characteristic points corresponding to the matching characteristic points, and counting the number of the matching characteristic points which are not matched with the position information of the fingerprint characteristic points;
and determining the matching result of the fingerprint images to be identified based on the number, which is favorable for further fingerprint identification.
For example, if the fingerprint template image corresponding to the fingerprint image a to be identified in the fingerprint template library is a fingerprint template image a, and the fingerprint feature points in the fingerprint template image a are respectively a1, a2, A3, a4, a5, a6, a7, A8, a9, and a 10; after feature points of the fingerprint image a to be identified are extracted in step S1, if the feature points to be identified in the fingerprint image a to be identified are obtained as a1, a2.. a49 and a50, respectively; step S2 is to identify each feature point to be identified in the fingerprint image a: a1, a2.. a49, a50 respectively correspond to each fingerprint feature point in the fingerprint template image a: a1, A2, A3, A4, A5, A6, A7, A8, A9 and A10 are subjected to feature point matching, and the feature points to be identified in the fingerprint image a to be identified are: a1, a2.. a49, a50, corresponding fingerprint feature points are acquired: a1, A2, A3, A4, A5, A6, A7, A8, A9 and A10.
Here, if the result of feature point matching between the fingerprint image a to be recognized and the corresponding fingerprint template image a is: a1-a1, A2-A3, A3-a5, A4-a7, A5-a10, A6-a20, A7-a25, A8-a30, A9-a35 and A10-a47, namely: the feature point to be identified, which is matched with the corresponding fingerprint feature point a1, is a1, the feature point to be identified, which is matched with the corresponding fingerprint feature point a2, is A3, the feature point to be identified, which is matched with the corresponding fingerprint feature point A3, is a5, the feature points to be identified, which are sequentially and respectively corresponding until the feature point to be identified, which is matched with the corresponding fingerprint feature point a10, is a47, and then the feature points to be identified in the fingerprint image a to be identified are selected from: a1, a2.. a49, a50, corresponding fingerprint feature points are acquired: matching characteristic points matched with A1, A2, A3, A4, A5, A6, A7, A8, A9 and A10 are as follows: a1, a3, a5, a7, a10, a20, a25, a30, a35, a40 and a 47.
Next, the position information D1 of the matching feature point a1 is subjected to position matching with the position information D1 of the corresponding fingerprint feature point a1, the position information D1 of the matching feature point a1 is subjected to position matching with the position information D1 of the corresponding fingerprint feature point a1, and the position information D1 of the matching feature point a1 is subjected to position matching with the position information D1 of the corresponding fingerprint feature point a1, and the position information D1 of the corresponding fingerprint feature point a1 is subjected to position matching with the position information D1 of the position matching. And performing position matching on the position information D35 of the matched feature point a35 and the position information D9 of the corresponding fingerprint feature point A9, performing position matching on the position information D47 of the matched feature point a47 and the position information D10 of the corresponding fingerprint feature point A10, and counting the number n of matched feature points which are not matched with the position information of the fingerprint feature points. Here, if the matching feature points that do not match the position information of the corresponding fingerprint feature points are obtained as a10 and a20, that is, the position information D10 of the matching feature point a10 does not match the position information D5 of the corresponding fingerprint feature point a5, and the position information D20 of the matching feature point a20 does not match the position information D6 of the corresponding fingerprint feature point a6, the number n of matching feature points that do not match the position information of the fingerprint feature points is obtained as 2, that is, n is 2.
Further, the determining, based on the number, a matching result of the fingerprint image to be recognized in step S2 specifically includes:
presetting a preset quantity threshold of the characteristic points to be identified, which are not matched with the position information of the fingerprint characteristic points in the fingerprint template image;
and determining a matching result of the fingerprint images to be identified based on the number and the preset number threshold.
For example, if the matching feature points that do not match the location information of the corresponding fingerprint feature points are a10 and a20, that is, the number n of matching feature points that do not match the location information of the fingerprint feature points is 2, that is, n is 2. If the preset number threshold of the feature points to be identified, which are not matched with the position information of the fingerprint feature points in the fingerprint template image, is N, determining a matching result of the fingerprint image to be identified according to the comparison between the number N and the preset number threshold N, wherein the matching result includes that the number is smaller than the preset number threshold, or the number is larger than or equal to the preset number threshold.
Next to the foregoing embodiment of the present application, the step S3 calls a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized, and specifically includes:
if the matching result is that the number is larger than or equal to the preset number threshold, calling an image algorithm to perform fingerprint identification on the fingerprint image to be identified; the image algorithm extracts interest points by using a mode based on image gray information detection, extracts high-dimensional information of the extracted interest points, and finally matches the interest point positions and the high-dimensional information of the fingerprint images to be identified with the interest point positions and the high-dimensional information of all the fingerprint images in the fingerprint database to obtain a fingerprint identification result.
And if the matching result is that the number is smaller than the preset number threshold, calling a characteristic point algorithm to perform fingerprint identification on the fingerprint image to be identified. Here, in the feature point algorithm, the feature point extraction is to judge in the direction of the ridge line structure of the fingerprint image, and information such as an end point and a branch point can be extracted. And recording information such as the type, angle, position and the like of the feature points based on the extraction of the information, and matching the recorded information of the fingerprint image to be identified with the recorded information of the fingerprint image in the fingerprint library to obtain a fingerprint identification result.
For example: if the matched feature points whose position information does not match are a10 and a20, that is, the number of matched feature points whose position information does not match is n-2. The preset threshold of the matching feature point with unmatched position information is N, and the determination process here is as follows:
when N is larger than or equal to N, the fingerprint lines of the fingerprint image to be recognized are not clear enough or damaged, an image algorithm is selected to call the image algorithm to perform fingerprint recognition on the fingerprint image to be recognized, so that the fingerprint recognition is more intelligent, the error recognition rate of the fingerprint recognition of the fingerprint image to be recognized with the fingerprint lines not clear enough or damaged is reduced, the accuracy of the fingerprint recognition is further improved, the error recognition rate of the fingerprint recognition is reduced, and the accuracy of the fingerprint recognition is further improved; for example, when the preset threshold N is 2, the number of matching feature points whose position information does not match is N-2, that is, N-N, and an image algorithm is called to perform fingerprint identification on the fingerprint image to be identified.
When N is less than N, the fingerprint lines of the fingerprint image to be recognized are clear, a feature point algorithm is selected to call the feature point algorithm to perform fingerprint recognition on the fingerprint image to be recognized, the feature points extracted directly based on the steps are processed to obtain a fingerprint recognition result, so that the fingerprint recognition is more intelligent, the accuracy of the fingerprint recognition of the fingerprint image to be recognized with clear fingerprint lines is further improved, and the false recognition rate of the fingerprint recognition is reduced, for example, when a preset threshold value N is 5, the number of matched feature points with unmatched position information is N-2, namely N is less than N, and the feature point algorithm is called to perform fingerprint recognition on the fingerprint image to be recognized.
Next, in the foregoing embodiment of the present application, the invoking an image algorithm to perform fingerprint identification on the fingerprint image to be identified includes:
and calling a binarization algorithm, a filtering algorithm and the image algorithm to perform fingerprint identification on the fingerprint image to be identified.
For example, aiming at the problem that the fingerprint lines of the children are shallow and unclear, an image algorithm is called to perform fingerprint identification on the fingerprint image to be identified, and a filtering algorithm and a binarization algorithm are added simultaneously, so that the binarization algorithm with a filtering function is added when the fingerprint image to be identified of the children is subjected to fingerprint identification, and the gray level stretching treatment is performed on the fingerprint image to be identified of the children so that the lines in the fingerprint image to be identified are clearer, thereby being beneficial to the further operation of fingerprint identification; and then, on the basis of the gray level stretching processing of the fingerprint image to be identified, the work of extracting characteristic values and the like is carried out, the problem of unclear fingerprints is solved, the accuracy of fingerprint identification is improved, and the error identification rate of fingerprint identification is reduced.
Next, in the foregoing embodiment of the present application, the invoking an image algorithm to perform fingerprint identification on the fingerprint image to be identified includes:
and calling a multi-direction filtering algorithm and the image algorithm to perform fingerprint identification on the fingerprint image to be identified.
For example, aiming at the problem of dry and damaged fingerprints of the old people, an image algorithm is called to perform fingerprint identification on the fingerprint image to be identified, and meanwhile, a multi-direction filtering algorithm is called to perform processing of filling up damaged areas on the fingerprint image to be identified, so that the continuity of the fingerprint image to be identified is recovered, the problems of damaged and unclear fingerprints are solved, and the accuracy of fingerprint identification is improved.
According to another aspect of the present application, there is also provided a computer readable medium having stored thereon computer readable instructions, which, when executed by a processor, cause the processor to implement the method of controlling user base alignment as described above.
According to another aspect of the present application, there is also provided a fingerprint recognition apparatus, characterized in that the apparatus includes:
one or more processors;
a computer-readable medium for storing one or more computer-readable instructions,
when executed by the one or more processors, cause the one or more processors to implement a method of controlling user base station on a device as described above.
Here, for details of each embodiment of the device, reference may be specifically made to corresponding parts of the embodiment of the method for controlling user base pairing at the device side, and details are not described here.
In summary, the fingerprint image to be identified is obtained, feature points of the fingerprint image to be identified are extracted, and at least two feature points to be identified and position information of each feature point to be identified are obtained; matching the fingerprint image to be identified with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be identified based on the at least two characteristic points to be identified and the position information of each characteristic point to be identified; and calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized, so that the fingerprint recognition of the fingerprint image to be recognized is realized by extracting at least two characteristic points to be recognized from the fingerprint image to be recognized and the position information of each characteristic point to be recognized, matching the fingerprint image to be recognized with the corresponding fingerprint template image, and calling the corresponding recognition algorithm according to the matching result, so that the fingerprint recognition is more intelligent, and the fingerprint recognition of the fingerprint image to be recognized is performed by calling the corresponding recognition algorithm according to different matching results caused by the problems of fingerprint breakage, unclear and the like, so that the error recognition rate of the fingerprint recognition is reduced, and the accuracy of the fingerprint recognition is further improved.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (5)
1. A method of fingerprint identification, the method comprising:
acquiring a fingerprint image to be identified, and extracting feature points of the fingerprint image to be identified to obtain at least two feature points to be identified and position information of each feature point to be identified;
matching the fingerprint image to be identified with a corresponding fingerprint template image to obtain a matching result of the fingerprint image to be identified based on the at least two characteristic points to be identified and the position information of each characteristic point to be identified; the method further comprises the following steps: presetting a fingerprint template library, wherein the fingerprint template library comprises at least one fingerprint template image, and each fingerprint template image comprises at least two fingerprint characteristic points and position information of each fingerprint characteristic point;
calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized;
the matching of the fingerprint image to be identified and the corresponding fingerprint template image to obtain the matching result of the fingerprint image to be identified based on the at least two feature points to be identified and the position information of each feature point to be identified comprises: respectively carrying out feature point matching on the at least two feature points to be identified and each fingerprint feature point in the corresponding fingerprint template image to obtain matching feature points which are matched with the corresponding fingerprint feature points in the at least two feature points to be identified; carrying out position matching on the position information of the matching characteristic points and the position information of the fingerprint characteristic points corresponding to the matching characteristic points, and counting the number of the matching characteristic points which are not matched with the position information of the fingerprint characteristic points; determining a matching result of the fingerprint images to be identified based on the number;
the determining the matching result of the fingerprint image to be identified based on the number comprises: presetting a preset quantity threshold of the characteristic points to be identified, which are not matched with the position information of the fingerprint characteristic points in the fingerprint template image; determining a matching result of the fingerprint images to be identified based on the number and the preset number threshold;
the step of calling a corresponding recognition algorithm based on the matching result to perform fingerprint recognition on the fingerprint image to be recognized comprises the following steps: if the matching result is that the number is larger than or equal to the preset number threshold, calling an image algorithm to perform fingerprint identification on the fingerprint image to be identified; and if the matching result is that the number is smaller than the preset number threshold, calling a characteristic point algorithm to perform fingerprint identification on the fingerprint image to be identified.
2. The method according to claim 1, wherein the invoking of the image algorithm performs fingerprint recognition on the fingerprint image to be recognized, and comprises:
and calling a binarization algorithm, a filtering algorithm and the image algorithm to perform fingerprint identification on the fingerprint image to be identified.
3. The method according to claim 1, wherein the invoking of the image algorithm performs fingerprint recognition on the fingerprint image to be recognized, and comprises:
and calling a multi-direction filtering algorithm and the image algorithm to perform fingerprint identification on the fingerprint image to be identified.
4. A computer readable medium having computer readable instructions stored thereon, which, when executed by a processor, cause the processor to implement the method of any one of claims 1 to 3.
5. An apparatus for fingerprint recognition, the apparatus comprising:
one or more processors;
a computer-readable medium for storing one or more computer-readable instructions,
the one or more computer-readable instructions, when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910616537.3A CN110348377B (en) | 2019-07-09 | 2019-07-09 | Fingerprint identification method and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910616537.3A CN110348377B (en) | 2019-07-09 | 2019-07-09 | Fingerprint identification method and equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110348377A CN110348377A (en) | 2019-10-18 |
| CN110348377B true CN110348377B (en) | 2022-02-11 |
Family
ID=68178613
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910616537.3A Active CN110348377B (en) | 2019-07-09 | 2019-07-09 | Fingerprint identification method and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110348377B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111126337A (en) * | 2019-12-31 | 2020-05-08 | 芜湖哈特机器人产业技术研究院有限公司 | Fingerprint identification method based on feature extraction and matching |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106127000A (en) * | 2016-06-17 | 2016-11-16 | 广东欧珀移动通信有限公司 | A kind of unlocked by fingerprint method and terminal |
| CN106778457A (en) * | 2015-12-11 | 2017-05-31 | 深圳市汇顶科技股份有限公司 | The fingerprint identification method and system of fingerprint recognition rate can be improved |
| CN107748877A (en) * | 2017-11-10 | 2018-03-02 | 杭州晟元数据安全技术股份有限公司 | A kind of Fingerprint recognition method based on minutiae point and textural characteristics |
| CN108460346A (en) * | 2018-02-09 | 2018-08-28 | 厦门美图移动科技有限公司 | Fingerprint identification method and device |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104966061B (en) * | 2015-06-16 | 2018-07-10 | 京东方科技集团股份有限公司 | A kind of palm grain identification method and device, intelligent safety door |
| CN105447454B (en) * | 2015-11-13 | 2018-05-01 | 广东欧珀移动通信有限公司 | Fingerprint template improving method, device and terminal device |
| CN105678238B (en) * | 2015-12-29 | 2019-04-26 | 努比亚技术有限公司 | Fingerprint certification device, method |
| US20170337410A1 (en) * | 2016-05-20 | 2017-11-23 | Novatek Microelectronics Corp. | Fingerprint sensing apparatus, an integrated sensor device, and a fingerprint sensing method |
| CN106250817A (en) * | 2016-07-19 | 2016-12-21 | 青岛海信移动通信技术股份有限公司 | A kind of fingerprint identification method and device |
| CN106339678A (en) * | 2016-08-23 | 2017-01-18 | 上海交通大学 | Fingerprint image representation method based on a variety of feature points |
-
2019
- 2019-07-09 CN CN201910616537.3A patent/CN110348377B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106778457A (en) * | 2015-12-11 | 2017-05-31 | 深圳市汇顶科技股份有限公司 | The fingerprint identification method and system of fingerprint recognition rate can be improved |
| CN106127000A (en) * | 2016-06-17 | 2016-11-16 | 广东欧珀移动通信有限公司 | A kind of unlocked by fingerprint method and terminal |
| CN107748877A (en) * | 2017-11-10 | 2018-03-02 | 杭州晟元数据安全技术股份有限公司 | A kind of Fingerprint recognition method based on minutiae point and textural characteristics |
| CN108460346A (en) * | 2018-02-09 | 2018-08-28 | 厦门美图移动科技有限公司 | Fingerprint identification method and device |
Non-Patent Citations (1)
| Title |
|---|
| 指纹图像的特征提取与匹配算法研究;车荣禄;《中国优秀硕士学位论文全文数据库信息科技辑》;20150115(第01期);I138-1315，第5、7、36页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110348377A (en) | 2019-10-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109086734B (en) | Method and device for positioning pupil image in human eye image | |
| US20210004587A1 (en) | Image detection method, apparatus, device and storage medium | |
| CN110348393B (en) | Vehicle feature extraction model training method, vehicle identification method and equipment | |
| US20200125836A1 (en) | Training Method for Descreening System, Descreening Method, Device, Apparatus and Medium | |
| CN111931548B (en) | Face recognition system, method for establishing face recognition data and face recognition method | |
| CN110969045B (en) | Behavior detection method and device, electronic equipment and storage medium | |
| CN110348392B (en) | Vehicle matching method and device | |
| CN110348377B (en) | Fingerprint identification method and equipment | |
| CN113052064B (en) | Attention detection method based on face orientation, facial expression and pupil tracking | |
| US20210319204A1 (en) | Fingerprint Matching Method And Apparatus, Electronic Equipment And Readable Storage Medium | |
| CN110909655A (en) | Method and equipment for identifying video event | |
| Khalil | Reference point detection for camera-based fingerprint image based on wavelet transformation | |
| CN111340788B (en) | Hardware Trojan horse layout detection method and device, electronic equipment and readable storage medium | |
| JP7121132B2 (en) | Image processing method, apparatus and electronic equipment | |
| CN109871779B (en) | Palm print identification method and electronic equipment | |
| WO2020244076A1 (en) | Face recognition method and apparatus, and electronic device and storage medium | |
| CN113613079B (en) | Intelligent device video advertisement processing method and intelligent device | |
| US10902106B2 (en) | Authentication and authentication mode determination method, apparatus, and electronic device | |
| CN114998283A (en) | Lens blocking object detection method and device | |
| CN114708420A (en) | Visual positioning method and device based on local variance and posterior probability classifier | |
| CN111310824A (en) | Multi-angle dense target detection inhibition optimization method and equipment | |
| CN111881770B (en) | Face recognition method and system | |
| CN113158788B (en) | Facial expression recognition method and device, terminal equipment and storage medium | |
| CN111524097B (en) | Method and device for detecting horn mouth of two devices, storage medium and equipment | |
| US20230298326A1 (en) | Image augmentation method, electronic device and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information |
Address after: Room 001a, 11 / F, building 1, 588 Zixing Road, Minhang District, Shanghai, 200241 Applicant after: Shanghai chuangmi Shulian Intelligent Technology Development Co.,Ltd. Address before: Room 908, No.1, Lane 399, shengxia Road, Pudong New Area pilot Free Trade Zone, Shanghai 201203 Applicant before: SHANGHAI CHUANGMI TECHNOLOGY Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |