CN107729884A - Fingerprint identification method, mobile terminal and computer-readable recording medium - Google Patents
Fingerprint identification method, mobile terminal and computer-readable recording medium Download PDFInfo
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- CN107729884A CN107729884A CN201711178323.XA CN201711178323A CN107729884A CN 107729884 A CN107729884 A CN 107729884A CN 201711178323 A CN201711178323 A CN 201711178323A CN 107729884 A CN107729884 A CN 107729884A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1365—Matching; Classification
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Abstract
The invention discloses a kind of fingerprint identification method, mobile terminal and computer-readable recording medium.Fingerprint identification method includes：The fingerprint image of typing is obtained, and current finger print characteristic point is extracted to fingerprint image；Judge that current finger print characteristic point whether there is bad point；When the result judged is is, bad point is removed, avoids that bad point is matched with the fingerprint feature point to prestore and bad point is updated to new fingerprint feature point, if the result judged is no, current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.Thus the accuracy rate and degree of safety of fingerprint recognition can be improved.
Description
Technical field
The present invention relates to fingerprint identification technology field, more particularly to a kind of fingerprint identification method, mobile terminal and meter
Calculation machine readable storage medium storing program for executing.
Background technology
With awareness more and more higher of the people to information security, people will carry out various safeguard protections, for example, in various shiftings
Move in the operations such as the screen unlocking of terminal, the opening of some individual application, checkout payment, it is complete to be required to progress authentication ability
Into associative operation.And fingerprint almost turns into living things feature recognition because it has unchangeable property, uniqueness and convenience
Synonym.In today that safety requirements increasingly improves, fingerprint is unlocked as the hobby of each large user.
And due to each stamp orientation not exclusively, impetus difference can bring different degrees of deformation, again exist
Largely fuzzy fingerprints, and the self problem by mobile terminal, such as the damage etc. of inductor so that the fingerprint of typing there is also
Problem, it is difficult which results in fingerprint recognition, reduce the degree of accuracy of fingerprint recognition.
The content of the invention
On the one hand the embodiment of the present application provides a kind of fingerprint identification method, fingerprint identification method includes：Obtain typing
Fingerprint image, and the current finger print characteristic point is extracted to the fingerprint image；Judge whether the current finger print characteristic point deposits
In bad point；When the result judged is is, the bad point is removed, avoids the bad point from being matched with the fingerprint feature point to prestore
And the bad point is updated to new fingerprint feature point；If the result judged is no, by the current finger print characteristic point and in advance
The fingerprint feature point deposited is matched and updated.
On the other hand, the embodiment of the present application additionally provides a kind of mobile terminal, and mobile terminal includes：Acquisition module, it is used for
The fingerprint image of typing is obtained, and the current finger print characteristic point is extracted to the fingerprint image；Judge module, for judging
State current finger print characteristic point and whether there is bad point；Control module, during for the result that judges in the judge module to be, remove
The bad point, avoids that the bad point is matched with the fingerprint feature point to prestore and the bad point is updated to new fingerprint characteristic
Point, and the result that judge module judges as it is no when, current finger print characteristic point with the fingerprint feature point to prestore match and
Renewal.
On the other hand, the embodiment of the present application additionally provides a kind of mobile terminal, and mobile terminal includes processor and the place
The memory and input unit of device connection are managed, wherein：The input unit is used for the fingerprint image for obtaining typing；The storage
Device storage program data, described program data can realize the fingerprint recognition described in any one above by the computing device
Method.
On the other hand, the embodiment of the present application additionally provides a kind of computer-readable recording medium, computer-readable storage medium
Matter is stored with computer program, and the computer program can be performed to realize the fingerprint recognition side described in any one above
Method.
The embodiment of the present application is first before current finger print characteristic point is matched and updated with the fingerprint feature point to prestore
First judge that current finger print characteristic point whether there is bad point, and remove bad point when determining and bad point being present, it is possible thereby to avoid
Bad point is matched with the fingerprint feature point to prestore and bad point is updated to new fingerprint feature point, so as to improve fingerprint recognition
Accuracy rate and degree of safety.
Brief description of the drawings
In order to illustrate more clearly of the technical scheme in the embodiment of the present application, make required in being described below to embodiment
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present application, for
For those of ordinary skill in the art, on the premise of not paying creative work, other can also be obtained according to these accompanying drawings
Accompanying drawing.
Fig. 1 is a kind of schematic flow sheet of fingerprint identification method provided in an embodiment of the present invention；
Fig. 2 is a kind of structural representation of fingerprint provided in an embodiment of the present invention；
Fig. 3 is the structural representation of another fingerprint provided in an embodiment of the present invention；
Fig. 4 is the schematic flow sheet of another fingerprint identification method provided in an embodiment of the present invention；
Fig. 5 is the schematic flow sheet of another fingerprint identification method provided in an embodiment of the present invention；
Fig. 6 is the schematic flow sheet of another fingerprint identification method provided in an embodiment of the present invention；
Fig. 7 is a kind of structural representation of mobile terminal provided in an embodiment of the present invention；
Fig. 8 is the structural representation of another mobile terminal provided in an embodiment of the present invention；
Fig. 9 is the structural representation of another mobile terminal provided in an embodiment of the present invention；
Figure 10 is a kind of structural representation of computer-readable recording medium provided in an embodiment of the present invention.
Embodiment
With reference to the accompanying drawings and examples, this application is described in further detail.It is it is emphasized that following real
Apply example and be merely to illustrate this application, but this scope of the present application is not defined.Likewise, following examples are only book
The section Example of application and not all embodiments, those of ordinary skill in the art institute under the premise of creative work is not made
The all other embodiment obtained, belong to the scope of this application protection.
Term " first " in this application, " second ", " the 3rd " are only used for describing purpose, and it is not intended that instruction or
Imply relative importance or the implicit quantity for indicating indicated technical characteristic.Thus, " first ", " second ", " are defined
At least one this feature can be expressed or be implicitly included to three " feature.In this description of the present application, " multiple " are meant that
At least two, such as two, three etc., unless otherwise specifically defined.The directional finger of institute in this embodiment of the present application
Show that (such as up, down, left, right, before and after ...) is only used for explaining under a certain particular pose (as shown in drawings) between each part
Relative position relation, motion conditions etc., if the particular pose changes, directionality instruction is also correspondingly therewith
Change.In addition, term " comprising " and " having " and their any deformations, it is intended that cover non-exclusive include.Such as wrap
Contain the step of process, method, system, product or the equipment of series of steps or unit is not limited to list or unit,
But the step of alternatively also including not listing or unit, or alternatively also include for these processes, method, product or set
Standby intrinsic other steps or unit.
Referenced herein " embodiment " is it is meant that the special characteristic, structure or the characteristic that describe can wrap in conjunction with the embodiments
It is contained at least one embodiment of this application.The phrase, which occurs, in each position in the description might not each mean phase
Same embodiment, nor the independent or alternative embodiment with other embodiments mutual exclusion.Those skilled in the art are explicitly
Implicitly understand, embodiment described herein can be combined with other embodiments.
Significantly, since the appearance requirement of mobile terminal, fingerprint module more do it is smaller, no matter cause to be logged on
Typing fingerprint image can all occur identifying the problem of area is too small when typing fingerprint image is still registered.When registration typing fingerprint image
Fingerprint typing area is too small when picture, and whole finger print, which is not entirely included in the inside, may result in user and step on later
Record service stage discrimination is very low, that is, refusing sincere Frr can be very high, only when the fingerprint image of whole finger is all in registration typing
When, user little by little can also identify partially even if finger when in use.
But can not require that user's typing number is excessive when registration, typing number will excessively reduce Consumer's Experience,
Even if number is more again, if user does not pass through special training, it is also difficult to obtain whole finger print whole typing success.
Therefore, in the case that registration typing fingerprint image is not complete, existing fingerprint recognition is generally carried by repetition learning
Pinpoint accuracy.Specifically, during the follow-up use of user, when there is the higher fingerprint image of some quality, just this is referred to
Print image is stored in updating to the fingerprint template storehouse of user, while some ropy fingerprint moulds are also deleted in fingerprint template storehouse
Plate.By constantly using, learning, fingerprint template storehouse is constantly updated, can be constantly to improve fingerprint template storehouse, Yong Hu
During follow-up use, the fingerprint stored in fingerprint template storehouse becomes closer to user's real time fingerprint, and refusing sincere FRR will be more next
It is lower.
But above-mentioned learning algorithm exist one it is fatal the problem of：When fingerprint module storehouse goes out during the use of user
Existing bad point, or the surface cap of mobile terminal have microcrack and produce bad point, for example fingerprint pressing is overweight, and fingerprint module receives
Electrostatic damage etc. can all cause fingerprint module bad point to produce.And what the fingerprint image at bad point was usually fixed.When bad point
When number is excessive, learning algorithm also learns the image of bad point to enter fingerprint template storehouse.Fingerprint template storehouse is with mixing bad point figure
As being updated, the measured fingerprint of original matter is caused to become the fingerprint with bad point.Fingerprint in fingerprint template storehouse exists a lot
Bad point, unblock image below is also with same bad point.Now because image is fixed, anybody typing solution at bad point
The fingerprint image of lock, the fingerprint image in itself and the fingerprint template storehouse with bad point compares, because the similarity at bad point is very high,
From the matching principle of characteristic point, more than similar threshold values, it can unlock.Therefore it will cause any people can be by fingerprint solution
Lock, greatly reduces the accuracy rate of unblock and the degree of safety of user profile.The present invention will provide a kind of fingerprint identification method and
Mobile terminal, to solve the above problems, referring specifically to following examples.
Referring to Fig. 1, Fig. 1 is a kind of flowage structure schematic diagram of fingerprint identification method provided in an embodiment of the present invention.Such as
Shown in Fig. 1, the fingerprint identification method of the present embodiment is further comprising the steps of：
Step S11：The fingerprint image of typing is obtained, and current finger print characteristic point is extracted to fingerprint image.
Fingerprint includes fingerprint lines, and fingerprint lines is not continuous, smooth straight, but often occurs interrupting, divides
Fork or turnover.Breakpoint, bifurcation and the turning point formed respectively by interruption, bifurcated and turnover can be fingerprint feature point.
Fingerprint feature point provides the confirmation of fingerprint uniqueness.The parameter of fingerprint feature point includes direction, and (node can
With towards certain direction), curvature (speed that description fingerprint ridge orientation changes), (position of node passes through x/y coordinates for position
Can be absolute or relative to triangulation point or characteristic point to describe).
This step can obtain fingerprint image by fingerprint sensor, and wherein acquisition modes may include scratching formula and pressing
Formula.
The acquisition modes of the current finger print characteristic point of this step are specific as follows：Fingerprint image is subjected to following pre- place first
Reason, including：Fingerprint enhancement, fingerprint image region detection, the fingerprint orientation in fingerprint image and frequence estimation, fingerprint image
As binaryzation, fingerprint image refine.Then from pretreated fingerprint image, the crestal line data of fingerprint are obtained.Finally from finger
Current finger print characteristic point needed for the crestal line extracting data fingerprint recognition of line.
Step S12：Judge that current finger print characteristic point whether there is bad point.Wherein, specifically by current finger print characteristic point with
The fingerprint feature point being pre-stored in fingerprint masterplate is compared to judge.Specific determination methods may include following two：
The first, bad point is judged whether by the characteristics of image corresponding to current finger print characteristic point.
Second, bad point is judged whether by the capacitance present value of pixel corresponding to current finger print characteristic point.
Specific determination methods refer to the embodiment provided hereinafter.
Also referring to Fig. 2 and Fig. 3, wherein, Fig. 2 is the structural representation of the normal fingerprints of storage, and Fig. 3 is going out for storage
The structural representation of fingerprint after existing bad point.As shown in Fig. 2 in the case of fingerprint is normal, during due to each typing fingerprint
Posture is different, therefore the fingerprint feature point that the fingerprint image of typing is extracted every time is different.After there is bad point, because bad
Image is fixed at point, as shown in figure 3, the cross striped in image 3.1 to 3.4 is exactly bad point concentration zones.Now, no matter
It is the fingerprint image of whose typing unblock, the fingerprint image in itself and the fingerprint template storehouse with bad point compares, because at bad point
Similarity is very high, from the matching principle of characteristic point, more than similar threshold values, can unlock.Therefore any people will be caused all may be used
By unlocked by fingerprint, to greatly reduce the accuracy rate of unblock and the degree of safety of user profile.Therefore need will be bad for this step
Point identifies.
In step s 12, if the result judged is yes, step S13 is jumped to, if the result judged is no, is redirected
To step S14.
Step S13：Remove bad point, avoid bad point matched with the fingerprint feature point to prestore and bad point be updated to it is new
Fingerprint feature point.
Step S14：Current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.
In this step, if current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or
Equal to default similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image with
The quality of the fingerprint image to prestore, it can be judged by fingerprint feature point, ought if current fingerprint image quality is higher
Relatively poor fingerprint image in the fingerprint image renewal fingerprint masterplate of preceding typing.
It is possible thereby to avoid that bad point is matched with the fingerprint feature point to prestore and bad point is updated to new fingerprint characteristic
Point, so as to improve the accuracy rate of fingerprint recognition and degree of safety.
Referring to Fig. 4, Fig. 4 is the schematic flow sheet of another fingerprint identification method provided in an embodiment of the present invention.Such as Fig. 4
Shown, the fingerprint identification method of the present embodiment comprises the following steps：
Step S21：The fingerprint image of typing is obtained, and current finger print characteristic point is extracted to fingerprint image.The tool of this step
Gymnastics is made as it was noted above, will not be repeated here.
Step S22：Whether the number for judging identical image feature to be present in same position exceedes default frequency threshold value.
The present embodiment mainly judges whether bad point by the characteristics of image corresponding to current finger print characteristic point.When
When the panel of mobile terminal typing fingerprint image is cover-plate glass or is ceramic, easily influenceed by external force and to occur some small
Crack, caused by this is extraneous physical factor, but the now chip of fingerprint collecting, such as previously described fingerprint sensing
Device is again no bad, and now hardware can not detect.For the crackle on cover-plate glass or ceramics, in image algorithm
The detection of identical image is arranged to, if detecting that the current finger print characteristic point extracted in fingerprint image has phase in same position
Number with characteristics of image exceedes default frequency threshold value, then is judged as that the fingerprint feature point in the region has bad point, will not go
For matching and updating fingerprint template.The same section is removed when forming image.
Wherein, default frequency threshold value can be the half of the quantity of the fingerprint image of storage.
In step S22, if the result judged is yes, step S23 is jumped to, if the result judged is no, is redirected
To step S24.
Step S23：Remove bad point, avoid bad point matched with the fingerprint feature point to prestore and bad point be updated to it is new
Fingerprint feature point.
Further, judge whether image area corresponding to bad point exceeds default area threshold, and in the result of judgement
Stop fingerprint recognition during to be.Such as fingerprint will be stopped when image area corresponding to bad point exceedes the 10% of fingerprint image area
Identification.
Step S24：Current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.
In this step, if current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or
Equal to default similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image with
The quality of the fingerprint image to prestore, it can be judged by fingerprint feature point, ought if current fingerprint image quality is higher
Relatively poor fingerprint image in the fingerprint image renewal fingerprint masterplate of preceding typing.
It is possible thereby to avoid that bad point is matched with the fingerprint feature point to prestore and bad point is updated to new fingerprint characteristic
Point, so as to improve the accuracy rate of fingerprint recognition and degree of safety.
Referring to Fig. 5, Fig. 5 is the schematic flow sheet of another fingerprint identification method provided in an embodiment of the present invention.Such as Fig. 5
Shown, the fingerprint identification method of the present embodiment comprises the following steps：
Step S31：The fingerprint image of typing is obtained, and current finger print characteristic point is extracted to fingerprint image.The tool of this step
Gymnastics is made as it was noted above, will not be repeated here.
Step S32：Judge corresponding to the characteristics of image corresponding to current finger print characteristic point and the fingerprint feature point to prestore
Whether the similarity of characteristics of image exceedes default similarity threshold.
The present embodiment judges whether bad point again by the characteristics of image corresponding to current finger print characteristic point.But
Unlike embodiment above：The present embodiment is that the similarity of characteristics of image is judged, as it was noted above, defeated in fingerprint
It is fashionable, because each pressing dynamics of user and direction etc. can not possibly be identical, even therefore same user, its is every
The fingerprint image of secondary typing is also impossible to identical, and the fingerprint image of bad point is fixed, and the present embodiment is based on this
Distinctive points judge that bad point whether there is.Wherein, default similarity threshold can be the 90%-100% of the fingerprint image of storage.
In step s 32, if the result judged is yes, step S33 is jumped to, if the result judged is no, is redirected
To step S34.
Step S33：Remove bad point, avoid bad point matched with the fingerprint feature point to prestore and bad point be updated to it is new
Fingerprint feature point.
Further, judge whether image area corresponding to bad point exceeds default area threshold, and in the result of judgement
Stop fingerprint recognition during to be.Such as fingerprint will be stopped when image area corresponding to bad point exceedes the 10% of fingerprint image area
Identification.
Step S34：Current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.
In this step, if current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or
Equal to default similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image with
The quality of the fingerprint image to prestore, it can be judged by fingerprint feature point, ought if current fingerprint image quality is higher
Relatively poor fingerprint image in the fingerprint image renewal fingerprint masterplate of preceding typing.
It is possible thereby to avoid that bad point is matched with the fingerprint feature point to prestore and bad point is updated to new fingerprint characteristic
Point, so as to improve the accuracy rate of fingerprint recognition and degree of safety.
Referring to Fig. 6, Fig. 6 is the schematic flow sheet of another fingerprint identification method provided in an embodiment of the present invention.Such as Fig. 6
Shown, the fingerprint identification method of the present embodiment comprises the following steps：
Step S41：The fingerprint image of typing is obtained, and current finger print characteristic point is extracted to fingerprint image.The tool of this step
Gymnastics is made as it was noted above, will not be repeated here.
Step S42：Judge the capacitance present value of pixel corresponding to current finger print characteristic point and the difference of the capacitance to prestore
Whether exceed default range threshold, and be defined as bad point when the result judged is is.
Fingerprint module bad point would generally occur during the use of user because of misoperation, for example fingerprint is by pressing through
Weight, fingerprint module can all be caused fingerprint module bad point to produce by electrostatic damage etc..And the fingerprint image at bad point is fixed
's.These bad points can be identified by hardware circuit, because the capacitance of pixel corresponding to bad point and normal
The capacitance of pixel can be poor far, it is easy to identifies.Therefore this step is pre- by the way that the capacitance of normal pixel is carried out
First store, then be compared to sentence with the capacitance to prestore by the capacitance present value of pixel corresponding to current finger print characteristic point
It is disconnected to whether there is bad point.
In step S42, if the result judged is yes, step S43 is jumped to, if the result judged is no, is redirected
To step S44.
Step S43：Remove bad point, avoid bad point matched with the fingerprint feature point to prestore and bad point be updated to it is new
Fingerprint feature point.
Specifically, because the bad point of the present embodiment is by chip, for example, fingerprint sensor damage and occur, because
This, can thoroughly sleep chip corresponding to the pixel, not use chip its data.
Further, judge whether the quantity of bad point exceeds default amount threshold, and stop when the result judged is is
Only fingerprint recognition.
Amount threshold can be total figure as the 10% of pixel, if more than thinking ensure safety if amount threshold
Property, it is stopped.
Step S44：Current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.
In this step, if current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or
Equal to default similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image with
The quality of the fingerprint image to prestore, it can be judged by fingerprint feature point, ought if current fingerprint image quality is higher
Relatively poor fingerprint image in the fingerprint image renewal fingerprint masterplate of preceding typing.
It is possible thereby to avoid that bad point is matched with the fingerprint feature point to prestore and bad point is updated to new fingerprint characteristic
Point, so as to improve the accuracy rate of fingerprint recognition and degree of safety.
Referring to Fig. 7, Fig. 7 is a kind of structural representation of mobile terminal.As shown in fig. 7, the mobile terminal of the present embodiment
60 include acquisition module 61, judge module 62 and control module 63.
Wherein, acquisition module 61 is used for the fingerprint image for obtaining typing, and extracts current finger print characteristic point to fingerprint image.
Fingerprint image can be obtained by fingerprint sensor, wherein acquisition modes may include scratching formula and push type.
The acquisition modes of current finger print characteristic point are specific as follows：Fingerprint image is pre-processed as follows first, including：Refer to
Print image enhancing, fingerprint image region detection, the fingerprint orientation in fingerprint image and frequence estimation, Fingerprint Image Binarization,
Fingerprint image refines.Then from pretreated fingerprint image, the crestal line data of fingerprint are obtained.Finally from the crestal line number of fingerprint
The current finger print characteristic point to be taken the fingerprint in needed for identification.
Judge module 62 is used to judge that current finger print characteristic point whether there is bad point.Wherein, specifically can be special by current finger print
Sign point is compared to judge with the fingerprint feature point being pre-stored in fingerprint masterplate.Specific determination methods may include following two：
The first, bad point is judged whether by the characteristics of image of current finger print characteristic point.
Second, bad point is judged whether by the capacitance present value of pixel corresponding to current finger print characteristic point.
The specific step of both the above determination methods is as it was noted above, will not be repeated here.
Control module 63 is used for when the result that judge module 62 judges is as being, removal bad point, avoids bad point and prestores
Fingerprint feature point is matched and bad point is updated to new fingerprint feature point.
More than in the first determination methods, judge module 62 determines whether image area corresponding to bad point exceeds
Default area threshold, control module 63 stop fingerprint recognition when the result that judge module 62 judges is is.Such as in bad point
Corresponding image area will stop fingerprint recognition when exceeding the 10% of fingerprint image area.
More than in second of determination methods, judge module 62 determines whether the quantity of bad point exceeds default number
Threshold value is measured, control module 63 stops fingerprint recognition when the result that judge module 62 judges is is.For example, amount threshold can be total
The 10% of image slices vegetarian refreshments, think ensure security if amount threshold is exceeded, be stopped.
Control module 63 further the result that judge module 62 judges as it is no when, i.e., when bad point be present, will currently refer to
Line characteristic point is matched and updated with the fingerprint feature point to prestore.
If current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or equal to it is default
Similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image and the fingerprint to prestore
The quality of image, it can be judged by fingerprint feature point, if current fingerprint image quality is higher, by the finger of current typing
Relatively poor fingerprint image in print image renewal fingerprint masterplate.
Referring to Fig. 8, Fig. 8 is the structural representation of another mobile terminal provided in an embodiment of the present invention, such as Fig. 8 institutes
Show, the mobile terminal 70 of the present embodiment includes processor 71, the memory 72 and input unit 73 that are connected with processor 71.
Wherein, input unit 73 is used for the fingerprint image for obtaining typing.Input unit 73 for example can be touching for mobile terminal
Control screen.Fingerprint sensor is may be provided with touch screen, fingerprint image is obtained by fingerprint sensor, wherein acquisition modes can wrap
Include scratching formula and push type.
The storage program data of memory 72, routine data can be performed by processor 71 to realize that previously described fingerprint is known
Other method.
Specifically, the fingerprint image extraction current finger print characteristic point that processor 71 obtains to input unit 73.Currently refer to
The acquisition modes of line characteristic point are specific as follows：Fingerprint image is pre-processed as follows first, including：Fingerprint enhancement, refer to
Fingerprint orientation and frequence estimation, Fingerprint Image Binarization, fingerprint image refinement in print image region detection, fingerprint image.
Then from pretreated fingerprint image, the crestal line data of fingerprint are obtained.Finally from the crestal line extracting data fingerprint of fingerprint
Current finger print characteristic point needed for identification.
Processor 71 determines whether that current finger print characteristic point whether there is bad point.Wherein, specifically can be special by current finger print
Sign point is compared to judge with the fingerprint feature point being pre-stored in fingerprint masterplate.Specific determination methods may include following two：
The first, bad point is judged whether by the characteristics of image of current finger print characteristic point.
Second, bad point is judged whether by the capacitance present value of pixel corresponding to current finger print characteristic point.
The specific step of both the above determination methods is as it was noted above, will not be repeated here.
Processor 71 further when the result judged is is, removes bad point, avoids bad point and the fingerprint feature point to prestore
Matched and bad point is updated to new fingerprint feature point.
More than in the first determination methods, whether processor 71 determines whether image area corresponding to bad point beyond pre-
If area threshold, stop fingerprint recognition when the result judged is is.Such as exceed fingerprint in image area corresponding to bad point
Image area 10% when will stop fingerprint recognition.
More than in second of determination methods, processor 71 determines whether the quantity of bad point exceeds default quantity
Threshold value, stop fingerprint recognition when the result judged is is.For example, amount threshold can be total figure as the 10% of pixel, if super
Cross amount threshold then to think ensure security, be stopped.
Processor 71 further the result judged as it is no when, i.e., when bad point be present, by current finger print characteristic point with it is pre-
The fingerprint feature point deposited is matched and updated.
If current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or equal to it is default
Similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image and the fingerprint to prestore
The quality of image, it can be judged by fingerprint feature point, if current fingerprint image quality is higher, by the finger of current typing
Relatively poor fingerprint image in print image renewal fingerprint masterplate.
Referring to Fig. 9, Fig. 9 is the structural representation of another mobile terminal provided in an embodiment of the present invention, such as Fig. 9 institutes
Show, the mobile terminal 800 includes RF circuits 810, memory 820, input block 830, display unit 840, sensor 850, sound
Frequency circuit 860, wifi module 870, processor 880, power supply 890 etc..Wherein, RF circuits 810, memory 820, input block
830th, display unit 840, sensor 850, voicefrequency circuit 860, wifi module 870 are connected with processor 880, and power supply 890 is used for
Electric energy is provided for whole mobile terminal 80.
Specifically, RF circuits 810 are used to receiving and sending signal；Memory 820 is used for data storage command information；It is defeated
Enter unit 830 to be used to input information, can specifically include other input equipments 832 such as contact panel 831 and Cao Zuoanjian；It is aobvious
Show that unit 840 can then include display panel 841 etc.；Sensor 850 includes infrared sensor, laser sensor, fingerprint sensing
Device etc., for detecting user's approach signal, distance signal and touching signals etc.；Loudspeaker 861 and microphone (or Mike
Wind) 862 electrically connected by voicefrequency circuit 860 with processor 880, for receiving and sending voice signal；Wifi module 870 is then used
In reception and transmitting wifi signals.
Input block 831 is additionally operable to obtain the fingerprint image of typing.
Processor 880 is used to extract current finger print characteristic point to the fingerprint image that input block 831 obtains.Specific method is such as
It is described previously, it will not be repeated here.
Processor 880 determines whether that current finger print characteristic point whether there is bad point.Wherein, specifically can be special by current finger print
Sign point is compared to judge with the fingerprint feature point being pre-stored in fingerprint masterplate.Specific determination methods may include following two：
The first, bad point is judged whether by the characteristics of image of current finger print characteristic point.
Second, bad point is judged whether by the capacitance present value of pixel corresponding to current finger print characteristic point.
The specific step of both the above determination methods is as it was noted above, will not be repeated here.
Processor 880 further when the result judged is is, removes bad point, avoids bad point and the fingerprint feature point to prestore
Matched and bad point is updated to new fingerprint feature point.
More than in the first determination methods, processor 880 determines whether image area corresponding to bad point exceeds
Default area threshold, stop fingerprint recognition when the result judged is is.Such as exceed in image area corresponding to bad point and refer to
Print image area 10% when will stop fingerprint recognition.
More than in second of determination methods, processor 880 determines whether the quantity of bad point exceeds default number
Threshold value is measured, stops fingerprint recognition when the result judged is is.For example, amount threshold can be total figure as the 10% of pixel, if
Then think ensure security more than amount threshold, be stopped.
Processor 880 further the result judged as it is no when, i.e., when bad point be present, by current finger print characteristic point with it is pre-
The fingerprint feature point deposited is matched and updated.
If current finger print characteristic point matched with the fingerprint feature point to prestore after similarity be more than or equal to it is default
Similar threshold value, then the match is successful, carries out the unblock operation of correlation.And determine whether current fingerprint image and the fingerprint to prestore
The quality of image, it can be judged by fingerprint feature point, if current fingerprint image quality is higher, by the finger of current typing
Relatively poor fingerprint image in print image renewal fingerprint masterplate.
Memory 820 is then used to store the information such as the operational order of processor 880.Specifically operated on processor 880
Flow, equally refer to the detailed description in above method embodiment.
Referring to Fig. 10, Figure 10 is a kind of structural representation for computer-readable recording medium that the embodiment of the present application provides
Figure.
The computer-readable recording medium 90 is stored with computer program 91, the computer program 91 can be performed with
The fingerprint identification method illustrated in above-described embodiment is realized, is just repeated no more herein.
As skilled in the art to understand, the computer-readable recording medium 90 can be the physical stores such as USB flash disk, CD
The virtual storage medium such as medium or server.
Embodiments of the invention are the foregoing is only, are not intended to limit the scope of the invention, it is every to utilize this hair
The equivalent structure or equivalent flow conversion that bright specification and accompanying drawing content are made, or directly or indirectly it is used in other related skills
Art field, is included within the scope of the present invention.
Claims (11)
1. a kind of fingerprint identification method, it is characterised in that the fingerprint identification method includes：
The fingerprint image of typing is obtained, and current finger print characteristic point is extracted to the fingerprint image；
Judge that the current finger print characteristic point whether there is bad point；
When the result judged is is, remove the bad point, avoid the bad point from being matched with the fingerprint feature point to prestore with
And the bad point is updated to new fingerprint feature point；
If the result judged is no, the current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.
2. fingerprint identification method according to claim 1, it is characterised in that described to judge that the current finger print characteristic point is
No have the step of bad point and include：
Bad point is judged whether by the characteristics of image corresponding to the current finger print characteristic point.
3. fingerprint identification method according to claim 2, it is characterised in that described to pass through the current finger print characteristic point pair
The step of characteristics of image answered is to judge whether bad point includes：
Judge the characteristics of image corresponding to the current finger print characteristic point and the characteristics of image corresponding to the fingerprint feature point to prestore
Similarity whether exceed default similarity threshold, and be defined as bad point when the result judged is is.
4. fingerprint identification method according to claim 2, it is characterised in that described to pass through the current finger print characteristic point institute
The step of corresponding characteristics of image is to judge whether bad point includes：
Whether the number for judging identical image feature to be present in same position exceedes default frequency threshold value, and in the result of judgement
It is defined as bad point during to be.
5. according to the fingerprint identification method described in any one of claim 3 or 4, it is characterised in that the fingerprint identification method is also
Including：
Judge whether the area of the bad point exceeds default area threshold, and stop fingerprint when the result judged is is and know
Not.
6. fingerprint identification method according to claim 1, it is characterised in that described to judge that the current finger print characteristic point is
No have the step of bad point and include：
Bad point is judged whether by the capacitance present value of pixel corresponding to the current finger print characteristic point.
7. fingerprint identification method according to claim 6, it is characterised in that described to pass through the current finger print characteristic point pair
The step of capacitance present value for the pixel answered is to judge whether bad point includes：
Judge whether the difference of capacitance of the capacitance present value of pixel with prestoring corresponding to the current finger print characteristic point exceeds
Default range threshold, and it is defined as bad point when the result judged is is.
8. fingerprint identification method according to claim 7, it is characterised in that the fingerprint identification method also includes：
Judge whether the quantity of the bad point exceeds default amount threshold, and stop fingerprint when the result judged is is and know
Not.
9. a kind of mobile terminal, it is characterised in that the mobile terminal includes：
Acquisition module, the current finger print characteristic point is extracted for obtaining the fingerprint image of typing, and to the fingerprint image；
Judge module, for judging that the current finger print characteristic point whether there is bad point；
Control module, during for the result that judges in the judge module to be, remove the bad point, avoid the bad point with it is pre-
The fingerprint feature point deposited is matched and the bad point is updated to new fingerprint feature point, and judge in the judge module
When being as a result no, the current finger print characteristic point is matched and updated with the fingerprint feature point to prestore.
A kind of 10. mobile terminal, it is characterised in that the storage that the mobile terminal includes processor, is connected with the processor
Device and input unit, wherein：
The input unit is used for the fingerprint image for obtaining typing；
The memory storage routine data, described program data can realize claim 1-8 by the computing device
Fingerprint identification method described in any one.
11. a kind of computer-readable recording medium, it is characterised in that the computer-readable recording medium storage has computer journey
Sequence, the computer program can be performed to realize the fingerprint identification method described in claim 1-8 any one.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108898089A (en) * | 2018-06-25 | 2018-11-27 | 联想(北京)有限公司 | A kind of characteristic recognition method and electronic equipment |
| CN110929548A (en) * | 2018-09-19 | 2020-03-27 | 北京小米移动软件有限公司 | Fingerprint identification method, device, equipment and storage medium |
| CN111144323A (en) * | 2019-12-28 | 2020-05-12 | 广东智冠信息技术股份有限公司 | Palm vein biological feature recognition registry self-adaptive change method |
| CN111241314A (en) * | 2020-01-13 | 2020-06-05 | 北京迈格威科技有限公司 | Fingerprint bottom library input method and device, electronic equipment and storage medium |
| CN113406429A (en) * | 2021-07-30 | 2021-09-17 | 佛山市墨纳森智能科技有限公司 | Electronic metering device detection method and device, storage medium and electronic equipment |
| CN113762080A (en) * | 2021-08-05 | 2021-12-07 | 当趣网络科技(杭州)有限公司 | Large screen end control method and device without fingerprint prerecording and readable storage medium |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105469083A (en) * | 2015-11-13 | 2016-04-06 | 广东欧珀移动通信有限公司 | Fingerprint image processing method, fingerprint image processing device and terminal equipment |
| CN105631443A (en) * | 2016-03-11 | 2016-06-01 | 广东欧珀移动通信有限公司 | Fingerprint template updating method and terminal device |
| CN105809133A (en) * | 2016-03-08 | 2016-07-27 | 广东欧珀移动通信有限公司 | Fingerprint feature information updating method and device |
| CN105808108A (en) * | 2016-05-27 | 2016-07-27 | 广东欧珀移动通信有限公司 | Unlocking control method and mobile terminal |
| CN105956553A (en) * | 2016-04-28 | 2016-09-21 | 广东欧珀移动通信有限公司 | Unlocking method and mobile terminal |
| CN105991997A (en) * | 2015-03-06 | 2016-10-05 | 成都方程式电子有限公司 | Capacitive image sensor dead pixel real-time positioning method |
-
2017
- 2017-11-22 CN CN201711178323.XA patent/CN107729884A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105991997A (en) * | 2015-03-06 | 2016-10-05 | 成都方程式电子有限公司 | Capacitive image sensor dead pixel real-time positioning method |
| CN105469083A (en) * | 2015-11-13 | 2016-04-06 | 广东欧珀移动通信有限公司 | Fingerprint image processing method, fingerprint image processing device and terminal equipment |
| CN105809133A (en) * | 2016-03-08 | 2016-07-27 | 广东欧珀移动通信有限公司 | Fingerprint feature information updating method and device |
| CN105631443A (en) * | 2016-03-11 | 2016-06-01 | 广东欧珀移动通信有限公司 | Fingerprint template updating method and terminal device |
| CN105956553A (en) * | 2016-04-28 | 2016-09-21 | 广东欧珀移动通信有限公司 | Unlocking method and mobile terminal |
| CN105808108A (en) * | 2016-05-27 | 2016-07-27 | 广东欧珀移动通信有限公司 | Unlocking control method and mobile terminal |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108898089A (en) * | 2018-06-25 | 2018-11-27 | 联想(北京)有限公司 | A kind of characteristic recognition method and electronic equipment |
| CN110929548A (en) * | 2018-09-19 | 2020-03-27 | 北京小米移动软件有限公司 | Fingerprint identification method, device, equipment and storage medium |
| CN110929548B (en) * | 2018-09-19 | 2023-11-03 | 北京小米移动软件有限公司 | Fingerprint identification method, device, equipment and storage medium |
| CN111144323A (en) * | 2019-12-28 | 2020-05-12 | 广东智冠信息技术股份有限公司 | Palm vein biological feature recognition registry self-adaptive change method |
| CN111241314A (en) * | 2020-01-13 | 2020-06-05 | 北京迈格威科技有限公司 | Fingerprint bottom library input method and device, electronic equipment and storage medium |
| CN113406429A (en) * | 2021-07-30 | 2021-09-17 | 佛山市墨纳森智能科技有限公司 | Electronic metering device detection method and device, storage medium and electronic equipment |
| CN113406429B (en) * | 2021-07-30 | 2021-11-12 | 佛山市墨纳森智能科技有限公司 | Electronic metering device detection method and device, storage medium and electronic equipment |
| CN113762080A (en) * | 2021-08-05 | 2021-12-07 | 当趣网络科技(杭州)有限公司 | Large screen end control method and device without fingerprint prerecording and readable storage medium |
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