CN105227306B - A kind of identity identifying method and device - Google Patents
A kind of identity identifying method and device Download PDFInfo
- Publication number
- CN105227306B CN105227306B CN201410234344.9A CN201410234344A CN105227306B CN 105227306 B CN105227306 B CN 105227306B CN 201410234344 A CN201410234344 A CN 201410234344A CN 105227306 B CN105227306 B CN 105227306B
- Authority
- CN
- China
- Prior art keywords
- sequence
- axis direction
- power spectrum
- coordinate axis
- change
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 44
- 230000001133 acceleration Effects 0.000 claims abstract description 224
- 230000035479 physiological effects, processes and functions Effects 0.000 claims abstract description 153
- 238000001228 spectrum Methods 0.000 claims abstract description 146
- 238000005070 sampling Methods 0.000 claims abstract description 85
- 230000003595 spectral effect Effects 0.000 claims abstract description 41
- 238000012512 characterization method Methods 0.000 claims abstract description 36
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 35
- 230000008859 change Effects 0.000 claims description 124
- 230000009466 transformation Effects 0.000 claims description 27
- 238000001914 filtration Methods 0.000 claims description 18
- 230000003044 adaptive effect Effects 0.000 claims description 17
- 238000001514 detection method Methods 0.000 claims description 14
- 238000012545 processing Methods 0.000 claims description 14
- 238000000844 transformation Methods 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000006870 function Effects 0.000 description 12
- 238000010586 diagram Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 230000003068 static effect Effects 0.000 description 5
- 230000002349 favourable effect Effects 0.000 description 4
- 238000003825 pressing Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000012804 iterative process Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Landscapes
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses a kind of identity identifying method and devices, it include: the physiology vibration feature for obtaining sampling holder, physiology vibration feature is to acquire the acceleration information sequence of characterization physiology vibration at least once in preset duration when receiving the trigger signal of acquisition physiology vibration feature；The power spectral density for determining the acceleration information sequence of sampling holder, as sampled power spectrum density；When needing to carry out authentication to certification holder, the physiology vibration feature of certification holder is obtained, and determines the current power spectrum density of the acceleration information sequence of certification holder；It according to preset matching algorithm, determines whether current power spectrum density sequence and sampled power spectrum density sequence match, obtains matching result；According to the matching result, the legitimacy of certification holder's identity is determined.Using above scheme provided by the invention, the safety and accuracy of authentication are improved.
Description
Technical field
The present invention relates to field of communication technology more particularly to a kind of identity identifying methods and device.
Background technique
In order to guarantee safety and the privacy of the information in terminal that terminal user uses, it usually needs to terminal user
Identity authenticated, at present to terminal user carry out authentication include following methods:
Cipher authentication: terminal user is arranged personal identification number and is stored in terminal, and user inputs password before using terminal, eventually
Hold password input to user to be compared in the local password saved, if the password that inputs of user with saved it is close
Code is identical, and the authentication success to the user allows the user using the terminal, otherwise, the user forbidden to use the terminal.
The personal identification number of user setting can be the character string password including number and character.
Dynamic gesture certification: terminal built-in acceleration transducer, terminal user do one by my habit in triplicate and move
State gesture, for example, standardized circle, terminal acquire three groups of acceleration generated by the dynamic gesture to terminal user's handheld terminal in the sky
Data sequence is spent, is handled using three group acceleration information sequences of the dynamic time warping algorithm to acquisition, determines one
Threshold value, as preset threshold value.When user wants using terminal, terminal user does the dynamic gesture set, acceleration sensing
Device acquires this acceleration information sequence, the acceleration information sequence that is acquired using dynamic time warping algorithm to this and most
The three groups of acceleration information sequences just acquired are handled, and determine this threshold value, by this threshold value and preset threshold value
It is matched according to certain rule, it is successful to the authentication of the user if successful match, allow the user to use the end
Otherwise the user is forbidden to use the terminal in end.
It is above-mentioned existing that terminal user, since password is easy to be stolen or forgets, make in identity authentication method
It is poor with cipher authentication method safety.Using dynamic gesture authentication method, due to terminal user do dynamic gesture every time can
Poor repeatability causes the accuracy of this method also poor.
Summary of the invention
The embodiment of the present invention provides a kind of identity identifying method and device, uses to solve to exist in the prior art terminal
The problem of the safety of family authentication and accuracy difference.
The embodiment of the present invention provides a kind of identity identifying method, comprising:
The physiology for obtaining sampling holder shakes feature, and the physiology shakes feature for when the terminal receives acquisition institute
When stating the trigger signal of physiology vibration feature, acquisition characterizes the acceleration information sequence of physiology vibration at least once in preset duration
Column；
The power spectral density for determining the acceleration information sequence of the sampling holder, as sampled power spectrum density；
When needing to carry out authentication to certification holder, the physiology for obtaining the certification holder shakes feature, and
Determine the current power spectrum density of the acceleration information sequence of the certification holder；
According to preset matching algorithm, determines the current power spectrum density sequence and the sampled power spectrum density sequence is
No matching, obtains matching result；
According to the matching result, the legitimacy of certification holder's identity is determined.
Using method provided in an embodiment of the present invention, due to the acceleration information sequence using characterization physiology vibration feature into
The acceleration information sequence of row authentication, favorable repeatability, the characterization physiology vibration of acquisition is accurate, and then improves identity and recognize
The accuracy of card, and the acceleration information for characterizing physiology vibration is difficult to be replicated, and also improves the safety of authentication.
Further, the physiology for obtaining sampling holder shakes feature, specifically includes:
When receiving the trigger signal of acquisition physiology vibration feature, characterization of the sampling holder in preset duration is obtained
The raw acceleration data sequence of physiology vibration；
Denoising disposal is carried out to the raw acceleration data sequence, obtains characterizing the sampling and holds human physiology vibration
Acceleration information sequence.
Further, in the raw acceleration data sequence for obtaining characterization physiology vibration of the sampling holder in preset duration
Before column, further includes:
Whether the physiology vibration feature of detection sampling holder is stable；
When determining that the physiology vibration feature is stablized, instruction information, the instruction letter are sent to the sampling holder
Breath is used to indicate the trigger signal of sampling holder's triggering collection physiology vibration feature.
Further, the power spectral density for determining the acceleration information sequence of the sampling holder, specifically includes:
For the acceleration information subsequence of each change in coordinate axis direction of each acceleration information sequence, by the acceleration
Data subsequence is divided into the second preset quantity acceleration information subsegment；
Fourier transformation processing is carried out to acceleration information subsegment described in every section；
The power spectrum of acceleration information subsegment after determining all sections of Fourier transformations of each change in coordinate axis direction respectively is flat
Equal value sequence, using the corresponding power spectrum sequence of average of three change in coordinate axis direction as this group of acceleration information sequence
Power spectrum degree series.
Further, the preset matching algorithm is adaptive morphology filter device algorithm；The physiology shakes feature
When receiving the trigger signal for acquiring the physiology vibration feature, the physiology vibration of one acquisition characterization adds in preset duration
Speed data sequence；
According to adaptive morphology filter device algorithm, the current power spectrum density sequence and sampled power spectrum are determined
Whether density sequence matches, and specifically includes:
Shape filtering operation is carried out to the current power spectrum density sequence of each change in coordinate axis direction respectively, obtains the reference axis
The filtered current power spectrum density sequence in direction；
The filtered current power spectrum density of each change in coordinate axis direction and identical with the change in coordinate axis direction is determined respectively
The root-mean-square error of the sampled power spectrum density sequence of change in coordinate axis direction；
Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
Further, the preset matching algorithm is adaptive morphology filter device algorithm；The physiology shakes feature
When receiving the trigger signal for acquiring the physiology vibration feature, the physiology vibration of multi collect characterization adds in preset duration
Speed data sequence；
According to adaptive morphology filter device algorithm, the current power spectrum density sequence and sampled power spectrum are determined
Whether density sequence matches, and specifically includes:
Shape filtering operation is carried out to the current power spectrum density sequence of each change in coordinate axis direction respectively, obtains the reference axis
The filtered current power spectrum density sequence in direction；
The power spectral density of same coordinate axis direction in the first preset quantity sampled power spectrum density sequence is determined respectively
Sequence of average；
Determine respectively each change in coordinate axis direction filtered current power spectrum density sequence and with the change in coordinate axis direction phase
The root-mean-square error of the power spectral density sequence of average of same change in coordinate axis direction；
Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
Further, it according to the matching result, determines the legitimacy of certification holder's identity, specifically includes:
When the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold, determine that the person is held in the certification
Part is legal；
When at least one in the root-mean-square error of three change in coordinate axis direction is not less than preset threshold, recognize described in determination
It is illegal to demonstrate,prove holder's identity.
The embodiment of the invention also provides a kind of identification authentication systems, comprising:
First acquisition unit, the physiology for obtaining sampling holder shake feature, and the physiology vibration feature is to work as to connect
When receiving the trigger signal of the acquisition physiology vibration feature, acquisition characterizes adding for physiology vibration at least once in preset duration
Speed data sequence；
First determination unit, the power spectral density of the acceleration information sequence for determining the sampling holder, as
Sampled power spectrum density；
Second acquisition unit, for obtaining the certification holder when needing to carry out authentication to certification holder
Physiology shake feature, and determine it is described certification holder acceleration information sequence current power spectrum density；
Second determination unit, for according to preset matching algorithm, determining the current power spectrum density sequence and described adopting
Whether sample power spectrum degree series match, and obtain matching result；
Third determination unit, for determining the legitimacy of certification holder's identity according to the matching result.
Using device provided in an embodiment of the present invention, due to the acceleration information sequence using characterization physiology vibration feature into
The acceleration information sequence of row authentication, favorable repeatability, the characterization physiology vibration of acquisition is accurate, and then improves identity and recognize
The accuracy of card, and the acceleration information for characterizing physiology vibration is difficult to be replicated, and also improves the safety of authentication.
Further, the first acquisition unit, specifically for when the trigger signal for receiving acquisition physiology vibration feature
When, obtain the raw acceleration data sequence of characterization physiology vibration of the sampling holder in preset duration；To it is described it is original plus
Speed data sequence carries out Denoising disposal, obtains characterizing the acceleration information sequence that human physiology vibration is held in the sampling.
Further, above-mentioned apparatus, further includes:
Detection unit, in the original acceleration number for obtaining characterization physiology vibration of the sampling holder in preset duration
Before sequence, whether the physiology vibration feature of detection sampling holder is stable；
Transmission unit, for sending instruction letter to the sampling holder when determining that the physiology vibration feature is stablized
Breath, the instruction information are used to indicate the trigger signal of sampling holder's triggering collection physiology vibration feature.
Further, first determination unit, specifically for being directed to each reference axis of the acceleration information sequence
The acceleration information subsequence is divided into preset quantity acceleration information subsegment by the acceleration information subsequence in direction；
Fourier transformation processing is carried out to acceleration information subsegment described in every section；In all sections of Fu for determining each change in coordinate axis direction respectively
The power spectrum sequence of average of acceleration information subsegment after leaf transformation, by the corresponding power of three change in coordinate axis direction
Compose power spectrum degree series of the sequence of average as the acceleration information sequence.
Further, the preset matching algorithm is adaptive morphology filter device algorithm；The physiology shakes feature
When receiving the trigger signal for acquiring the physiology vibration feature, the physiology vibration of one acquisition characterization adds in preset duration
Speed data sequence；
Second determination unit is carried out specifically for the current power spectrum density sequence respectively to each change in coordinate axis direction
Shape filtering operation obtains the filtered current power spectrum density sequence of the change in coordinate axis direction；Each reference axis is determined respectively
The filtered current power spectrum density in direction and the sampled power spectrum of change in coordinate axis direction identical with the change in coordinate axis direction
The root-mean-square error of density sequence；Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
Further, the preset matching algorithm is adaptive morphology filter device algorithm；The physiology shakes feature
When receiving the trigger signal for acquiring the physiology vibration feature, the physiology vibration of multi collect characterization adds in preset duration
Speed data sequence；
Second determination unit is carried out specifically for the current power spectrum density sequence respectively to each change in coordinate axis direction
Shape filtering operation obtains the filtered current power spectrum density sequence of the change in coordinate axis direction；Multi collect is determined respectively
Characterize same coordinate axis side in the sampled power spectrum density sequence for the acceleration information sequence that human physiology vibration is held in the sampling
To power spectral density sequence of average；Determine respectively each change in coordinate axis direction filtered current power spectrum density sequence and
The root-mean-square error of the power spectral density sequence of average of change in coordinate axis direction identical with the change in coordinate axis direction；Determine three
Whether the root-mean-square error of change in coordinate axis direction is respectively less than preset threshold.
Further, the third determination unit, it is equal specifically for the root-mean-square error when three change in coordinate axis direction
When less than preset threshold, determine that certification holder's identity is legal；When in the root-mean-square error of three change in coordinate axis direction
When at least one is not less than preset threshold, determine that certification holder's identity is illegal.
Other features and advantage will illustrate in the following description, also, partly become from specification
It obtains it is clear that being understood and implementing the application.The purpose of the application and other advantages can be by written explanations
Specifically noted structure is achieved and obtained in book, claims and attached drawing.
Detailed description of the invention
Attached drawing is used to provide further understanding of the present invention, and constitutes part of specification, is implemented with the present invention
Example is used to explain the present invention together, is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is the flow chart of identity identifying method provided in an embodiment of the present invention；
Fig. 2 is the flow chart for the identity identifying method that the embodiment of the present invention 1 provides；
Fig. 3 is the flow chart for the identity identifying method that the embodiment of the present invention 2 provides；
Fig. 4 is the structural schematic diagram for the identification authentication system that the embodiment of the present invention 3 provides.
Specific embodiment
It is mentioned to provide the safety for improving terminal user identity authentication and the implementation of accuracy, the embodiment of the present invention
A kind of identity identifying method and device are supplied, preferred embodiment of the present invention will be described below in conjunction with Figure of description, answers
Work as understanding, preferred embodiments described herein are only used to illustrate and explain the present invention, is not intended to limit the present invention.And
In the case where not conflicting, the features in the embodiments and the embodiments of the present application be can be combined with each other.
The embodiment of the present invention provides a kind of identity identifying method, as shown in Figure 1, comprising:
Step 101, the physiology vibration feature of acquisition sampling holder, physiology vibration feature is to work as to receive acquisition physiology
When shaking the trigger signal of feature, acquisition characterizes the acceleration information sequence of physiology vibration at least once in preset duration.
Step 102, determine sampling holder acceleration information sequence power spectral density, as sampled power compose it is close
Degree.
Step 103, when needing to carry out authentication to certification holder, the physiology vibration for obtaining certification holder is special
Sign, and determine the current power spectrum density of the acceleration information sequence of certification holder.
Step 104, according to preset matching algorithm, determine the current power spectral density sequence and the sampled power spectrum density sequence
Whether column match, and obtain matching result.
Step 105, according to the matching result, determine the legitimacy of certification holder's identity.
In the embodiment of the present invention, physiology vibration is the vibration signal generated by muscle.Terminal built-in acceleration transducer,
The acceleration information sequence generated in the entire verification process of acceleration transducer real-time reception can be used.Wherein, accelerate degree
It can acquire once, can also be acquired repeatedly according to sequence.The power spectral density is that the per unit frequency wave of acceleration signal carries
Power.
With reference to the accompanying drawing, method and device provided by the invention is described in detail with specific embodiment.
Embodiment 1:
When terminal obtains the acceleration information sequence of characterization physiology vibration of primary sampling holder, the present invention is implemented
Example provides a kind of specific process flow of authentication, as shown in Fig. 2, specifically including following processing step:
Whether step 201, the physiology vibration feature of terminal detection sampling holder are stable.
In this step, sampling holder can be accustomed to according to me, and handheld terminal keeps a specified static posture constant,
Whether the physiology vibration feature of terminal detection sampling holder is stable, specifically, can shake feature by detection characterization physiology
Acceleration information sequence curve whether there is violent fluctuation, if there is big ups and downs, can determine sampling holder's
Physiology, which shakes feature, to be stablized, and if there is no big ups and downs, can determine that the physiology vibration feature of sampling holder is unstable.
Step 202, when determine physiology vibration feature stablize when, terminal to sampling holder send instruction information.
Wherein, which is used to indicate the trigger signal of sampling holder's triggering collection physiology vibration feature.Eventually
End can send instruction to sampling holder by the Authentication Client installed in terminal when determining that physiology vibration feature is stablized
Information, such as: display START button is used to indicate sampling holder and triggers the touching for sending acquisition physiology vibration feature to terminal
It signals.
Step 203, when terminal receive acquisition physiology vibration feature trigger signal when, terminal obtain sampling holder exist
The raw acceleration data sequence of characterization physiology vibration feature in preset duration.
After sampling holder presses START button, i.e., the trigger signal of acquisition physiology vibration feature is sent to terminal,
The Authentication Client installed in the terminal starts acquisition in advance by the application programming interfaces of the acceleration transducer of the terminal built-in
If the raw acceleration data sequence in duration, when sampling holder presses conclusion button, it is original that triggering terminal stops acquisition
Acceleration information sequence, wherein the preset duration can based on practical experience with need to carry out flexible setting, for example, this is default
Duration can be 7 seconds.The raw acceleration data sequence includes the raw acceleration data subsequence of three change in coordinate axis direction.
Step 204 carries out Denoising disposal to the raw acceleration data sequence, obtains characterizing the sampling and holds human physiology
Shake the acceleration information sequence of feature.
Due to when obtaining raw acceleration data sequence, being to be terminated using pressing start button as opening flag with pressing
Button is that end mark is acquired raw acceleration data sequence, presses start button and can bring when receiving button and makes an uproar
Sound, it is therefore desirable to which Denoising disposal is carried out to raw acceleration data sequence.
In this step, each change in coordinate axis direction for the raw acceleration data sequence that acceleration transducer can be acquired
The data of a period of time of the beginning and end of raw acceleration data subsequence are deleted, such as: acceleration transducer acquires 7
The raw acceleration data sequence of second can will start to adopt for the raw acceleration data subsequence of each change in coordinate axis direction
Raw acceleration data deletion in raw acceleration data and finally acquire 2 seconds in 2 seconds of collection, obtains acceleration information
Sequence, the acceleration information sequence also include the acceleration information subsequence of three change in coordinate axis direction.
Step 205, for the acceleration information sequence each change in coordinate axis direction acceleration information subsequence, by the seat
The acceleration information subsequence in parameter direction is divided into preset quantity acceleration information subsegment.
In this step, the acceleration information subsequence of each change in coordinate axis direction can specifically be divided as follows, with x-axis
Acceleration information subsequence for:
The acceleration information subsequence for the x-axis that time span is N is divided into L sections of acceleration information according to following formula
Section:
Wherein, M is the time span of every section of acceleration information subsegment, and N is that the time of x-axis acceleration information subsequence is long
Degree.The length being overlapped between two adjacent acceleration information subsegments is M/2, for example, the acceleration of N=200 seconds x-axis of time span
Data subsequence, the time span for dividing every section of acceleration information subsegment is M=100 seconds, then calculates L=3 according to above-mentioned formula,
Period where 3 sections of acceleration information subsegments is respectively 0-100 seconds, 50-150 seconds, 100-200 seconds.
Step 206 carries out Fourier transformation processing to every section of acceleration subsegment.
In this step, carried out after identical hamming window being added to every section of acceleration information subsegment of each change in coordinate axis direction
Fourier transformation can specifically use following formula:
Wherein, Xi(ejω) be i-th section of acceleration information subsegment of the change in coordinate axis direction is carried out Fourier transformation as a result,
I-th section of acceleration information subsegment i.e. after Fourier transformation, w (n) are value of the hamming window function at n-th of time point, xi(n)
For the acceleration value at n-th of time point of i-th section of acceleration information subsegment of the change in coordinate axis direction, M is acceleration information
The time span of section.
Step 207 determines the acceleration information subsegment after all sections of Fourier transformations of each change in coordinate axis direction respectively
Power spectrum sequence of average.
Acceleration in this step, after all sections of Fourier transformations of each change in coordinate axis direction can be determined using following formula
Degree according to subsegment power spectrum sequence of average, by taking x-axis direction as an example:
Wherein,For the mean power of window function w (n), ux(ω) is the acceleration information of x-axis direction
The power spectrum sequence of average of acceleration information subsegment after all sections of Fourier transformations that subsequence includes, Xi(ejω) it is x-axis
I-th section of acceleration information subsegment after the Fourier transformation in direction, using above-mentioned identical method respectively determine y-axis direction and
The power spectrum of acceleration information subsegment after all sections of Fourier transformations that the acceleration information subsequence in z-axis direction includes is average
Value sequence uy(ω) and uz(ω), by ux(ω)、uy(ω) and uzThe power spectral density of (ω) as the acceleration information sequence, i.e.,
Sampled power spectrum density sequence.
Step 208, when need to certification holder carry out authentication when, obtain certification holder in preset duration
Characterize the current acceleration data sequence of physiology vibration feature.
In this step, the acquisition modes of the current acceleration data sequence in step 201-204 by the way of it is identical,
It is no longer described in detail herein.
Step 209, determine the current acceleration data sequence three change in coordinate axis direction current power spectrum density sequence.
In this step, the current acceleration data sequence can be determined using with identical mode in step 205-207
The current power spectrum density sequence of three change in coordinate axis direction, is no longer described in detail herein.
Further, adaptive morphology filter device algorithm can be used, determines current power spectrum density sequence and sampling
Whether power spectrum degree series match, and are specifically handled using following steps 210- step 214.
Step 210, the current power spectrum density sequence progress shape filtering operation for each change in coordinate axis direction, are somebody's turn to do
The filtered current power spectrum density sequence of change in coordinate axis direction.
In this step, it can specifically be carried out using current power spectrum density sequence of the following formula to each change in coordinate axis direction
Shape filtering operation, by taking x-axis as an example:
Y (ω)=ord { (Nω-1)pω+1；f|Bω}；
Wherein, y (ω) be x-axis power spectral density carry out shape filtering operation after at frequencies omega filter output,It is the structural element set at frequencies omega, NωIt is BωStructural element number in set, institute
There is structural element ji(i=1...Nω) it is different integers, pωFor order morphology filtering percentile,Ord is ordering operators, ord { (Nω-1)pω+1；f|BωIndicate to incite somebody to actionAccording to (the N after sequence sequence from small to largeω-1)pω+ 1 current
Power spectral density value, f () indicate current power spectrum density sequence.
Bω、Pω、NωIt can be determined by following iterative process:
All structural elements in any given one sufficiently large candidate structure collection A, A are different integers, and in A
Each structural element r respectively correspond a configuration index value mω(r), a given structure rope is distributed before iteration starts
Draw mω, 0(r), it and according to following formula is iterated:
yk+1(ω)=ord { (Nt,k+1-1)pt,k+1+1；f|Bt,k+1}；
Wherein, mω, k+1It (r) is the configuration index value after+1 iteration of kth, Bω, k+1At frequencies omega after+1 iteration of kth
Structural element set, Nω, k+1For Bω, k+1Structural element number in set, pω, k+1For the sequence shape after+1 iteration of kth
State filters percentile, k=0,1 ... ..., Q, and Q is default the number of iterations, such as Q=200, α and β are least mean-square error standards
Convergence control parameter under then, u (ω) are power spectral density value of the sampled power spectrum density sequence of x-axis at frequencies omega, sng
For sign function, sgn (f (ω-r)-yk(ω)) it indicates to work as f (ω-r)-ykWhen (ω) > 0, sgn (f (ω-r)-yk(ω))=1,
As f (ω-r)-ykWhen (ω) < 0, sgn (f (ω-r)-yk(ω))=- 1.When the number of iterations reaches default the number of iterations, then change
In generation, terminates, at this point, the filter output at frequencies omega is y (ω)=yQ(ω)。
Step 211, the filtered current power spectrum density sequence for determining each change in coordinate axis direction respectively and with the coordinate
The root-mean-square error of the sampled power spectrum density sequence of the identical change in coordinate axis direction of axis direction.
In this step, which can be determined using following formula, by taking x-axis as an example:
Wherein, exBe x-axis direction filtered current power spectrum density and x-axis direction sampled power spectrum density it is equal
Square error, yx(ω) is the current power spectrum density sequence of x-axis direction, ux(ω) is the sampled power spectrum density sequence of x-axis direction
Column.
The sampling of filtered the current power spectrum density and y-axis direction in y-axis direction is determined using above-mentioned identical mode
The root-mean-square error e of power spectral densityyAnd the sampled power of filtered the current power spectrum density and z-axis direction in z-axis direction
The root-mean-square error e of spectrum densityz。
Step 212 determines whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold, if so, into
Step 213, if not, entering step 214.
Wherein, the preset threshold can based on practical experience with need to carry out flexible setting.
Step 213, when the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold, determine certification holder
Identity is legal.
After determining that certification holder's identity is legal, the terminal is can be used in terminal holder.
Step 214, when at least one in the root-mean-square error of three change in coordinate axis direction be not less than preset threshold when, determination recognize
It is illegal to demonstrate,prove holder's identity.
After determining that certification holder's identity is illegal, terminal holder is forbidden to use the terminal.
The method that above-described embodiment 1 provides through the invention, due to the acceleration information using characterization physiology vibration feature
Sequence carries out authentication, and the acceleration information sequence of favorable repeatability, the characterization physiology vibration of acquisition is accurate, and then improves
The accuracy of authentication, and the acceleration information for characterizing physiology vibration is difficult to be replicated, and also improves the peace of authentication
Quan Xing.
Embodiment 2:
When terminal obtains the acceleration information sequence of characterization physiology vibration of multiple repairing weld holder, the embodiment of the present invention
A kind of specific process flow of authentication is provided, as shown in figure 3, specifically including following processing step:
Whether step 301, the physiology vibration feature of terminal detection sampling holder are stable.
In this step, sampling holder can be accustomed to according to me, and handheld terminal keeps a specified static posture constant,
Whether the physiology vibration feature of terminal detection sampling holder is stable, specifically, can shake feature by detection characterization physiology
Acceleration information sequence curve whether there is violent fluctuation, if there is big ups and downs, can determine sampling holder's
Physiology, which shakes feature, to be stablized, and if there is no big ups and downs, can determine that the physiology vibration feature of sampling holder is unstable.
Step 302, when determine physiology vibration feature stablize when, terminal to sampling holder send instruction information.
Wherein, which is used to indicate the trigger signal of sampling holder's triggering collection physiology vibration feature.Eventually
End can send instruction to sampling holder by the Authentication Client installed in terminal when determining that physiology vibration feature is stablized
Information, such as: display START button is used to indicate sampling holder and triggers the touching for sending acquisition physiology vibration feature to terminal
It signals.
Step 303, when terminal receive acquisition physiology vibration feature trigger signal when, terminal repeatedly obtains sample holds
The raw acceleration data sequence of characterization physiology vibration feature of the people in preset duration.
After sampling holder presses START button, i.e., the trigger signal of acquisition physiology vibration feature is sent to terminal,
The Authentication Client installed in the terminal starts to acquire by the application programming interfaces of the acceleration transducer of the terminal built-in
Raw acceleration data sequence in preset duration, when sampling holder presses conclusion button, it is former that triggering terminal stops acquisition
Starting acceleration data sequence, wherein the preset duration can based on practical experience with need to carry out flexible setting, for example, this is pre-
If duration can be 7 seconds.In the manner described above, terminal acquires the first preset quantity raw acceleration data sequence, this first
Preset quantity is greater than 1, for example, the terminal can acquire 3 raw acceleration data sequences.Each raw acceleration data sequence
Raw acceleration data subsequence including three change in coordinate axis direction.
Step 304 carries out Denoising disposal to each raw acceleration data sequence respectively, obtains multiple characterization samplings
Hold the acceleration information sequence of human physiology vibration feature.
Due to when obtaining raw acceleration data sequence, being to be terminated using pressing start button as opening flag with pressing
Button is that end mark is acquired raw acceleration data sequence, presses start button and can bring when receiving button and makes an uproar
Sound, it is therefore desirable to which Denoising disposal is carried out to raw acceleration data sequence.
In this step, each change in coordinate axis direction for the raw acceleration data sequence that acceleration transducer can be acquired
The data of a period of time of the beginning and end of raw acceleration data subsequence are deleted, such as: acceleration transducer acquires 7
The raw acceleration data sequence of second can will start to adopt for the raw acceleration data subsequence of each change in coordinate axis direction
Raw acceleration data deletion in raw acceleration data and finally acquire 2 seconds in 2 seconds of collection, obtains acceleration information
Sequence, the acceleration information sequence also include the acceleration information subsequence of three change in coordinate axis direction.
Further, it for each acceleration information sequence, is handled using following steps 305-307, obtains this and add
The corresponding sampled power spectrum density sequence of speed data sequence may finally obtain the first preset quantity sampled power spectrum density
Sequence.
Step 305, for each acceleration information sequence each change in coordinate axis direction acceleration information subsequence, by this
The acceleration information subsequence of change in coordinate axis direction is divided into preset quantity acceleration information subsegment.
In this step, the acceleration information subsequence of each change in coordinate axis direction can specifically be divided as follows, with x-axis
Acceleration information subsequence for:
The acceleration information subsequence for the x-axis that time span is N is divided into L sections of acceleration information according to following formula
Section:
Wherein, M is the time span of every section of acceleration information subsegment, and N is that the time of x-axis acceleration information subsequence is long
Degree.The length being overlapped between two adjacent acceleration information subsegments is M/2, for example, the acceleration of N=200 seconds x-axis of time span
Data subsequence, the time span for dividing every section of acceleration information subsegment is M=100 seconds, then calculates L=3 according to above-mentioned formula,
Period where 3 sections of acceleration information subsegments is respectively 0-100 seconds, 50-150 seconds, 100-200 seconds.
Step 306 carries out Fourier transformation processing to every section of acceleration subsegment.
In this step, carried out after identical hamming window being added to every section of acceleration information subsegment of each change in coordinate axis direction
Fourier transformation can specifically use following formula:
Wherein, Xi(ejω) be i-th section of acceleration information subsegment of the change in coordinate axis direction is carried out Fourier transformation as a result,
I-th section of acceleration information subsegment i.e. after Fourier transformation, w (n) are value of the hamming window function at n-th of time point, xi(n)
For the value at n-th of time point of i-th section of acceleration information subsegment of the change in coordinate axis direction, when M is acceleration information subsegment
Between length.
Step 307 determines the acceleration information subsegment after all sections of Fourier transformations of each change in coordinate axis direction respectively
Power spectrum sequence of average.
Acceleration in this step, after all sections of Fourier transformations of each change in coordinate axis direction can be determined using following formula
Degree according to subsegment power spectrum sequence of average, by taking x-axis direction as an example:
Wherein,For the mean power of window function w (n), ux(ω) is the acceleration information of x-axis direction
The power spectrum sequence of average of acceleration information subsegment after all sections of Fourier transformations that subsequence includes, Xi(ejω) it is x-axis
I-th section of acceleration information subsegment after the Fourier transformation in direction, using above-mentioned identical method respectively determine y-axis direction and
The power spectrum of acceleration information subsegment after all sections of Fourier transformations that the acceleration information subsequence in z-axis direction includes is average
Value sequence uy(ω) and uz(ω), by ux(ω)、uy(ω) and uzThe power spectral density of (ω) as the acceleration information sequence, i.e.,
Sampled power spectrum density sequence.
Step 308, when need to certification holder carry out authentication when, obtain certification holder in preset duration
Characterize the current acceleration data sequence of physiology vibration feature.
In this step, the acquisition modes of the current acceleration data sequence in step 301-304 by the way of it is identical,
It is no longer described in detail herein.
Step 309, determine the current acceleration data sequence three change in coordinate axis direction current power spectrum density sequence.
In this step, the current acceleration data sequence can be determined using with identical mode in step 305-307
The current power spectrum density sequence of three change in coordinate axis direction, is no longer described in detail herein.
Further, can use adaptive morphology filter device algorithm, determine the current power spectrum density sequence and
Whether sampled power spectrum density sequence matches, and is specifically handled using following steps 310- step 315.
Step 310, the current power spectrum density sequence progress shape filtering operation for each change in coordinate axis direction, are somebody's turn to do
The filtered current power spectrum density sequence of change in coordinate axis direction.
In this step, it can specifically be carried out using current power spectrum density sequence of the following formula to each change in coordinate axis direction
Shape filtering operation, by taking x-axis as an example:
Y (ω)=ord { (Nω-1)pω+1；f|Bω}；
Wherein, y (ω) be x-axis power spectral density carry out shape filtering operation after at frequencies omega filter output,It is the structural element set at frequencies omega, NωIt is BωStructural element number in set, institute
There is structural element ji(i=1...Nω) it is different integers, pωFor order morphology filtering percentile,Ord is ordering operators, ord { (Nω-1)pω+1；fBωIndicate to incite somebody to actionAccording to (the N after sequence sequence from small to largeω-1)pω+ 1 current
Power spectral density value, f () indicate current power spectrum density sequence.
Bω、Pω、NωIt can be determined by following iterative process:
All structural elements in any given one sufficiently large candidate structure collection A, A are different integers, and in A
Each structural element r respectively correspond a configuration index value mω(r), a given structure rope is distributed before iteration starts
Draw mω, 0(r), and it is pre-configured with the m of kth time iterationω, k(r)、Bω, k、Nω, k、pω, kValue, and change according to following formula
Generation:
yk+1(ω)=ord { (Nt,k+1-1)pt,k+1+1；f|Bt,k+1}；
Wherein, mω, k+1It (r) is the configuration index value after+1 iteration of kth, Bω, k+1At frequencies omega after+1 iteration of kth
Structural element set, Nω, k+1For Bω, k+1Structural element number in set, pω, k+1For the sequence shape after+1 iteration of kth
State filters percentile, k=0,1 ... ..., Q, and Q is default the number of iterations, such as Q=200, α and β are least mean-square error standards
Convergence control parameter under then, u (ω) are power spectral density value of the sampled power spectrum density sequence of x-axis at frequencies omega, sng
For sign function, sgn (f (ω-r)-yk(ω)) it indicates to work as f (ω-r)-ykWhen (ω) > 0, sgn (f (ω-r)-yk(ω))=1,
As f (ω-r)-ykWhen (ω) < 0, sgn (f (ω-r)-yk(ω))=- 1.When the number of iterations reaches default the number of iterations, then change
In generation, terminates, at this point, the filter output at frequencies omega is y (ω)=yQ(ω)。
Step 311 determines that the power spectral density of same coordinate axis direction in multiple sampled power spectrum density sequences is flat respectively
Equal value sequence.
It include the power spectral density of three change in coordinate axis direction of x, y, z in this step, in each sampled power spectrum density sequence
Sequence is illustrated with 3 using power spectrum degree series, calculate x-axis direction in 3 sampled power spectrum density sequences in same frequency
The power spectral density average value of rate point obtains the power spectral density sequence of average u of x-axis directionx_avg(ω), using identical side
Method can respectively obtain the power spectral density sequence of average u in y-axis and z-axis directiony_avg(ω) and uz_avg(ω)。
There is no strict sequence between above-mentioned steps 310 and step 311.
Step 312, the filtered current power spectrum density sequence for determining each change in coordinate axis direction respectively and with the coordinate
The root-mean-square error of the power spectral density sequence of average of the identical change in coordinate axis direction of axis direction.
In this step, which can be determined using following formula, by taking x-axis as an example:
Wherein, exBe x-axis direction filtered current power spectrum density and x-axis direction power spectral density root mean square
Error, yx(ω) is the current power spectrum density sequence of x-axis direction, ux(ω) is the power spectrum degree series of x-axis direction.
The power of filtered the current power spectrum density and y-axis direction in y-axis direction is determined using above-mentioned identical mode
The root-mean-square error e of spectrum densityyAnd the power spectral density of the filtered current power spectrum density and z-axis direction in z-axis direction
Root-mean-square error ez。
Step 313 determines whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold, if so, into
Step 314, if not, entering step 315.
Wherein, the preset threshold can based on practical experience with need to carry out flexible setting.
Step 314, when the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold, determine certification holder
Identity is legal.
After determining that certification holder's identity is legal, the terminal is can be used in terminal holder.
Step 315, when at least one in the root-mean-square error of three change in coordinate axis direction be not less than preset threshold when, determination recognize
It is illegal to demonstrate,prove holder's identity.
After determining that certification holder's identity is illegal, terminal holder is forbidden to use the terminal.
Further, adaptive morphology filter device algorithm is being used, is determining current power spectrum density sequence and sampling function
When whether rate spectrum density sequence matches, a sampled power spectrum density can also be chosen in multiple sampled power spectrum density sequences
Sequence is handled using the identical mode of step 210-214 in above-described embodiment 1, is no longer described in detail herein.
Further, when determining whether current power spectrum density sequence and sampled power spectrum density sequence match, may be used also
In a manner of using and use in the prior art, such as: dynamic time warping, details are not described herein.
The method that above-described embodiment 2 provides through the invention, due to the acceleration information using characterization physiology vibration feature
Sequence carries out authentication, and the acceleration information sequence of favorable repeatability, the characterization physiology vibration of acquisition is accurate, and then improves
The accuracy of authentication, and the acceleration information for characterizing physiology vibration is difficult to be replicated, and also improves the peace of authentication
Quan Xing.
Embodiment 3:
Based on the same inventive concept, the identity identifying method provided according to that above embodiment of the present invention, correspondingly, the present invention
Embodiment 3 additionally provides a kind of identification authentication system, and structural schematic diagram is as shown in figure 4, specifically include:
First acquisition unit 401, the physiology for obtaining sampling holder shake feature, and the physiology vibration feature is to work as
When receiving the trigger signal for acquiring the physiology vibration feature, acquisition characterizes physiology vibration at least once in preset duration
Acceleration information sequence；
First determination unit 402, the power spectral density of the acceleration information sequence for determining the sampling holder, makees
For sampled power spectrum density；
Second acquisition unit 403 is held for when needing to carry out authentication to certification holder, obtaining the certification
The physiology of people shakes feature, and determines the current power spectrum density of the acceleration information sequence of the certification holder；
Second determination unit 404, for according to preset matching algorithm, determining the current power spectrum density sequence and described
Whether sampled power spectrum density sequence matches, and obtains matching result；
Third determination unit 405, for determining the legitimacy of certification holder's identity according to the matching result.
Further, first acquisition unit 401, specifically for when the trigger signal for receiving acquisition physiology vibration feature
When, obtain the raw acceleration data sequence of characterization physiology vibration of the sampling holder in preset duration；To it is described it is original plus
Speed data sequence carries out Denoising disposal, obtains characterizing the acceleration information sequence that human physiology vibration is held in the sampling.
Further, above-mentioned apparatus, further includes:
Detection unit 406, in the original acceleration for obtaining characterization physiology vibration of the sampling holder in preset duration
It spends before data sequence, whether the physiology vibration feature of detection sampling holder is stable；
Transmission unit 407, for sending and indicating to the sampling holder when determining that the physiology vibration feature is stablized
Information, the instruction information are used to indicate the trigger signal of sampling holder's triggering collection physiology vibration feature.
Further, the first determination unit 402, specifically for being directed to each reference axis side of the acceleration information sequence
To acceleration information subsequence, the acceleration information subsequence is divided into preset quantity acceleration information subsegment；It is right
Every section of acceleration information subsegment carries out Fourier transformation processing；All sections of Fourier of each change in coordinate axis direction are determined respectively
The power spectrum sequence of average of transformed acceleration information subsegment, by the corresponding power spectrum of three change in coordinate axis direction
Power spectrum degree series of the sequence of average as the acceleration information sequence.
Further, the preset matching algorithm is adaptive morphology filter device algorithm；The physiology shakes feature
When receiving the trigger signal for acquiring the physiology vibration feature, the physiology vibration of one acquisition characterization adds in preset duration
Speed data sequence；
Second determination unit 404 is carried out specifically for the current power spectrum density sequence respectively to each change in coordinate axis direction
Shape filtering operation obtains the filtered current power spectrum density sequence of the change in coordinate axis direction；Each reference axis is determined respectively
The filtered current power spectrum density in direction and the sampled power spectrum of change in coordinate axis direction identical with the change in coordinate axis direction
The root-mean-square error of density sequence；Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
Further, the preset matching algorithm is adaptive morphology filter device algorithm；The physiology shakes feature
When receiving the trigger signal for acquiring the physiology vibration feature, the physiology vibration of multi collect characterization adds in preset duration
Speed data sequence；
Second determination unit 404 is carried out specifically for the current power spectrum density sequence respectively to each change in coordinate axis direction
Shape filtering operation obtains the filtered current power spectrum density sequence of the change in coordinate axis direction；Multi collect is determined respectively
Characterize same coordinate axis side in the sampled power spectrum density sequence for the acceleration information sequence that human physiology vibration is held in the sampling
To power spectral density sequence of average；Determine respectively each change in coordinate axis direction filtered current power spectrum density sequence and
The root-mean-square error of the power spectral density sequence of average of change in coordinate axis direction identical with the change in coordinate axis direction；Determine three
Whether the root-mean-square error of change in coordinate axis direction is respectively less than preset threshold.
Further, third determination unit 405 is small specifically for the root-mean-square error when three change in coordinate axis direction
When preset threshold, determine that certification holder's identity is legal；When in the root-mean-square error of three change in coordinate axis direction extremely
When lacking one not less than preset threshold, determine that certification holder's identity is illegal.
The function of above-mentioned each unit can correspond to the respective handling step in process shown in Fig. 1, Fig. 2 or Fig. 3, herein no longer
It repeats.
In conclusion scheme provided in an embodiment of the present invention, comprising: the physiology for obtaining sampling holder shakes feature, should
Physiology vibration feature is the acquisition tables at least once in preset duration when receiving acquisition physiology and shaking the trigger signal of feature
Levy the acceleration information sequence of physiology vibration；The power spectral density for determining the acceleration information sequence of sampling holder, as
Sampled power spectrum density；When needing to carry out authentication to certification holder, the physiology vibration for obtaining certification holder is special
Sign, and determine the current power spectrum density of the acceleration information sequence of certification holder；According to preset matching algorithm, determining should
Whether current power spectrum density sequence and the sampled power spectrum density sequence match, and obtain matching result；According to the matching result,
Determine the legitimacy of certification holder's identity.Using above scheme provided by the invention, compared to the prior art, body is improved
The safety and accuracy of part certification.
Identification authentication system provided by embodiments herein can be realized by a computer program.Those skilled in the art
It should be appreciated that above-mentioned module division mode is only one of numerous module division modes, if being divided into other moulds
Block or non-division module all should be within the scope of protection of this application as long as identification authentication system has above-mentioned function.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device of static function in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
Static function in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
In a box or multiple boxes the step of static function.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (14)
1. a kind of identity identifying method characterized by comprising
The physiology for obtaining sampling holder shakes feature, and the physiology vibration feature is special when receiving the acquisition physiology vibration
When the trigger signal of sign, acquisition characterizes the acceleration information sequence of physiology vibration at least once in preset duration；
The power spectral density for determining the acceleration information sequence of the sampling holder, as sampled power spectrum density；
When needing to carry out authentication to certification holder, the physiology for obtaining the certification holder shakes feature, and determines
The current power spectrum density of the acceleration information sequence of the certification holder；
According to preset matching algorithm, determine the current power spectrum density sequence and the sampled power spectrum density sequence whether
Match, obtains matching result；
According to the matching result, the legitimacy of certification holder's identity is determined.
2. the method as described in claim 1, which is characterized in that the physiology for obtaining sampling holder shakes feature, specifically includes:
When receiving the trigger signal of acquisition physiology vibration feature, characterization physiology of the sampling holder in preset duration is obtained
The raw acceleration data sequence of vibration；
Denoising disposal is carried out to the raw acceleration data sequence, obtain characterizing the sampling hold human physiology vibration plus
Speed data sequence.
3. method according to claim 2, which is characterized in that obtaining characterization physiology of the sampling holder in preset duration
Before the raw acceleration data sequence of vibration, further includes:
Whether the physiology vibration feature of detection sampling holder is stable；
When determining that the physiology vibration feature is stablized, instruction information is sent to the sampling holder, the instruction information is used
In the trigger signal for indicating sampling holder's triggering collection physiology vibration feature.
4. method a method according to any one of claims 1-3, which is characterized in that determine the acceleration information sequence of the sampling holder
The power spectral density of column, specifically includes:
For the acceleration information subsequence of each change in coordinate axis direction of the acceleration information sequence, by the acceleration information
Subsequence is divided into preset quantity acceleration information subsegment；
Fourier transformation processing is carried out to acceleration information subsegment described in every section；
The power spectrum average value of acceleration information subsegment after determining all sections of Fourier transformations of each change in coordinate axis direction respectively
Sequence, using the corresponding power spectrum sequence of average of three change in coordinate axis direction as the function of the acceleration information sequence
Rate spectrum density sequence.
5. the method as described in claim 1, which is characterized in that the preset matching algorithm is the calculation of adaptive morphology filter device
Method；The physiology vibration feature is when receiving the trigger signal for acquiring the physiology vibration feature, one in preset duration
The acceleration information sequence of secondary acquisition characterization physiology vibration；
According to adaptive morphology filter device algorithm, the current power spectrum density sequence and the sampled power spectrum density are determined
Whether sequence matches, and specifically includes:
Shape filtering operation is carried out to the current power spectrum density sequence of each change in coordinate axis direction respectively, obtains the change in coordinate axis direction
Filtered current power spectrum density sequence；
Determine respectively each change in coordinate axis direction filtered current power spectrum density and coordinate identical with the change in coordinate axis direction
The root-mean-square error of the sampled power spectrum density sequence of axis direction；
Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
6. the method as described in claim 1, which is characterized in that the preset matching algorithm is the calculation of adaptive morphology filter device
Method；Physiology vibration feature be when receive acquire the physiology and shake the trigger signal of feature when, it is more in preset duration
The acceleration information sequence of secondary acquisition characterization physiology vibration；
According to adaptive morphology filter device algorithm, the current power spectrum density sequence and the sampled power spectrum density are determined
Whether sequence matches, and specifically includes:
Shape filtering operation is carried out to the current power spectrum density sequence of each change in coordinate axis direction respectively, obtains the change in coordinate axis direction
Filtered current power spectrum density sequence；
Determine that the sampled power spectrum of the acceleration information sequence of human physiology vibration is held in the sampling of the characterization of multi collect respectively
The power spectral density sequence of average of same coordinate axis direction in density sequence；
The filtered current power spectrum density sequence of each change in coordinate axis direction and identical with the change in coordinate axis direction is determined respectively
The root-mean-square error of the power spectral density sequence of average of change in coordinate axis direction；
Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
7. such as method described in claim 5 or 6, which is characterized in that according to the matching result, determine the certification holder
The legitimacy of identity, specifically includes:
When the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold, determine that certification holder's identity is closed
Method；
When at least one in the root-mean-square error of three change in coordinate axis direction is not less than preset threshold, determine that the certification is held
Someone's identity is illegal.
8. a kind of identification authentication system characterized by comprising
First acquisition unit, the physiology for obtaining sampling holder shake feature, and the physiology vibration feature is to work as to receive
When acquiring the trigger signal of the physiology vibration feature, acquisition characterizes the acceleration of physiology vibration at least once in preset duration
Data sequence；
First determination unit, the power spectral density of the acceleration information sequence for determining the sampling holder, as sampling
Power spectral density；
Second acquisition unit, for when needing to carry out authentication to certification holder, obtaining the life of the certification holder
Reason vibration feature, and determine the current power spectrum density of the acceleration information sequence of the certification holder；
Second determination unit, for determining the current power spectrum density sequence and the sampling function according to preset matching algorithm
Whether rate spectrum density sequence matches, and obtains matching result；
Third determination unit, for determining the legitimacy of certification holder's identity according to the matching result.
9. device as claimed in claim 8, which is characterized in that the first acquisition unit receives acquisition specifically for working as
When physiology shakes the trigger signal of feature, the original acceleration of characterization physiology vibration of the sampling holder in preset duration is obtained
Data sequence；Denoising disposal is carried out to the raw acceleration data sequence, obtains characterizing the sampling and holds human physiology shake
Dynamic acceleration information sequence.
10. device as claimed in claim 9, which is characterized in that further include:
Detection unit, in the raw acceleration data sequence for obtaining characterization physiology vibration of the sampling holder in preset duration
Before column, whether the physiology vibration feature of detection sampling holder is stable；
Transmission unit, for sending instruction information, institute to the sampling holder when determining that the physiology vibration feature is stablized
State the trigger signal that instruction information is used to indicate sampling holder's triggering collection physiology vibration feature.
11. the device as described in claim 8-10 is any, which is characterized in that first determination unit, specifically for being directed to
The acceleration information subsequence of each change in coordinate axis direction of the acceleration information sequence draws the acceleration information subsequence
It is divided into preset quantity acceleration information subsegment；Fourier transformation processing is carried out to acceleration information subsegment described in every section；Respectively
The power spectrum sequence of average of acceleration information subsegment after determining all sections of Fourier transformations of each change in coordinate axis direction, by three
Power spectral density of a corresponding power spectrum sequence of average of change in coordinate axis direction as the acceleration information sequence
Sequence.
12. device as claimed in claim 8, which is characterized in that the preset matching algorithm is adaptive morphology filter device
Algorithm；The physiology vibration feature is when receiving the trigger signal for acquiring the physiology vibration feature, in preset duration
One acquisition characterizes the acceleration information sequence of physiology vibration；
Second determination unit carries out form specifically for the current power spectrum density sequence respectively to each change in coordinate axis direction
Filtering operation obtains the filtered current power spectrum density sequence of the change in coordinate axis direction；Each change in coordinate axis direction is determined respectively
Filtered current power spectrum density and change in coordinate axis direction identical with the change in coordinate axis direction the sampled power spectrum density
The root-mean-square error of sequence；Determine whether the root-mean-square error of three change in coordinate axis direction is respectively less than preset threshold.
13. device as claimed in claim 8, which is characterized in that the preset matching algorithm is adaptive morphology filter device
Algorithm；The physiology vibration feature is when receiving the trigger signal for acquiring the physiology vibration feature, in preset duration
Multi collect characterizes the acceleration information sequence of physiology vibration；
Second determination unit carries out form specifically for the current power spectrum density sequence respectively to each change in coordinate axis direction
Filtering operation obtains the filtered current power spectrum density sequence of the change in coordinate axis direction；The characterization of multi collect is determined respectively
Same coordinate axis direction in the sampled power spectrum density sequence of the acceleration information sequence of human physiology vibration is held in the sampling
Power spectral density sequence of average；Determine respectively each change in coordinate axis direction filtered current power spectrum density sequence and with this
The root-mean-square error of the power spectral density sequence of average of the identical change in coordinate axis direction of change in coordinate axis direction；Determine three coordinates
Whether the root-mean-square error of axis direction is respectively less than preset threshold.
14. device as described in claim 12 or 13, which is characterized in that the third determination unit is specifically used for when three
When the root-mean-square error of change in coordinate axis direction is respectively less than preset threshold, determine that certification holder's identity is legal；When three
When at least one in the root-mean-square error of change in coordinate axis direction is not less than preset threshold, determine that certification holder's identity is non-
Method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410234344.9A CN105227306B (en) | 2014-05-29 | 2014-05-29 | A kind of identity identifying method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410234344.9A CN105227306B (en) | 2014-05-29 | 2014-05-29 | A kind of identity identifying method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105227306A CN105227306A (en) | 2016-01-06 |
| CN105227306B true CN105227306B (en) | 2018-12-07 |
Family
ID=54996027
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410234344.9A Active CN105227306B (en) | 2014-05-29 | 2014-05-29 | A kind of identity identifying method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105227306B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1745420A1 (en) * | 2004-05-05 | 2007-01-24 | Koninklijke Philips Electronics N.V. | Identification system using mechanical vibrations on identifier |
| CN103795537A (en) * | 2013-10-29 | 2014-05-14 | 清华大学 | Authentication method and terminal equipment |
-
2014
- 2014-05-29 CN CN201410234344.9A patent/CN105227306B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1745420A1 (en) * | 2004-05-05 | 2007-01-24 | Koninklijke Philips Electronics N.V. | Identification system using mechanical vibrations on identifier |
| CN103795537A (en) * | 2013-10-29 | 2014-05-14 | 清华大学 | Authentication method and terminal equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105227306A (en) | 2016-01-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10223512B2 (en) | Voice-based liveness verification | |
| EP3182316B1 (en) | Fingerprint authentication method and system, and terminal supporting fingerprint authentication | |
| KR20180072148A (en) | Method for managing contents and electronic device for the same | |
| WO2017080311A1 (en) | Method and device for improving fingerprint template and terminal device | |
| WO2016110002A1 (en) | Screen interface unlocking method and screen interface unlocking device | |
| CN109378006B (en) | Cross-device voiceprint recognition method and system | |
| US10303433B2 (en) | Portable terminal device and information processing system | |
| EP3580753A1 (en) | Voice signature for user authentication to electronic device | |
| EP3437020B1 (en) | Secure storage of fingerprint related elements | |
| WO2014089993A1 (en) | Method and apparatus for unlocking a touch screen | |
| US20140137221A1 (en) | Image meta data driven device authentication | |
| CN111630510B (en) | Echo pattern user authentication | |
| CN105278666A (en) | Method and device for obtaining work and rest time of users | |
| WO2017215186A1 (en) | Secure login method and device, and a storage medium | |
| WO2019085000A1 (en) | Method and device for controlling reading of electronic book | |
| WO2017016032A1 (en) | Fingerprint verification method, fingerprint verification device and terminal | |
| CN113177850A (en) | Method and device for multi-party identity authentication of insurance | |
| CN109947971A (en) | Image search method, device, electronic equipment and storage medium | |
| CN105741841B (en) | Sound control method and electronic equipment | |
| EP3499502A1 (en) | Voice information processing method and apparatus | |
| CN103870735A (en) | Unlocking processing method and device | |
| CN105227306B (en) | A kind of identity identifying method and device | |
| CN110709783A (en) | Methods, systems, and media for authenticating a user using a biometric signature | |
| CN108630208B (en) | Server, voiceprint-based identity authentication method and storage medium | |
| CN109284588A (en) | Information Authentication method, apparatus and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |