CN112528946A - Fingerprint identification method and device, storage medium and electronic equipment - Google Patents
Fingerprint identification method and device, storage medium and electronic equipment Download PDFInfo
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- 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
- G06V40/13—Sensors therefor
- G06V40/1324—Sensors therefor by using geometrical optics, e.g. using prisms
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- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
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- 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
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1382—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger
- G06V40/1394—Detecting the live character of the finger, i.e. distinguishing from a fake or cadaver finger using acquisition arrangements
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Abstract
The present disclosure provides a fingerprint identification method, apparatus, storage medium and electronic device, the method comprising: acquiring a fingerprint characteristic value to be identified; sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a first fingerprint group, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in a fingerprint database, and A is a positive integer; and determining that the fingerprint to be identified passes the verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified. This openly constitutes first fingerprint group with a plurality of fingerprint eigenvalues that verify the frequency is the highest in the fingerprint database, when acquireing and treating discernment fingerprint eigenvalue, the fingerprint eigenvalue of storage among the first fingerprint group of preferential use contrasts, can carry out preferential identification to the higher fingerprint of verification frequency, shortens the verification time of effective fingerprint eigenvalue greatly to promote fingerprint identification's efficiency, promote user experience.
Description
Technical Field
The present disclosure relates to the field of intelligent identification technologies, and in particular, to a fingerprint identification method and apparatus, a storage medium, and an electronic device.
Background
At present, the intelligent door lock in the market is divided into a low end, a middle end and a low end, and the fingerprint module is generally a standard matching of the intelligent door lock. Starting from a fingerprint module, an optical fingerprint module is generally adopted at the low end, so that the cost is low, but the performance is poor, and an artificial fingerprint scheme can also pass; the middle end or the middle-high end generally adopts a semiconductor-capacitor or an inductance type; high-end generally employs biometric radio frequency fingerprint identification technology, such as vein fingerprint.
In the use in-process at current intelligent lock, to the very many intelligent lock of fingerprint number that can add, for example thousands of fingerprints, need compare in proper order with the fingerprint in the database to the fingerprint eigenvalue of gathering, if the fingerprint eigenvalue memory location that has added is more back, then need compare in proper order before all fingerprints before can compare with the fingerprint eigenvalue that corresponds, lead to fingerprint identification response time longer, the discernment is inefficient, influences user's use and experiences.
Disclosure of Invention
An object of the embodiments of the present disclosure is to provide a fingerprint identification method, an apparatus, a storage medium, and an electronic device, so as to solve the problems of long fingerprint identification time and low identification efficiency in the prior art.
The embodiment of the disclosure adopts the following technical scheme: a fingerprint identification method, comprising: acquiring a fingerprint characteristic value to be identified; sequentially comparing the characteristic values of the fingerprint to be identified with the characteristic values in a first fingerprint group, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in the fingerprint database, and A is a positive integer; and determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
Further, still include: and under the condition that the first fingerprint data does not exist in the first fingerprint group, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints except the first fingerprint group in the fingerprint database, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
Further, still include: and updating the fingerprint characteristic values stored in the first fingerprint group every a first preset period.
Further, before comparing the characteristic value of the fingerprint to be identified with the characteristic value in the first fingerprint group in sequence, the method further includes: acquiring current time; detecting whether the current time is within a preset time period; under the condition that the current time is within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with highest verification frequency within the preset time period in the fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within a preset time period.
Further, in case the first fingerprint data is not present in the first fingerprint group, the method further comprises: acquiring current time; detecting whether the current time is within a preset time period; under the condition that the current time is within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with highest verification frequency within the preset time period in the fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and under the condition that the first fingerprint data does not exist in the second fingerprint group or the current time is not within a preset time period, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints in the fingerprint database except the first fingerprint group, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
Further, still include: and updating the fingerprint characteristic values stored in the second fingerprint group every second preset period.
An embodiment of the present disclosure further provides a fingerprint identification device, including: the acquisition module is used for acquiring a fingerprint characteristic value to be identified; the comparison module is used for sequentially comparing the characteristic values of the fingerprint to be identified with the characteristic values in a first fingerprint group, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in the fingerprint database, and A is a positive integer; and determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
Further, still include: the time acquisition module is used for acquiring the current time; the detection module is used for detecting whether the current time is within a preset time period; the comparison module is further configured to sequentially compare the feature values of the fingerprint to be identified with feature values in a second fingerprint group when the current time is within the preset time period, where the second fingerprint group is a set of feature values corresponding to B fingerprints in the fingerprint database that have the highest verification frequency within the preset time period, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within a preset time period.
Embodiments of the present disclosure also provide a storage medium having a computer program stored thereon, which, when being executed by a processor, performs the steps of the fingerprint identification method described above.
Embodiments of the present disclosure also provide an electronic device, which at least includes a memory and a processor, where the memory stores a computer program thereon, and the processor implements the steps of the fingerprint identification method when executing the computer program on the memory.
The beneficial effects of this disclosed embodiment lie in: a plurality of fingerprint characteristic values with the highest verification frequency in the fingerprint database form a first fingerprint group, when the fingerprint characteristic values to be recognized are obtained, the fingerprint characteristic values stored in the first fingerprint group are preferentially used for comparison, the fingerprint with the higher verification frequency can be preferentially recognized, the verification time of effective fingerprint characteristic values is greatly shortened, the fingerprint recognition efficiency is improved, and the user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present disclosure, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a fingerprint identification method according to a first embodiment of the present disclosure;
FIG. 2 is a flow chart of a fingerprint identification method according to a second embodiment of the present disclosure;
FIG. 3 is a diagram illustrating a first exemplary structure of a fingerprint identification device according to a third embodiment of the present disclosure;
FIG. 4 is a diagram illustrating a second exemplary structure of a fingerprint identification device according to a third embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device in a fifth embodiment of the present disclosure.
Detailed Description
Various aspects and features of the disclosure are described herein with reference to the drawings.
It will be understood that various modifications may be made to the embodiments of the present application. Accordingly, the foregoing description should not be construed as limiting, but merely as exemplifications of embodiments. Other modifications will occur to those skilled in the art within the scope and spirit of the disclosure.
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the disclosure and, together with a general description of the disclosure given above, and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.
These and other characteristics of the present disclosure will become apparent from the following description of preferred forms of embodiment, given as non-limiting examples, with reference to the attached drawings.
It should also be understood that, although the present disclosure has been described with reference to some specific examples, a person of skill in the art shall certainly be able to achieve many other equivalent forms of the disclosure, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.
The above and other aspects, features and advantages of the present disclosure will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the present disclosure are described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various forms. Well-known and/or repeated functions and structures have not been described in detail so as not to obscure the present disclosure with unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present disclosure in virtually any appropriately detailed structure.
The specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may each refer to one or more of the same or different embodiments in accordance with the disclosure.
In the use in-process at current intelligent lock, to the very many intelligent lock of fingerprint number that can add, for example thousands of fingerprints, need compare in proper order with the fingerprint in the database to the fingerprint eigenvalue of gathering, if the fingerprint eigenvalue memory location that has added is more back, then need compare in proper order before all fingerprints before can compare with the fingerprint eigenvalue that corresponds, lead to fingerprint identification response time longer, the discernment is inefficient, influences user's use and experiences.
In order to solve the above problem, a first embodiment of the present disclosure provides a fingerprint identification method applied in an intelligent door lock, a flowchart of which is shown in fig. 1, and mainly includes steps S101 to S103:
and S101, acquiring a fingerprint characteristic value to be identified.
The intelligent door lock can add, delete, modify and the like the currently stored fingerprint information before and during use, a fingerprint database is arranged in the door lock host of the intelligent door lock and used for storing the IDs of all users and the corresponding fingerprint characteristic values of the users, the fingerprint module of the intelligent door lock can convert the fingerprint data of the users into the corresponding characteristic values and send the corresponding characteristic values to the door lock host after acquiring the fingerprint data of the users, the door lock host carries out sequential comparison of the fingerprint characteristic values in the database, and the fingerprint characteristic values corresponding to the users are different due to the fact that the fingerprints of the users are different. In this embodiment, the fingerprint feature value to be identified refers to the feature value of the fingerprint of the current user collected by the fingerprint module of the intelligent door lock.
And S102, comparing the characteristic value of the fingerprint to be identified with the characteristic value in the first fingerprint group in sequence.
When fingerprint identification is carried out, firstly, a fingerprint characteristic value to be identified is compared with a fingerprint characteristic value in a first fingerprint group, wherein the first fingerprint group is a set of characteristic values of A fingerprints with the highest verification frequency in all fingerprints recorded in the intelligent door lock, A is a positive integer, and is preferably between 10 and 30.
In this embodiment, the door lock host of the intelligent door lock counts the verification frequency of each fingerprint in the fingerprint database within a certain historical time period through self-learning and analysis of historical verification conditions, the higher the verification frequency is, the higher the frequency of using the intelligent door lock by the user corresponding to the fingerprint is, for the part of users, if the sequence of the corresponding fingerprint characteristic values stored in the fingerprint database is relatively backward, it takes a long time to perform the feature value traversal comparison each time fingerprint recognition is performed, the user experience is poor, so the fingerprint characteristic values of the part of users are extracted to form a first fingerprint group, the first fingerprint group is higher in priority in identification than other fingerprint characteristic values in the fingerprint database, after the fingerprint characteristic value to be identified is obtained, the fingerprint characteristic value in the first fingerprint group is preferentially used for comparing with the fingerprint to be identified.
It should be noted that, in the actual use process, the fingerprint feature values in the first fingerprint group may be updated after a first preset period, for example, if the first preset period is one month, then the verification frequency of each fingerprint in the fingerprint database is counted again every other month, the a fingerprints with the highest verification frequency in the month are taken as the fingerprints in the first fingerprint group, and the feature values are stored to be preferentially compared when fingerprint identification is performed in the next month.
S103, determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
Because the number of the fingerprint characteristic values in the first fingerprint group is small, the comparison result can be known quickly during comparison and identification, if a first fingerprint data exists in the first fingerprint group, the characteristic value of the first fingerprint data is the same as the characteristic value of the fingerprint to be identified, the fact that the user corresponding to the fingerprint characteristic value to be identified is the user who has performed fingerprint input in advance is proved, namely the fingerprint to be identified passes verification, and the intelligent door lock can perform unlocking operation.
This embodiment constitutes first fingerprint group with a plurality of fingerprint eigenvalues that verify the frequency is the highest in the fingerprint database, when acquireing and treating discernment fingerprint eigenvalue, preferentially uses the fingerprint eigenvalue of storage in the first fingerprint group to contrast, can carry out preferential identification to the higher fingerprint of verification frequency, shortens the verification time of effective fingerprint eigenvalue greatly to promote fingerprint identification's efficiency, promote user experience.
Fig. 1 further comprises a step S104, which discloses the following:
and S104, under the condition that the first fingerprint data does not exist in the first fingerprint group, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints except the first fingerprint group in the fingerprint database, and determining whether the fingerprint to be identified passes the verification or not based on the comparison result.
Under the condition that the first fingerprint data does not exist in the first fingerprint group, the verification frequency of the current fingerprint to be recognized is low, at the moment, the fingerprint characteristic value to be recognized can be sequentially compared with other fingerprint characteristic values except the first fingerprint group in the fingerprint database, if the fingerprint data with the same fingerprint characteristic value to be recognized exists in the fingerprint database, the fact that the current user is the user who carries out fingerprint input in advance is proved, namely the fingerprint to be recognized passes the verification, the intelligent door lock can carry out unlocking operation, if the fingerprint data with the same fingerprint characteristic value to be recognized does not exist in the fingerprint database, the user corresponding to the fingerprint to be recognized is determined not to be the user who carries out fingerprint input in advance, the intelligent door lock is kept in a locked state, and the condition that the user illegally unlocks the door lock is prevented.
The second embodiment of the present disclosure provides another implementation of the fingerprint identification method, which further performs the steps shown in fig. 2 before step S102 of the first embodiment:
s201, acquiring current time;
s202, detecting whether the current time is within a preset time period;
s203, under the condition that the current time is within a preset time period, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic value in the second fingerprint group;
s204, determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified;
s205, under the condition that the second fingerprint data does not exist in the second fingerprint group, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic value in the first fingerprint group.
In the actual use process, the verification frequency of some users in a fixed time period may be higher, for example, long-term overtime personnel or people who are accustomed to arriving early, but the overall verification frequency of the fingerprint feature values of the people may not be the highest; therefore, on the basis of setting the first fingerprint group, at least one second fingerprint group can be set, and each second fingerprint group is a set of characteristic values corresponding to B fingerprints with the highest verification frequency in the fingerprint database in different preset time periods, wherein B is a positive integer; certainly, in actual use, for the second fingerprint groups corresponding to different preset time periods, the number B of the fingerprint feature values contained in the second fingerprint groups may also be different, and the feature value of the same fingerprint may also exist in a plurality of second fingerprint groups at the same time.
After the fingerprint characteristic value to be identified is obtained, the current time is obtained, whether the current time is in one or more preset time periods or not is judged, if the current time is in the preset time period, the fingerprint characteristic value to be identified is preferentially compared with the characteristic values in the second fingerprint group, because the number of the fingerprint characteristic values in the second fingerprint group is less than that of all fingerprints, the comparison result can be rapidly known during comparison and identification, if a second fingerprint data exists in the second fingerprint group, the characteristic value is the same as the fingerprint characteristic value to be identified, the fact that the user corresponding to the fingerprint characteristic value to be identified is the user who has performed fingerprint input in advance is proved, namely the fingerprint to be identified passes verification, and the intelligent door lock can be unlocked.
If the second fingerprint data does not exist in the second fingerprint group, or the current time is not within the preset time period, the to-be-identified fingerprint feature value may be compared with the feature value in the first fingerprint group, that is, step S102 and subsequent steps in the first embodiment are executed until the comparison result is determined, which is not repeated here.
In addition, the method of this embodiment may also have an implementation manner that, after acquiring the fingerprint feature value to be identified, the fingerprint feature value is compared with the fingerprints in the first fingerprint group, and when the first fingerprint data does not exist in the first fingerprint group, whether the fingerprint feature value is within the preset time period is judged according to the current time, and when the fingerprint feature value is within the preset time period, the fingerprint feature value to be identified is compared with the fingerprint feature value in the second fingerprint group; if the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified, determining that the fingerprint to be identified passes verification, and at the moment, improving the fingerprint identification efficiency; if the second fingerprint data does not exist in the second fingerprint group or the current time is not in any preset time period, sequentially comparing the fingerprint characteristic value to be identified with other fingerprint characteristic values except the first fingerprint group in the fingerprint database, and determining whether the fingerprint to be identified passes verification or not based on the comparison result.
It should be noted that, in the actual use process, the fingerprint feature values in the second fingerprint group may be updated after a second preset period is set, for example, if the second preset period is one month, then, every other month, the verification frequency of each fingerprint in the fingerprint database in a preset time period is counted again, the B fingerprints with the highest verification frequency in the corresponding preset time period in the one month are taken as the fingerprints in the second fingerprint group, and the feature values are stored and compared preferentially according to the verification time when fingerprint identification is performed in the next month.
A third embodiment of the present disclosure provides a fingerprint identification apparatus, which can be installed in an electronic device with a fingerprint acquisition function, and a schematic structural diagram of the apparatus is shown in fig. 3, and mainly includes an acquisition module 10 and a comparison module 20, which are coupled to each other, where the acquisition module 10 is configured to acquire a characteristic value of a fingerprint to be identified; the comparison module 20 is configured to sequentially compare a feature value of a fingerprint to be identified with feature values in a first fingerprint group, where the first fingerprint group is a set of feature values corresponding to a fingerprint with the highest verification frequency in a fingerprint database, and a is a positive integer; and determining that the fingerprint to be identified passes the verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
In this embodiment, the obtaining module 10 may be a fingerprint obtaining module or a fingerprint obtaining device, which implements direct collection and obtaining of a user fingerprint, or may be a communication module connected to the fingerprint obtaining module or the fingerprint obtaining device, which implements obtaining of a fingerprint feature value collected by the fingerprint obtaining module or the fingerprint obtaining device through data interaction.
When fingerprint identification is performed, the comparison module 20 first compares the fingerprint features to be identified with the fingerprint feature values in a first fingerprint group, where the first fingerprint group is a set of feature values of a fingerprints with the highest verification frequency among all fingerprints recorded in the intelligent door lock, where a is a positive integer, and is preferably between 10 and 30.
In this embodiment, the comparison module 20 may count the verification frequency of each fingerprint in the fingerprint database within a certain historical time period through self-learning and analysis of historical verification conditions, where a higher verification frequency indicates that a user corresponding to the fingerprint uses the intelligent door lock more frequently, for the part of users, if the sequence of the corresponding fingerprint characteristic values stored in the fingerprint database is relatively backward, it takes a long time to perform the feature value traversal comparison each time fingerprint recognition is performed, the user experience is poor, so the fingerprint characteristic values of the part of users are extracted to form a first fingerprint group, the first fingerprint group is higher in priority in identification than other fingerprint characteristic values in the fingerprint database, after the fingerprint characteristic value to be identified is obtained, the fingerprint characteristic value in the first fingerprint group is preferentially used for comparing with the fingerprint to be identified.
It should be noted that, in the actual use process, the fingerprint feature values in the first fingerprint group may be updated after a first preset period, for example, if the first preset period is one month, then the verification frequency of each fingerprint in the fingerprint database is counted again every other month, the a fingerprints with the highest verification frequency in the month are taken as the fingerprints in the first fingerprint group, and the feature values are stored to be preferentially compared when fingerprint identification is performed in the next month.
Because the number of the fingerprint characteristic values in the first fingerprint group is small, the comparison result can be known quickly when the comparison module 20 performs comparison and identification, if a first fingerprint data exists in the first fingerprint group, and the characteristic value of the first fingerprint data is the same as the characteristic value of the fingerprint to be identified, it is proved that the user corresponding to the fingerprint characteristic value to be identified is indeed the user who has performed fingerprint input in advance, that is, the fingerprint to be identified passes verification, and the intelligent door lock can perform unlocking operation.
This embodiment constitutes first fingerprint group with a plurality of fingerprint eigenvalues that verify the frequency is the highest in the fingerprint database, when acquireing and treating discernment fingerprint eigenvalue, preferentially uses the fingerprint eigenvalue of storage in the first fingerprint group to contrast, can carry out preferential identification to the higher fingerprint of verification frequency, shortens the verification time of effective fingerprint eigenvalue greatly to promote fingerprint identification's efficiency, promote user experience.
Under the condition that the comparison module 20 determines that the first fingerprint data does not exist in the first fingerprint group, it is indicated that the verification frequency of the current fingerprint to be recognized is low, at this time, the comparison module 20 can sequentially compare the fingerprint characteristic value to be recognized with other fingerprint characteristic values in the fingerprint database except the first fingerprint group, if the fingerprint data with the same fingerprint characteristic value to be recognized exists in the fingerprint database, it is proved that the current user is indeed the user who has performed fingerprint entry in advance, that is, the fingerprint to be recognized passes the verification, the intelligent door lock can perform the unlocking operation, if the fingerprint data with the same fingerprint characteristic value to be recognized does not exist in the fingerprint database, it is determined that the user corresponding to the fingerprint to be recognized is not the user who has performed fingerprint entry in advance, and the intelligent door lock is kept in a locked state, so as to prevent the illegal user from unlocking the door lock.
Fig. 4 is a schematic diagram of another structure of the fingerprint identification device, which further includes a time acquisition module 30 and a detection module 40 on the basis of fig. 3, wherein the time acquisition module 30 is used for acquiring the current time; the detection module 40 is configured to detect whether the current time is within a preset time period; at this time, the comparison module 20 is further configured to, when the current time is within the preset time period, sequentially compare the feature values of the fingerprints to be identified with the feature values in a second fingerprint group, where the second fingerprint group is a set of feature values corresponding to B fingerprints with the highest verification frequency within the preset time period in the fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group.
In the actual use process, the verification frequency of some users in a fixed time period may be higher, for example, long-term overtime personnel or people who are accustomed to arriving early, but the overall verification frequency of the fingerprint feature values of the people may not be the highest; therefore, on the basis of setting the first fingerprint group, at least one second fingerprint group can be set, and each second fingerprint group is a set of characteristic values corresponding to B fingerprints with the highest verification frequency in the fingerprint database in different preset time periods, wherein B is a positive integer; certainly, in actual use, for the second fingerprint groups corresponding to different preset time periods, the number B of the fingerprint feature values contained in the second fingerprint groups may also be different, and the feature value of the same fingerprint may also exist in a plurality of second fingerprint groups at the same time.
After the acquisition module 10 acquires the fingerprint feature value to be identified, the current time is acquired by the time acquisition module 30, and the detecting module 40 is used to determine whether the current time is within a preset time period or a preset time period, and if the current time is within the preset time period, the comparison module 20 preferably compares the characteristic values of the fingerprint to be identified with the characteristic values of the second fingerprint group, since the number of fingerprint feature values within the second fingerprint group is small relative to the number of all fingerprints, when the comparison identification is carried out, the comparison result can be known more quickly, if a second fingerprint data exists in the second fingerprint group, if the characteristic value is the same as the fingerprint characteristic value to be identified, the fact that the user corresponding to the fingerprint characteristic value to be identified is the user who has performed fingerprint input in advance is proved, namely the fingerprint to be identified passes verification, and the intelligent door lock can be unlocked.
If the second fingerprint data does not exist in the second fingerprint group, or the current time is not within the preset time period, the comparison module 20 may compare the fingerprint feature value to be identified with the feature value in the first fingerprint group until the comparison result is determined, which is not repeated here.
In addition, the method of this embodiment may also have an implementation manner that, after the obtaining module 10 obtains the fingerprint feature value to be identified, the comparison module 20 compares the fingerprint feature value to be identified with the fingerprint in the first fingerprint group, and when the first fingerprint data does not exist in the first fingerprint group, the detection module 40 determines whether the fingerprint feature value is within the preset time period according to the current time, and when the fingerprint feature value is within the preset time period, the comparison module 20 compares the fingerprint feature value to be identified with the fingerprint feature value in the second fingerprint group; if the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified, determining that the fingerprint to be identified passes verification, and at the moment, improving the fingerprint identification efficiency; if the second fingerprint data does not exist in the second fingerprint group, or the current time is not within any preset time period, the comparison module 20 sequentially compares the fingerprint feature value to be identified with other fingerprint feature values in the fingerprint database except the first fingerprint group, and determines whether the fingerprint to be identified passes the verification based on the comparison result.
It should be noted that, in the actual use process, the fingerprint feature values in the second fingerprint group may be updated after a second preset period is set, for example, if the second preset period is one month, then, every other month, the verification frequency of each fingerprint in the fingerprint database in a preset time period is counted again, the B fingerprints with the highest verification frequency in the corresponding preset time period in the one month are taken as the fingerprints in the second fingerprint group, and the feature values are stored and compared preferentially according to the verification time when fingerprint identification is performed in the next month.
A fourth embodiment of the present disclosure provides a storage medium, which is mountable in any electronic device with a fingerprint identification function, especially an intelligent door lock, and is specifically a computer-readable medium storing a computer program, where the computer program is executed by a processor to implement the method provided in any embodiment of the present disclosure, and the method includes the following steps S41 to S43:
s41, acquiring a fingerprint characteristic value to be identified;
s42, comparing the fingerprint characteristic value to be identified with the characteristic values in a first fingerprint group in sequence, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in a fingerprint database, and A is a positive integer;
and S43, determining that the fingerprint to be identified passes the verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
The computer program is further executable by the processor to perform the steps of: and under the condition that the first fingerprint data does not exist in the first fingerprint group, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints except the first fingerprint group in the fingerprint database, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
The computer program is further executable by the processor to perform the steps of: and updating the fingerprint characteristic values stored in the first fingerprint group every a first preset period.
Before the computer program is executed by the processor to compare the characteristic value of the fingerprint to be identified with the characteristic value in the first fingerprint group in sequence, the processor also executes the following steps: acquiring current time; detecting whether the current time is within a preset time period; under the condition that the current time is within a preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with the highest verification frequency within the preset time period in a fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group.
After determining that the first fingerprint data is not present in the first fingerprint group, the computer program is further executed by the processor for: acquiring current time; detecting whether the current time is within a preset time period; under the condition that the current time is within a preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with the highest verification frequency within the preset time period in a fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and under the condition that the first fingerprint data does not exist in the second fingerprint group or the current time is not within the preset time period, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints in the fingerprint database except the first fingerprint group, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
The computer program is further executable by the processor to perform the steps of: and updating the fingerprint characteristic values stored in the second fingerprint group every second preset period.
This embodiment constitutes first fingerprint group with a plurality of fingerprint eigenvalues that verify the frequency is the highest in the fingerprint database, when acquireing and treating discernment fingerprint eigenvalue, preferentially uses the fingerprint eigenvalue of storage in the first fingerprint group to contrast, can carry out preferential identification to the higher fingerprint of verification frequency, shortens the verification time of effective fingerprint eigenvalue greatly to promote fingerprint identification's efficiency, promote user experience.
A fifth embodiment of the present disclosure provides an electronic device, which may be any electronic device with a fingerprint identification function, especially an intelligent door lock, and a schematic structural diagram of the electronic device is shown in fig. 5, where the electronic device at least includes a memory 100 and a processor 200, the memory 100 stores a computer program, and the processor 200 implements the method provided in any embodiment of the present disclosure when executing the computer program on the memory 100. Illustratively, the electronic device computer program steps are as follows S51-S55:
s51, acquiring a fingerprint characteristic value to be identified;
s52, comparing the fingerprint characteristic value to be identified with the characteristic values in a first fingerprint group in sequence, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in a fingerprint database, and A is a positive integer;
and S53, determining that the fingerprint to be identified passes the verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
The processor also executes the following computer program: and under the condition that the first fingerprint data does not exist in the first fingerprint group, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints except the first fingerprint group in the fingerprint database, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
The processor also executes the following computer program: and updating the fingerprint characteristic values stored in the first fingerprint group every a first preset period.
Before the processor compares the characteristic value of the fingerprint to be identified stored in the execution memory with the characteristic value in the first fingerprint group in sequence, the processor also executes the following computer program: acquiring current time; detecting whether the current time is within a preset time period; under the condition that the current time is within a preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with the highest verification frequency within the preset time period in a fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group.
In case no first fingerprint data is present in the first fingerprint group, the processor further executes the computer program: acquiring current time; detecting whether the current time is within a preset time period; under the condition that the current time is within a preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with the highest verification frequency within the preset time period in a fingerprint database, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and under the condition that the first fingerprint data does not exist in the second fingerprint group or the current time is not within the preset time period, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints in the fingerprint database except the first fingerprint group, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
The processor also executes the following computer program: and updating the fingerprint characteristic values stored in the second fingerprint group every second preset period.
This embodiment constitutes first fingerprint group with a plurality of fingerprint eigenvalues that verify the frequency is the highest in the fingerprint database, when acquireing and treating discernment fingerprint eigenvalue, preferentially uses the fingerprint eigenvalue of storage in the first fingerprint group to contrast, can carry out preferential identification to the higher fingerprint of verification frequency, shortens the verification time of effective fingerprint eigenvalue greatly to promote fingerprint identification's efficiency, promote user experience.
While the present disclosure has been described in detail with reference to the embodiments, the present disclosure is not limited to the specific embodiments, and those skilled in the art can make various modifications and alterations based on the concept of the present disclosure, and the modifications and alterations should fall within the scope of the present disclosure as claimed.
Claims (10)
1. A fingerprint identification method, comprising:
acquiring a fingerprint characteristic value to be identified;
sequentially comparing the characteristic values of the fingerprint to be identified with the characteristic values in a first fingerprint group, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in the fingerprint database, and A is a positive integer;
and determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
2. The fingerprint recognition method of claim 1, further comprising:
and under the condition that the first fingerprint data does not exist in the first fingerprint group, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints except the first fingerprint group in the fingerprint database, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
3. The fingerprint recognition method of claim 1, further comprising:
and updating the fingerprint characteristic values stored in the first fingerprint group every a first preset period.
4. The fingerprint identification method according to claim 1, wherein before comparing the characteristic value of the fingerprint to be identified with the characteristic values in the first fingerprint group in sequence, the method further comprises:
acquiring current time;
detecting whether the current time is within a preset time period;
under the condition that the current time is within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with highest verification frequency within the preset time period in the fingerprint database, and B is a positive integer;
determining that the fingerprint to be identified passes verification under the condition that the characteristic value of second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified;
and sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within a preset time period.
5. The fingerprint recognition method of claim 1, wherein in the absence of the first fingerprint data in the first fingerprint group, the method further comprises:
acquiring current time;
detecting whether the current time is within a preset time period;
under the condition that the current time is within the preset time period, sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in a second fingerprint group, wherein the second fingerprint group is a set of characteristic values corresponding to B fingerprints with highest verification frequency within the preset time period in the fingerprint database, and B is a positive integer;
determining that the fingerprint to be identified passes verification under the condition that the characteristic value of second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified;
and under the condition that the first fingerprint data does not exist in the second fingerprint group or the current time is not within a preset time period, sequentially comparing the characteristic value of the fingerprint to be identified with the characteristic values of other fingerprints in the fingerprint database except the first fingerprint group, and determining whether the fingerprint to be identified passes the verification based on the comparison result.
6. The fingerprint recognition method according to claim 4 or 5, further comprising:
and updating the fingerprint characteristic values stored in the second fingerprint group every second preset period.
7. A fingerprint recognition device, comprising:
the acquisition module is used for acquiring a fingerprint characteristic value to be identified;
the comparison module is used for sequentially comparing the characteristic values of the fingerprint to be identified with the characteristic values in a first fingerprint group, wherein the first fingerprint group is a set of characteristic values corresponding to A fingerprints with the highest verification frequency in the fingerprint database, and A is a positive integer; and determining that the fingerprint to be identified passes verification under the condition that the characteristic value of the first fingerprint data in the first fingerprint group is the same as the characteristic value of the fingerprint to be identified.
8. The fingerprint recognition device according to claim 7, further comprising:
the time acquisition module is used for acquiring the current time;
the detection module is used for detecting whether the current time is within a preset time period;
the comparison module is further configured to sequentially compare the feature values of the fingerprint to be identified with feature values in a second fingerprint group when the current time is within the preset time period, where the second fingerprint group is a set of feature values corresponding to B fingerprints in the fingerprint database that have the highest verification frequency within the preset time period, and B is a positive integer; determining that the fingerprint to be identified passes verification under the condition that the characteristic value of second fingerprint data in the second fingerprint group is the same as the characteristic value of the fingerprint to be identified; and sequentially comparing the characteristic values of the fingerprints to be identified with the characteristic values in the first fingerprint group under the condition that the second fingerprint data does not exist in the second fingerprint group or the current time is not within a preset time period.
9. A storage medium storing a computer program, characterized in that the computer program, when being executed by a processor, carries out the steps of the fingerprint recognition method according to any one of claims 1 to 6.
10. An electronic device comprising at least a memory, a processor, the memory having a computer program stored thereon, characterized in that the processor, when executing the computer program on the memory, implements the steps of the fingerprint recognition method according to any one of claims 1 to 6.
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