CN110390231A - Fingerprint identification module abnormality determination method, device, storage medium and electronic equipment - Google Patents
Fingerprint identification module abnormality determination method, device, storage medium and electronic equipment Download PDFInfo
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- CN110390231A CN110390231A CN201810362614.2A CN201810362614A CN110390231A CN 110390231 A CN110390231 A CN 110390231A CN 201810362614 A CN201810362614 A CN 201810362614A CN 110390231 A CN110390231 A CN 110390231A
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- fingerprint
- identification module
- fingerprint image
- pixel
- fingerprint identification
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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
- G06V40/1347—Preprocessing; Feature extraction
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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
Abstract
This disclosure relates to a kind of fingerprint identification module abnormality determination method, device, storage medium and electronic equipment.This method comprises: when collecting the first fingerprint image that user is applied on fingerprint identification module, determine target area similar with the gray value of the second fingerprint image in first fingerprint image, wherein, second fingerprint image is the last collected fingerprint image before first fingerprint image；According to the target area, determine the fingerprint identification module with the presence or absence of abnormal.Thus, it is whether abnormal that fingerprint identification module can quickly and accurately be determined, such as, whether adhesive tape with conductive pattern is covered on fingerprint identification module, so as to effectively fingerprint identification module be avoided to be cracked, the reliability and safety of fingerprint identification module are improved, and then has ensured the personal secrets and property safety of user.
Description
Technical field
This disclosure relates to field of electronic device, and in particular, to a kind of fingerprint identification module abnormality determination method, device,
Storage medium and electronic equipment.
Background technique
Electronic equipment at this stage is provided with fingerprint identification module mostly, and user is convenient to by the fingerprint identification module
Realize the functions such as unlock, payment.But when being covered with the adhesive tape with conductive pattern in unlocked by fingerprint module, if legitimate user
It is unlocked or is paid by fingerprint identification module up to preset times, which is cracked, later, the legal use
Any finger at family and the finger or any object of all other men can be unlocked by the fingerprint identification module
Or payment.The principle that fingerprint identification module is cracked is, can be in the local number of terminal when legitimate user's typing fingerprint for the first time
According to one legitimate user's fingerprint template of preservation in library；When again unlock or pay when, terminal can by collected finger print information with
Legitimate user's fingerprint template that lane database saves is compared, can when the two reaches preset matching degree (for example, 30%)
To complete unlock or payment.And after being sticked on the fingerprint identification module of terminal has the adhesive tape with conductive pattern, due to fingerprint
Algorithm has fingerprint self-learning function, and therefore, when legitimate user is unlocked or is paid by fingerprint identification module, fingerprint is calculated
Method is conductive pattern to be added in local data base in legitimate user's fingerprint template for saving, later, any as legitimate user
When finger and all other men or any object are unlocked or are paid by the fingerprint identification module, fingerprint identification module
After recognizing above-mentioned conductive pattern, unlock or payment can be realized.It can be seen that fingerprint identification module is easy to be cracked,
Reliability and safety will not know where to begin.
Summary of the invention
In order to solve the problems, such as present in the relevant technologies, the disclosure provide a kind of fingerprint identification module abnormality determination method,
Device, storage medium and electronic equipment.
To achieve the goals above, the disclosure provides a kind of line identification module abnormality determination method, comprising:
When collecting the first fingerprint image that user is applied on fingerprint identification module, first fingerprint image is determined
In target area similar with the gray value of the second fingerprint image, wherein second fingerprint image be in first fingerprint
The last collected fingerprint image before image；
According to the target area, determine the fingerprint identification module with the presence or absence of abnormal.
Optionally, target area similar with the gray value of the second fingerprint image in the determination first fingerprint image
Domain, comprising:
Obtain the first object pixel for meeting preset condition in first fingerprint image, wherein the preset condition
Gray scale absolute value of the difference between the corresponding points in second fingerprint image is less than default gray difference threshold and in non-
Background area, the non-background area are the pixel group for being less than default gray threshold by gray value in first fingerprint image
At region；
It is full when existing in the eight neighborhood pixel of the first object pixel for each first object pixel
When the pixel of the foot preset condition, the first object pixel is determined as the second target pixel points；
The region being made of second target pixel points is determined as the target area.
Optionally, described according to the target area, determine the fingerprint identification module with the presence or absence of abnormal, comprising:
Obtain the pixel sum in the target area and the pixel sum in first fingerprint image；
When in the target area pixel sum and the ratio of the pixel sum in first fingerprint image it is big
When preset threshold, it is abnormal to determine that the fingerprint identification module exists.
Optionally, the method also includes:
At least one of when determining that the fingerprint identification module deposits when abnormal, perform the following operation:
Outputting alarm information；
Terminal where forbidding the fingerprint identification module executes the fingerprint self study operation based on first fingerprint image；
Terminal performance objective operation where forbidding the fingerprint identification module, the object run are that user applies described the
It is intended to the operation for enabling the terminal carry out when one fingerprint image.
The disclosure also provides a kind of fingerprint identification module abnormity determining device, comprising:
Determining module, for determining institute when collecting the first fingerprint image that user is applied on fingerprint identification module
State target area similar with the gray value of the second fingerprint image in the first fingerprint image, wherein second fingerprint image is
The last collected fingerprint image before first fingerprint image；
Determination module, the target area for being determined according to the determining module, determines the fingerprint recognition mould
Block is with the presence or absence of abnormal.
Optionally, the determining module includes:
First acquisition submodule is configured as obtaining the first object picture for meeting preset condition in first fingerprint image
Vegetarian refreshments, wherein the preset condition is that the gray scale absolute value of the difference between the corresponding points in second fingerprint image is less than
It presets gray difference threshold and is in non-background area, the non-background area is small by gray value in first fingerprint image
In the region of the pixel composition of default gray threshold；
First determines submodule, the first object pixel for getting for each first acquisition submodule
Point will be described when there is the pixel for meeting the preset condition in the eight neighborhood pixel of the first object pixel
First object pixel is determined as the second target pixel points；
Second determines submodule, is configured as second object pixel that will be determined by the described first determining submodule
The region of point composition is determined as the target area.
Optionally, the determination module includes:
Second acquisition submodule, it is total for obtaining the pixel in the target area that the determining module is determined
Pixel sum in several and described first fingerprint image；
Third determines submodule, for when the pixel in the target area that second acquisition submodule is got
When the total ratio with the pixel sum in first fingerprint image is greater than preset threshold, the fingerprint identification module is determined
There are exceptions.
Optionally, described device further include:
Execution module carries out following behaviour for determining that the fingerprint identification module is deposited when abnormal when the determination module
At least one of make:
Outputting alarm information；
Terminal where forbidding the fingerprint identification module executes the fingerprint self study operation based on first fingerprint image；
Terminal performance objective operation where forbidding the fingerprint identification module, the object run are that user applies described the
It is intended to the operation for enabling the terminal carry out when one fingerprint image.
The disclosure also provides a kind of computer readable storage medium, is stored thereon with computer program, and the program is processed
The step of fingerprint identification module abnormality determination method that the disclosure provides is realized when device executes.
The disclosure also provides a kind of electronic equipment, comprising:
Fingerprint identification module；
The computer readable storage medium that the disclosure provides；And
One or more processor, for executing the program in the computer readable storage medium.
Through the above technical solutions, can be applied on fingerprint identification module according to current collected user first refers to
Print image and last time collected second fingerprint image, determine the gray value with the second fingerprint image from the first fingerprint image
Similar target area according to the target area, determines fingerprint identification module with the presence or absence of abnormal later.In this way, can be fast
Whether whether extremely speed accurately determine fingerprint identification module, for example, being covered with conductive pattern on fingerprint identification module
Adhesive tape improve the reliability and safety of fingerprint identification module so as to effectively fingerprint identification module be avoided to be cracked,
And then the personal secrets and property safety of user are ensured.
Other feature and advantage of the disclosure will the following detailed description will be given in the detailed implementation section.
Detailed description of the invention
Attached drawing is and to constitute part of specification for providing further understanding of the disclosure, with following tool
Body embodiment is used to explain the disclosure together, but does not constitute the limitation to the disclosure.In the accompanying drawings:
Fig. 1 is a kind of flow chart of fingerprint identification module abnormality determination method shown according to an exemplary embodiment.
Fig. 2 is a kind of flow chart of the method for determining target area shown according to an exemplary embodiment.
Fig. 3 be it is shown according to an exemplary embodiment a kind of according to target area, determine whether fingerprint identification module is deposited
In the flow chart of abnormal method.
Fig. 4 is a kind of flow chart of the fingerprint identification module abnormality determination method shown according to another exemplary embodiment.
Fig. 5 is a kind of block diagram of fingerprint identification module abnormity determining device shown according to an exemplary embodiment.
Fig. 6 is a kind of block diagram of the fingerprint identification module abnormity determining device shown according to another exemplary embodiment.
Fig. 7 is a kind of block diagram of the fingerprint identification module abnormity determining device shown according to another exemplary embodiment.
Fig. 8 is a kind of block diagram of the fingerprint identification module abnormity determining device shown according to another exemplary embodiment.
Fig. 9 is the block diagram of a kind of electronic equipment shown according to an exemplary embodiment.
Specific embodiment
It is described in detail below in conjunction with specific embodiment of the attached drawing to the disclosure.It should be understood that this place is retouched
The specific embodiment stated is only used for describing and explaining the disclosure, is not limited to the disclosure.
Fig. 1 is a kind of flow chart of fingerprint identification module abnormality determination method shown according to an exemplary embodiment.Such as
Shown in Fig. 1, this method be may comprise steps of.
In a step 101, when collecting the first fingerprint image that user is applied on fingerprint identification module, first is determined
Target area similar with the gray value of the second fingerprint image in fingerprint image.
In the disclosure, which can be the last collected before above-mentioned first fingerprint image
Fingerprint image, i.e. the first fingerprint image are current collected fingerprint image, and the second fingerprint image is last time collected fingerprint
Image.
In addition, when being covered with the adhesive tape with conductive pattern on fingerprint identification module, since user's finger presses every time
Angle, displacement, pressure on fingerprint identification module can not be all consistent completely, and the adhesive tape will not move, so above-mentioned
The image grayscale in the fingerprint identification module region where collected conductive pattern every time is consistent.It therefore, can be by working as
Preceding collected first fingerprint image and last time collected second fingerprint image are compared, to determine in the first fingerprint image
With the presence or absence of target area similar with the gray value of the second fingerprint image, and existing in determining above-mentioned first fingerprint image should
When target area, according to the target area, determine above-mentioned fingerprint identification module with the presence or absence of abnormal.
Specifically, above-mentioned first fingerprint image can be obtained by step 1011~step 1013 shown in Fig. 2
In target area similar with the gray value of the second fingerprint image.
In step 1011, the first object pixel for meeting preset condition in the first fingerprint image is obtained.
In the disclosure, which can be the gray scale difference between the corresponding points in above-mentioned second fingerprint image
Absolute value is less than default gray difference threshold (for example, the default gray difference threshold is 5) and is in non-background area, wherein this is non-
Background area is the region for being less than the pixel of default gray threshold by gray value in the first fingerprint image and forming.Specifically,
Above-mentioned first object pixel can be obtained in the following manner:
(1) firstly, when collecting the first fingerprint image, the second fingerprint image can be first obtained, illustratively, in above-mentioned finger
When line identification module collects the second fingerprint image, above-mentioned second fingerprint image can be stored by a global variable array
Picture, in this way, can obtain above-mentioned second by accessing the global variable array after collecting above-mentioned first fingerprint image and refer to
Print image；
(2) each picture in the first gray value and the second fingerprint image of each pixel in the first fingerprint image is obtained respectively
Second gray value of vegetarian refreshments, wherein the acquisition modes of above-mentioned the second gray value of first sum of the grayscale values are those skilled in the art institute
It is well known, it repeats no more in the disclosure；
(3) for each pixel in the first fingerprint image, calculate separately the pixel the first gray value and its
Gray scale difference between corresponding points in second fingerprint image is (wherein, since the first fingerprint image and the second fingerprint image are by same
What one fingerprint identification module acquired, so the pixel size of the two is consistent)；
(4) by the above-mentioned gray scale absolute value of the difference in above-mentioned first fingerprint image be less than above-mentioned default gray difference threshold and
The pixel (meeting above-mentioned preset condition) that first gray value is less than above-mentioned default gray threshold is determined as first object pixel
Point.
In addition, it is necessary to illustrating is that above-mentioned default gray difference threshold and default gray threshold can be value set by user,
The empirical value that can be default, is not especially limited in the disclosure.
In step 1012, for each first object pixel, when in the eight neighborhood pixel of first object pixel
When in the presence of the pixel for meeting preset condition, which is determined as the second target pixel points.
In step 1013, the region being made of the second target pixel points is determined as target area.
In the disclosure, when through the above steps 1011 determine first object pixel after, it is possible to determine that above-mentioned first
Target pixel points whether be it is discrete be distributed in above-mentioned first fingerprint image, in one embodiment, can be by sentencing respectively
Whether fixed each first object pixel is the mode of isolated pixel to determine the first object pixel in above-mentioned target area
Whether point is discrete distribution.Specifically, it can be directed to above-mentioned each first object pixel, determine the first object respectively
It is above-mentioned with the presence or absence of meeting in the eight neighborhood pixel (eight i.e. adjacent with first object pixel pixels) of pixel
The pixel of preset condition determines the first object pixel periphery with the presence or absence of other first object pixels, when in judgement
State at least one in eight neighborhood pixel be first object pixel when, can determine that above-mentioned first object pixel is not
Isolated pixel, at this point it is possible to determine that the first object pixel is the second target pixel points；And when the above-mentioned eight neighborhood of judgement
When each pixel in pixel is not first object pixel, it can determine that above-mentioned first object pixel is isolated
Pixel, at this point it is possible to determine that the first object pixel is not the second target pixel points.Finally, by being determined by above-mentioned
The region of each second target pixel points composition is determined as target area.
Fig. 2 is returned, in a step 102, according to target area, determines fingerprint identification module with the presence or absence of abnormal.
In the disclosure, it determines in above-mentioned first fingerprint image in above-mentioned steps 101 there are when above-mentioned target area, it can
First to determine whether the area of the target area and the ratio of the gross area of above-mentioned first fingerprint image are greater than preset threshold,
In, which is greater than or equal to smallest match rate when fingerprint authentication success, and illustratively, which is 30%, when
When the ratio of the gross area of the area of the target area and the first fingerprint image is greater than above-mentioned preset threshold, above-mentioned mesh can be determined
Marking region may be conductive pattern, that is to say, that the area of the conductive pattern and the gross area ratio of the first fingerprint image are greater than
Or be equal to preset threshold, that is, it is greater than or equal to smallest match rate when fingerprint authentication success, at this point it is possible to determine fingerprint recognition mould
Block exists abnormal.
In one embodiment, the face of the target area can be characterized with the pixel sum in above-mentioned target area
It accumulates, and characterizes the gross area of first fingerprint image with the pixel sum in above-mentioned first fingerprint image.Specifically,
, according to above-mentioned target area, above-mentioned fingerprint identification module can be determined by step 1021 shown in Fig. 3 and step 1022
With the presence or absence of exception.
In step 1021, obtains the pixel sum in target area and the pixel in the first fingerprint image is total
Number.
In step 1022, when the ratio of the pixel sum in the pixel sum and the first fingerprint image in target area
When value is greater than preset threshold, it is abnormal to determine that fingerprint identification module exists.
It, can be with after the pixel sum in the pixel sum for getting above-mentioned target area and the first fingerprint image
Determine whether the ratio of the two is greater than above-mentioned preset threshold.When the pixel sum and the first fingerprint image for determining target area
In pixel sum ratio be greater than above-mentioned preset threshold when, it can determine the area and the first fingerprint image of target area
The ratio of the gross area be greater than the preset threshold, at this point it is possible to which it is abnormal to determine that fingerprint identification module exists；When determining target area
Pixel sum and the pixel sum in the first fingerprint image ratio less than or equal to above-mentioned preset threshold, it can
When determining that the ratio of the area of target area and the gross area of the first fingerprint image is less than or equal to the preset threshold, at this point, can
To determine fingerprint identification module, there is no abnormal.
In addition, it is necessary to which explanation, above-mentioned preset threshold can be value set by user, it is also possible to the experience of default
Value, is not especially limited in the disclosure.
Through the above technical solutions, can be applied on fingerprint identification module according to current collected user first refers to
Print image and last time collected second fingerprint image, determine the gray value with the second fingerprint image from the first fingerprint image
Similar target area according to the target area, determines fingerprint identification module with the presence or absence of abnormal later.In this way, can be fast
Whether whether extremely speed accurately determine fingerprint identification module, for example, being covered with conductive pattern on fingerprint identification module
Adhesive tape improve the reliability and safety of fingerprint identification module so as to effectively fingerprint identification module be avoided to be cracked,
And then the personal secrets and property safety of user are ensured.
Fig. 4 is a kind of flow chart of the fingerprint identification module abnormality determination method shown according to another exemplary embodiment.
As shown in figure 4, the above method can also include the following steps.
In the disclosure, it when above-mentioned steps 102 determine that fingerprint identification module is deposited when abnormal, can follow the steps below
At least one:
In step 103, outputting alarm information.
It in the disclosure, can be with outputting alarm information, illustratively, with bullet when determining that fingerprint identification module deposits when abnormal
Terminal where the forms such as window, short message, notification message, chat messages to the fingerprint identification module sends the warning information, in this way,
It finds fingerprint identification module exception in time convenient for user and takes appropriate measures, so as to effectively avoid because of fingerprint recognition mould
The problems such as leakage of user information caused by block is cracked, property are damaged.
At step 104, terminal executes the fingerprint self study based on the first fingerprint image where forbidding fingerprint identification module
Operation.
In the disclosure, fingerprint algorithm used by fingerprint identification module usually has self-learning function, therefore, work as determination
Fingerprint identification module is deposited when abnormal, and terminal executes the fingerprint based on the first fingerprint image where can forbidding fingerprint identification module
Self study operation, it can fingerprint algorithm is forbidden the image in above-mentioned target area to be added the legal use that local data base saves
In the fingerprint template of family, in this way, it is possible to prevente effectively from fingerprint identification module is cracked, and then improve the personal secrets and wealth of user
Produce safety.
In step 105, terminal performance objective operation where forbidding fingerprint identification module.
In the disclosure, it is intended to enable above-mentioned terminal progress when which can apply the first fingerprint image for user
Operation, illustratively, the object run are unlock operation, delivery operation etc..It, can be with when determining that fingerprint identification module deposits when abnormal
Terminal executes above-mentioned object run where directly forbidding fingerprint identification module, in this way, this refers to even if fingerprint identification module is cracked
Terminal where line identification module does not execute corresponding object run yet, further improves the personal secrets and property peace of user
Entirely.
In addition, when above-mentioned steps 102 determine that fingerprint identification module there is no when exception, can execute following steps 106 (such as
Shown in Fig. 4).
In step 106, fingerprint verification operation is carried out, and in fingerprint authentication success, performance objective is operated and is based on
The fingerprint self study of first fingerprint image operates.
In the disclosure, when determining that fingerprint identification module is not present abnormal, fingerprint verification operation can be carried out.It is specific next
It says, the first fingerprint image can be matched with the fingerprint image template of legitimate user, and in first fingerprint image and close
When the fingerprint image template of method user matches, show fingerprint authentication success, executing above-mentioned object run, (user applies first and refers to
It is intended to the operation for enabling above-mentioned terminal carry out when print image)；In the fingerprint image template phase of first fingerprint image and legitimate user
When matching, shows that fingerprint authentication fails, do not execute any operation.
In addition, in the success of above-mentioned fingerprint authentication, can execute and be based on to promote the accuracy rate of fingerprint recognition and efficiency
The fingerprint self study of above-mentioned first fingerprint image operates, i.e., is added to above-mentioned conjunction using the relevant information of above-mentioned first fingerprint image
In the fingerprint image template of method user.
Fig. 5 is a kind of block diagram of fingerprint identification module abnormity determining device shown according to an exemplary embodiment.Reference
Fig. 5, the device 500 may include: determining module 501, in collect that user is applied on fingerprint identification module first
When fingerprint image, target area similar with the gray value of the second fingerprint image in first fingerprint image is determined, wherein institute
Stating the second fingerprint image is the last collected fingerprint image before first fingerprint image；Determination module 502 is used
In the target area determined according to the determining module 501, determine the fingerprint identification module with the presence or absence of abnormal.
Optionally, it as shown in fig. 6, the determining module 501 may include: the first acquisition submodule 5011, is configured as
Obtain the first object pixel for meeting preset condition in first fingerprint image, wherein the preset condition be with it is described
Gray scale absolute value of the difference between corresponding points in second fingerprint image is less than default gray difference threshold and is in non-background area
Domain, the non-background area are the area for being less than the pixel of default gray threshold by gray value in first fingerprint image and forming
Domain；First determines submodule 5012, the first object for getting for each first acquisition submodule 5011
Pixel will when there is the pixel for meeting the preset condition in the eight neighborhood pixel of the first object pixel
The first object pixel is determined as the second target pixel points；Second determines submodule 5013, and being configured as will be by described the
One determines that the region for second target pixel points composition that submodule 5012 is determined is determined as the target area.
Optionally, as shown in fig. 7, the determination module 502 may include: the second acquisition submodule 5021, for obtaining
Pixel sum in the target area that the determining module 501 is determined and the picture in first fingerprint image
Vegetarian refreshments sum；Third determines submodule 5022, the target area for getting when second acquisition submodule 5021
In pixel sum and first fingerprint image in pixel sum ratio greater than preset threshold when, determine the finger
Line identification module exists abnormal.
Fig. 8 is a kind of block diagram of the fingerprint identification module abnormity determining device shown according to another exemplary embodiment.Ginseng
According to Fig. 8, above-mentioned apparatus 500 can also include: execution module 503, for determining the fingerprint recognition when the determination module 502
At least one of module is deposited when abnormal, perform the following operation: outputting alarm information；Forbid the fingerprint identification module place
Terminal executes the fingerprint self study operation based on first fingerprint image；Terminal executes where forbidding the fingerprint identification module
Object run, the object run are that user is intended to the operation for enabling the terminal carry out when applying first fingerprint image.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
Fig. 9 is the block diagram of a kind of electronic equipment 900 shown according to an exemplary embodiment.As shown in figure 9, the electronics is set
Standby 900 may include: processor 901, memory 902.The electronic equipment 900 can also include multimedia component 903, input/
Export one or more of (I/O) interface 904 and communication component 905 and fingerprint identification module 906.
Wherein, processor 901 is used to control the integrated operation of the fingerprint identification module 906 in the electronic equipment 900, with complete
At all or part of the steps in above-mentioned fingerprint identification module abnormality determination method.Memory 902 is for storing various types
Data to support the operation in the electronic equipment 900, these data for example may include for grasping on the electronic equipment 900
The instruction of any application or method of work and the relevant data of application program, for example, contact data, transmitting-receiving disappear
Breath, picture, audio, video etc..The memory 902 can by any kind of volatibility or non-volatile memory device or
Their combination is realized, such as static random access memory (Static Random Access Memory, abbreviation SRAM),
Electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory,
Abbreviation EEPROM), Erasable Programmable Read Only Memory EPROM (Erasable Programmable Read-Only Memory, letter
Claim EPROM), programmable read only memory (Programmable Read-Only Memory, abbreviation PROM), read-only memory
(Read-Only Memory, abbreviation ROM), magnetic memory, flash memory, disk or CD.Multimedia component 903 can wrap
Include screen and audio component.Wherein screen for example can be touch screen, and audio component is used for output and/or input audio signal.
For example, audio component may include a microphone, microphone is for receiving external audio signal.The received audio signal can
To be further stored in memory 902 or be sent by communication component 905.Audio component further includes at least one loudspeaker,
For output audio signal.I/O interface 904 provides interface, other above-mentioned interfaces between processor 901 and other interface modules
Module can be keyboard, mouse, button etc..These buttons can be virtual push button or entity button.Communication component 905 is used for
Wired or wireless communication is carried out between the electronic equipment 900 and other equipment.Wireless communication, such as Wi-Fi, bluetooth, near field are logical
Believe (Near Field Communication, abbreviation NFC), 2G, 3G or 4G or they one or more of combination, because
This corresponding communication component 905 may include: Wi-Fi module, bluetooth module, NFC module.
In one exemplary embodiment, electronic equipment 900 can be by one or more application specific integrated circuit
(Application Specific Integrated Circuit, abbreviation ASIC), digital signal processor (Digital
Signal Processor, abbreviation DSP), digital signal processing appts (Digital Signal Processing Device,
Abbreviation DSPD), programmable logic device (Programmable Logic Device, abbreviation PLD), field programmable gate array
(Field Programmable Gate Array, abbreviation FPGA), controller, microcontroller, microprocessor or other electronics member
Part is realized, for executing above-mentioned fingerprint identification module abnormality determination method.
In a further exemplary embodiment, a kind of computer readable storage medium including program instruction is additionally provided, it should
The step of above-mentioned fingerprint identification module abnormality determination method is realized when program instruction is executed by processor.For example, the computer
Readable storage medium storing program for executing can be the above-mentioned memory 902 including program instruction, and above procedure instruction can be by electronic equipment 900
Device 901 is managed to execute to complete above-mentioned fingerprint identification module abnormality determination method.
The preferred embodiment of the disclosure is described in detail in conjunction with attached drawing above, still, the disclosure is not limited to above-mentioned reality
The detail in mode is applied, in the range of the technology design of the disclosure, a variety of letters can be carried out to the technical solution of the disclosure
Monotropic type, these simple variants belong to the protection scope of the disclosure.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, it can be combined in any appropriate way.In order to avoid unnecessary repetition, the disclosure to it is various can
No further explanation will be given for the combination of energy.
In addition, any combination can also be carried out between a variety of different embodiments of the disclosure, as long as it is without prejudice to originally
Disclosed thought equally should be considered as disclosure disclosure of that.
Claims (10)
1. a kind of fingerprint identification module abnormality determination method characterized by comprising
When collecting the first fingerprint image that user is applied on fingerprint identification module, determine in first fingerprint image with
The similar target area of the gray value of second fingerprint image, wherein second fingerprint image is in first fingerprint image
Before the last collected fingerprint image；
According to the target area, determine the fingerprint identification module with the presence or absence of abnormal.
2. the method according to claim 1, wherein in the determination first fingerprint image with the second fingerprint
The similar target area of the gray value of image, comprising:
Obtain the first object pixel for meeting preset condition in first fingerprint image, wherein the preset condition be with
The gray scale absolute value of the difference between corresponding points in second fingerprint image is less than default gray difference threshold and is in non-background
Region, the non-background area are that the pixel by gray value in first fingerprint image less than default gray threshold forms
Region；
For each first object pixel, meet institute when existing in the eight neighborhood pixel of the first object pixel
When stating the pixel of preset condition, the first object pixel is determined as the second target pixel points；
The region being made of second target pixel points is determined as the target area.
3. determining that the fingerprint is known the method according to claim 1, wherein described according to the target area
Other module is with the presence or absence of abnormal, comprising:
Obtain the pixel sum in the target area and the pixel sum in first fingerprint image；
When the ratio of the pixel sum in the pixel sum and first fingerprint image in the target area is greater than in advance
If when threshold value, it is abnormal to determine that the fingerprint identification module exists.
4. method according to any one of claim 1-3, which is characterized in that the method also includes:
At least one of when determining that the fingerprint identification module deposits when abnormal, perform the following operation:
Outputting alarm information；
Terminal where forbidding the fingerprint identification module executes the fingerprint self study operation based on first fingerprint image；
Terminal performance objective operation where forbidding the fingerprint identification module, the object run are that user applies first finger
It is intended to the operation for enabling the terminal carry out when print image.
5. a kind of fingerprint identification module abnormity determining device characterized by comprising
Determining module, for when collecting the first fingerprint image that user is applied on fingerprint identification module, determining described
Target area similar with the gray value of the second fingerprint image in one fingerprint image, wherein second fingerprint image is in institute
The last collected fingerprint image before stating the first fingerprint image；
Determination module, the target area for being determined according to the determining module determine that the fingerprint identification module is
It is no to there is exception.
6. device according to claim 5, which is characterized in that the determining module includes:
First acquisition submodule is configured as obtaining the first object pixel for meeting preset condition in first fingerprint image
Point, wherein the preset condition is that the gray scale absolute value of the difference between the corresponding points in second fingerprint image is less than in advance
If gray difference threshold and be in non-background area, the non-background area be less than by gray value in first fingerprint image
The region of the pixel composition of default gray threshold；
First determines submodule, the first object pixel for getting for each first acquisition submodule,
When there is the pixel for meeting the preset condition in the eight neighborhood pixel of the first object pixel, by described first
Target pixel points are determined as the second target pixel points；
Second determines submodule, is configured as the second target pixel points group that will be determined by the described first determining submodule
At region be determined as the target area.
7. device according to claim 5, which is characterized in that the determination module includes:
Second acquisition submodule, for obtain the pixel in the target area that the determining module is determined sum, with
And the pixel sum in first fingerprint image；
Third determines submodule, for when the pixel sum in the target area that second acquisition submodule is got
When being greater than preset threshold with the ratio of the pixel sum in first fingerprint image, determine that the fingerprint identification module exists
It is abnormal.
8. the device according to any one of claim 5-7, which is characterized in that described device further include:
Execution module is performed the following operation for determining that the fingerprint identification module is deposited when abnormal when the determination module
At least one:
Outputting alarm information；
Terminal where forbidding the fingerprint identification module executes the fingerprint self study operation based on first fingerprint image；
Terminal performance objective operation where forbidding the fingerprint identification module, the object run are that user applies first finger
It is intended to the operation for enabling the terminal carry out when print image.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
The step of any one of claim 1-4 the method is realized when row.
10. a kind of electronic equipment characterized by comprising
Fingerprint identification module；
Computer readable storage medium described in claim 9；And
One or more processor, for executing the program in the computer readable storage medium.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106096361A (en) * | 2016-05-31 | 2016-11-09 | 广东欧珀移动通信有限公司 | A kind of unlocked by fingerprint method and mobile terminal |
| CN106096353A (en) * | 2016-05-27 | 2016-11-09 | 广东欧珀移动通信有限公司 | A kind of solution lock control method and equipment |
| CN106203266A (en) * | 2016-06-28 | 2016-12-07 | 比亚迪股份有限公司 | The extracting method of image extreme point and device |
| CN106485125A (en) * | 2016-10-21 | 2017-03-08 | 上海与德信息技术有限公司 | A kind of fingerprint identification method and device |
| CN106650572A (en) * | 2016-09-12 | 2017-05-10 | 深圳芯启航科技有限公司 | Method for assessing quality of fingerprint image |
| US20180108018A1 (en) * | 2016-10-13 | 2018-04-19 | Kona I Co., Ltd. | Fingerprint Recognition Card and Method for Operating Fingerprint Recognition Card |
-
2018
- 2018-04-20 CN CN201810362614.2A patent/CN110390231B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106096353A (en) * | 2016-05-27 | 2016-11-09 | 广东欧珀移动通信有限公司 | A kind of solution lock control method and equipment |
| CN106096361A (en) * | 2016-05-31 | 2016-11-09 | 广东欧珀移动通信有限公司 | A kind of unlocked by fingerprint method and mobile terminal |
| CN106203266A (en) * | 2016-06-28 | 2016-12-07 | 比亚迪股份有限公司 | The extracting method of image extreme point and device |
| CN106650572A (en) * | 2016-09-12 | 2017-05-10 | 深圳芯启航科技有限公司 | Method for assessing quality of fingerprint image |
| US20180108018A1 (en) * | 2016-10-13 | 2018-04-19 | Kona I Co., Ltd. | Fingerprint Recognition Card and Method for Operating Fingerprint Recognition Card |
| CN106485125A (en) * | 2016-10-21 | 2017-03-08 | 上海与德信息技术有限公司 | A kind of fingerprint identification method and device |
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