CN108121940A - A kind of method and apparatus of fingerprint image analysis - Google Patents
A kind of method and apparatus of fingerprint image analysis Download PDFInfo
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- CN108121940A CN108121940A CN201611075402.3A CN201611075402A CN108121940A CN 108121940 A CN108121940 A CN 108121940A CN 201611075402 A CN201611075402 A CN 201611075402A CN 108121940 A CN108121940 A CN 108121940A
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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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Abstract
The present invention is suitable for technical field of image processing, provides a kind of method and apparatus of fingerprint image analysis, the described method includes：Gather the fingerprint image data of user；Frequency-domain transform is carried out to the fingerprint image data, and calculates the ridge distance of the fingerprint image data after the frequency-domain transform；Signature analysis is carried out according to the ridge distance, determines the identity attribute classification of the user.Technical scheme reduces the complexity of fingerprint image analyzing and processing, improves the efficiency of fingerprint image analysis by being analyzed ridge distance to determine the identity attribute classification of user, and cost is relatively low, easy to use.
Description
Technical field
The present invention relates to the method and apparatus that technical field of image processing more particularly to a kind of fingerprint image are analyzed.
Background technology
In recent years, with the development of information technology, the one kind of fingerprint recognition as biometrics identification technology is being pacified with it
Remarkable advantage in terms of full property and convenience, has been more and more widely used.
At present, common fingerprint recognition and processing method are mostly characteristic value and the spy by taking the fingerprint and analyzing fingerprint
Fingerprint is identified in the mode that value indicative compares, these recognition methods are higher to the hardware performance requirements of fingerprint identification device, meter
It calculates complexity, take long, it is less efficient, and cost is higher.
The content of the invention
It is an object of the invention to provide a kind of method and apparatus of fingerprint image analysis, it is intended to solve prior art middle finger
The problem of complex disposal process of line identification, efficiency is low, and of high cost.
The first aspect of the present invention provides a kind of method of fingerprint image analysis, including：
Gather the fingerprint image data of user；
Frequency-domain transform is carried out to the fingerprint image data, and calculates the fingerprint image data after the frequency-domain transform
Ridge distance；
Signature analysis is carried out according to the ridge distance, determines the identity attribute classification of the user.
The second aspect of the present invention provides a kind of device of fingerprint image analysis, including：
Acquisition module, for gathering the fingerprint image data of user；
Computing module for carrying out frequency-domain transform to the fingerprint image data, and calculates the institute after the frequency-domain transform
State the ridge distance of fingerprint image data；
Identification module for carrying out signature analysis according to the ridge distance, determines the identity attribute classification of the user.
The existing compared with prior art advantageous effect of the present invention is：By gathering the fingerprint image data of user, to this
Fingerprint image data carry out frequency-domain transform, calculate frequency-domain transform after fingerprint image data ridge distance, and to the streakline away from
From signature analysis is carried out, the identity attribute classification of the user is determined according to analysis result, reduces fingerprint image analyzing and processing
Complexity, improve fingerprint image analysis efficiency, and cost is relatively low, it is easy to use.
Description of the drawings
Fig. 1 is a kind of flow chart of the method for fingerprint image analysis that the embodiment of the present invention one provides；
Fig. 2 is a kind of flow chart of the method for fingerprint image analysis provided by Embodiment 2 of the present invention；
Fig. 3 is a kind of structure diagram of the device for fingerprint image analysis that the embodiment of the present invention three provides；
Fig. 4 is a kind of structure diagram of the device for fingerprint image analysis that the embodiment of the present invention four provides.
Specific embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to the accompanying drawings and embodiments, it is right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The realization of the present invention is described in detail below in conjunction with specific attached drawing.
Embodiment one：
Fig. 1 is a kind of flow chart of the method for fingerprint image analysis that the embodiment of the present invention one provides, and specifically includes step
S101 to S103, details are as follows：
S101, the fingerprint image data for gathering user.
Specifically, the fingerprint image data that fingerprint identification device passes through image acquisition device user.
It should be noted that the executive agent of the present embodiment can be the work(of fingerprint identification device or fingerprint identification device
Energy module, can also be the fingerprint identification device on specific product, is not limited herein.
S102, frequency-domain transform is carried out to fingerprint image data, and calculates the streakline of the fingerprint image data after frequency-domain transform
Distance.
Specifically, frequency-domain transform is carried out to the fingerprint image data that step S101 is collected, obtains the fingerprint image of frequency domain
Fingerprint image number is calculated as data, the i.e. frequency data of fingerprint ridge line and fingerprint valley mechanical periodicity, and according to the frequency data
According to ridge distance.
Ridge distance refers to the average value of ridge distance in certain area, usually by calculating fingerprint ridge line center to fingerprint
The average length at valley line center is as ridge distance.
S103, signature analysis is carried out according to the ridge distance of fingerprint image data, determines the identity attribute classification of user.
Specifically, the ridge distance calculated according to step S102 carries out signature analysis to the fingerprint image data of user,
And classified according to the result of signature analysis to the identity attribute of user.
The ridge distance of fingerprint part is bigger, shows that streakline is more sparse at this, conversely, the ridge distance of fingerprint part is got over
It is small, show that streakline is more intensive at this, therefore according to the signature analysis to ridge distance, can identify the identity group belonging to user
Body, and determine the identity attribute classification of user.Such as the ridge distance of old man passes through streakline commonly greater than the ridge distance of children
The signature analysis of distance can identify the age level of user.
In the present embodiment, by gathering the fingerprint image data of user, frequency-domain transform is carried out to fingerprint image data, is calculated
The ridge distance of fingerprint image data after frequency-domain transform, and signature analysis is carried out to the ridge distance, it is true according to analysis result
Determine the identity attribute classification of user, reduce the complexity of fingerprint image analyzing and processing, improve fingerprint image analysis efficiency, and
And cost is relatively low, it is easy to use.
Embodiment two：
Fig. 2 is a kind of flow chart of the method for fingerprint image analysis provided by Embodiment 2 of the present invention, specifically includes step
S201 to S208, details are as follows：
S201, the fingerprint image data for gathering user.
Specifically, the fingerprint image data that fingerprint identification device passes through image acquisition device user.
It should be noted that the executive agent of the present embodiment can be the work(of fingerprint identification device or fingerprint identification device
Energy module, can also be the fingerprint identification device on specific product, is not limited herein.
S202, the fingerprint image data collected is normalized, obtained and pre-set dimension scope and default bright
Spend the identical normalized image data of scope.
Specifically, to the fingerprint image data of the step S201 users collected, according to pre-set dimension scope and preset bright
Spend the normalization words processing that scope carries out size and gray scale so that different fingerprint image datas has phase after normalized
Same picture size and brightness.
S203, normalized image data are filtered, remove noise jamming.
Specifically, the normalized image data that step S202 is obtained are filtered, are retaining image detail feature
In the case of the noise of normalized image data is inhibited, remove noise jamming.
S204, binary conversion treatment is carried out to the normalized image data after filtering process, obtains binary image data.
Specifically, binary conversion treatment is carried out to the normalized image data after step S203 filtering process, judges to normalize
Whether the gray value of each pixel is more than default gray threshold in image data, if more than default gray threshold, then will
The gray value of the pixel is arranged to 255, otherwise, the gray value of the pixel is arranged to 0, obtains binary image data,
So that the corresponding fingerprint image of binary image data shows apparent black and white effect.
It is possible to further carry out micronization processes to obtained binary image data, original fingerprint image shape is being kept
Pixel extra in the binary image data is removed on the premise of shape feature, obtains the skeleton of fingerprint image.
S205, the gray value according to each pixel in binary image data carry out two-dimensional discrete to each pixel
Fourier transformation obtains the frequency spectrum data of fingerprint image data, wherein, which is identical frequency in fingerprint image data
The distributed data of circumference.
Specifically, two dimensional discrete Fourier transform is carried out to the gray value of each pixel in binary image data, obtained
The distribution of the distribution situation, the i.e. energy intensity of pixel of the circumference of the pixel composition of identical frequency into fingerprint image data
Situation.
S206, the frequency spectrum data according to fingerprint image data calculate the ridge distance of the fingerprint image data.
Specifically, according to the frequency spectrum data of fingerprint image data, step S2061 to step can be passed through by calculating ridge distance
S2063 is completed, and detailed description are as follows：
S2061, spectral centroid point is determined according to the frequency spectrum data of fingerprint image data.
Specifically, according to the frequency spectrum data of the fingerprint image data of the obtained frequency domains of step S205, frequency spectrum data is determined
Spectral centroid point.
S2062, using spectral centroid point as dot, determine same frequency spectrum pixel composition frequency spectrum annulus.
Specifically, the spectral centroid point determined using step S2061 determines frequency spectrum annulus as dot, which is phase
The circumference formed with the pixel of frequency spectrum.
S2063, the ridge distance that fingerprint image data is calculated by formula d=W/R, wherein, d is ridge distance, and W is frequency spectrum
The width of the corresponding fingerprint image of data, R are the average value of the radius of frequency spectrum annulus.
Specifically, the radius of ridge distance and frequency spectrum annulus is inversely proportional, and fingerprint image data is calculated according to formula d=W/R
Ridge distance.
It should be noted that ridge distance can also be calculated by the method for entropy estimate, entropy estimate can determine frequency
It is close to calculate maximum entropy by the method for entropy estimate for the concentrated area of the highest pixel of rate, i.e., the region that energy is concentrated the most
The ridge frequency in region is spent, accurate ridge distance is calculated by weighted euclidean distance further according to the ridge frequency.
S207, the fingerprint characteristic that user is determined according to ridge distance, wherein, which includes fingerprint density, fingerprint
Fineness degree and finger wear degree at least one or any combination.
Specifically, the fingerprint characteristic of user is determined according to the step S206 ridge distances calculated, which can be with
Including fingerprint density, fingerprint fineness degree and finger wear degree at least one or any combination.
Fingerprint density can be determined according to ridge distance, ridge distance is bigger, shows that streakline is more sparse at this, conversely, line
Linear distance is smaller, shows that streakline is more intensive at this.
The width of fingerprint ridge line and fingerprint valley is calculated according to ridge distance, fingerprint fineness degree is determined by the width, it is wide
Degree is bigger, shows that fingerprint is thicker at this, conversely, width is smaller, shows that fingerprint is thinner at this.
According to the amplitude of variation between ridge distance and default ridge distance average, that is, shaking strong degree can determine to refer to
Line wear intensity, amplitude of variation is bigger, shows that finger wear degree is bigger at this, conversely, amplitude of variation is smaller, shows fingerprint at this
The degree of wear is smaller.
S208, the group property that user is judged according to fingerprint characteristic.
It specifically, can be close according to fingerprint when judging the group property of user according to the step S207 fingerprint characteristics determined
Any one feature in degree, fingerprint fineness degree and finger wear degree judged, can also be according to fingerprint density, fingerprint
Any combination feature of fineness degree and finger wear degree carries out comprehensive descision, is not limited herein.
Group property can be age attribute, and the age-colony belonging to user can be determined by fingerprint characteristic, due into
Fingerprint density, fingerprint fineness degree and the finger wear degree of year crowd's body are all higher than minor group, therefore according to fingerprint characteristic
The age bracket of user can be distinguished, in some products and application scenarios for having and being applicable in age limit, is judged by fingerprint characteristic
The age bracket of user can realize that the use to the non-user for being applicable in age bracket limits, so that it is guaranteed that safe to use.
Such as lighter is not suitable for children's use, when children touch lighter, passes through the fingerprint recognition on lighter
The fingerprint collected can be identified in device, judge the age bracket of the user of current touch lighter, if it find that currently
User is children, can close ignition function, and refusal children use.
In the present embodiment, by gathering the fingerprint image data of user, fingerprint image data is normalized
It is filtered to the normalized image data identical with pre-set dimension scope and predetermined luminance range, and to normalized image data
Processing removes noise jamming, then carries out binary conversion treatment to the normalized image data after filtering process, obtains binary image
After data, according to the gray value of each pixel in the binary image data, each pixel is carried out in two-dimensional discrete Fu
Leaf transformation obtains the frequency spectrum data of fingerprint image data, and according to the frequency spectrum data of fingerprint image data, calculates the fingerprint image
The ridge distance of data determines the fingerprint characteristic of user according to ridge distance, and judges that the group of user belongs to according to fingerprint characteristic
Property, which includes fingerprint density, fingerprint fineness degree and finger wear degree at least one or any combination.The present invention
Technical solution the identity attribute classification of user is determined by way of analyzing ridge distance, fingerprint image can be reduced
The complexity of analyzing and processing improves the efficiency of fingerprint image analysis, and cost is relatively low, easy to use, meanwhile, by line
Linear distance carries out analyzing the fingerprint characteristics such as the fingerprint density of definite user, fingerprint fineness degree and finger wear degree, and according to these
Fingerprint characteristic judges the group property of user, can it is some have be applicable in group limitation product and application scenarios in, realize pair
The use limitation of the non-user for being applicable in group, so that it is guaranteed that it is safe to use, improve the use intelligent level of product.
Embodiment three：
Fig. 3 is a kind of structure diagram of the device for fingerprint image analysis that the embodiment of the present invention three provides, for the ease of
Illustrate, illustrate only and the relevant part of the embodiment of the present invention.Before a kind of exemplary devices of fingerprint image analysis of Fig. 3 can be
The executive agent of the method for the fingerprint image analysis of the offer of embodiment one is provided.A kind of exemplary devices of fingerprint image analysis of Fig. 3
Including：Acquisition module 31, computing module 32 and identification module 33.Detailed description are as follows for each function module：
Acquisition module 31, for gathering the fingerprint image data of user；
Computing module 32, the fingerprint image data for being collected to acquisition module 31 carries out frequency-domain transform, and calculates and be somebody's turn to do
The ridge distance of fingerprint image data after frequency-domain transform；
Identification module 33, the ridge distance for being calculated according to computing module 32 carry out signature analysis, determine user's
Identity attribute classification.
Each module realizes the process of respective function in a kind of device of fingerprint image analysis provided in this embodiment, specifically may be used
With reference to the description of foregoing embodiment illustrated in fig. 1, details are not described herein again.
It was found from a kind of exemplary devices of fingerprint image analysis of above-mentioned Fig. 3, in the present embodiment, by the finger for gathering user
Print image data carry out frequency-domain transform to fingerprint image data, calculate the ridge distance of the fingerprint image data after frequency-domain transform,
And signature analysis is carried out to the ridge distance, the identity attribute classification of user is determined according to analysis result, reduces fingerprint image
The complexity of analyzing and processing improves fingerprint image analysis efficiency, and cost is relatively low, easy to use.
Example IV：
Fig. 4 is a kind of structure diagram of the device for fingerprint image analysis that the embodiment of the present invention four provides, for the ease of
Illustrate, illustrate only and the relevant part of the embodiment of the present invention.Before a kind of exemplary devices of fingerprint image analysis of Fig. 4 can be
The executive agent of the method for the fingerprint image analysis of the offer of embodiment two is provided.A kind of exemplary devices of fingerprint image analysis of Fig. 4
Including：Acquisition module 41, computing module 42 and identification module 43.Detailed description are as follows for each function module：
Acquisition module 41, for gathering the fingerprint image data of user；
Computing module 42 carries out frequency-domain transform for collecting fingerprint image data to acquisition module 41, and calculates the frequency
The ridge distance of fingerprint image data after the conversion of domain；
Identification module 43, the ridge distance for being calculated according to computing module 42 carry out signature analysis, determine user's
Identity attribute classification.
Further, identification module 43 includes：
Feature determination sub-module 431, the ridge distance for being calculated according to computing module 42 determine that the fingerprint of user is special
Sign, wherein, which includes fingerprint density, fingerprint fineness degree and finger wear degree at least one or any combination；
Determined property submodule 432, the fingerprint characteristic for being determined according to feature determination sub-module 431 judge the group of user
Body attribute.
Further, which further includes：
Module 44 is normalized, the fingerprint image data for being collected to acquisition module 41 is normalized, obtains
The normalized image data identical with pre-set dimension scope and predetermined luminance range；
Filter module 45, the normalized image data for being obtained to normalization module 44 are filtered, and removal is made an uproar
Acoustic jamming；
Binarization block 46, for being carried out to the normalized image data after 45 filtering process of filter module at binaryzation
Reason, obtains binary image data.
Further, computing module 42 includes：
Fourier transformation submodule 421, for each picture in the binary image data that are obtained according to binarization block 46
The gray value of vegetarian refreshments carries out two dimensional discrete Fourier transform to each pixel, obtains the frequency spectrum data of fingerprint image data,
In, which is the distributed data of identical frequency circumference in fingerprint image data；
Ridge distance computational submodule 422 for the frequency spectrum data obtained according to Fourier transformation submodule 421, calculates
The ridge distance of fingerprint image data.
Further, ridge distance computational submodule 422 includes：
Center determination unit 4221, the frequency spectrum data for being obtained according to Fourier transformation submodule 421 are determined in frequency spectrum
Heart point；
Annulus determination unit 4222, the spectral centroid point for being obtained using center determination unit 4221 determine phase as dot
The frequency spectrum annulus formed with the pixel of frequency spectrum；
Metrics calculation unit 4223, for pressing the ridge distance that formula d=W/R calculates fingerprint image data, wherein, d is
Ridge distance, W are the width of the corresponding fingerprint image of frequency spectrum data, and R is the frequency spectrum annulus that annulus determination unit 4222 determines
The average value of radius.
Each module realizes the process of respective function in a kind of device of fingerprint image analysis provided in this embodiment, specifically may be used
With reference to the description of foregoing embodiment illustrated in fig. 2, details are not described herein again.
It was found from a kind of exemplary devices of fingerprint image analysis of above-mentioned Fig. 4, in the present embodiment, by the finger for gathering user
Print image data are normalized to obtain identical with pre-set dimension scope and predetermined luminance range to fingerprint image data
Normalized image data, and normalized image data are filtered, noise jamming is removed, then to returning after filtering process
One, which changes image data, carries out binary conversion treatment, after obtaining binary image data, according to each picture in the binary image data
The gray value of vegetarian refreshments carries out two dimensional discrete Fourier transform to each pixel, obtains the frequency spectrum data of fingerprint image data, and
According to the frequency spectrum data of fingerprint image data, the ridge distance of the fingerprint image data is calculated, user is determined according to ridge distance
Fingerprint characteristic, and judge according to fingerprint characteristic the group property of user, which includes fingerprint density, fingerprint thickness
Degree and finger wear degree at least one or any combination.Technical scheme is by analyzing ridge distance
Mode determines the identity attribute classification of user, can reduce the complexity of fingerprint image analyzing and processing, improves fingerprint image point
Efficiency is analysed, and cost is relatively low, it is easy to use, meanwhile, by carrying out analyzing the fingerprint density of definite user to ridge distance, refer to
The fingerprint characteristics such as line fineness degree and finger wear degree, and judge according to these fingerprint characteristics the group property of user, it can be at certain
Have a bit and be applicable in the product and application scenarios of group's limitation, realize that the use to the non-user for being applicable in group limits, so that it is guaranteed that
It is safe to use, improve the use intelligent level of product.
It should be noted that each embodiment in this specification is described by the way of progressive, each embodiment
What is stressed is all difference from other examples, between each embodiment same or similar part mutually referring to
.For device class embodiment, since it is basicly similar to embodiment of the method, so description is fairly simple, it is related
Part illustrates referring to the part of embodiment of the method.
It is worth noting that, in above device embodiment, included modules are simply drawn according to function logic
Point, but above-mentioned division is not limited to, as long as corresponding function can be realized；In addition, each function module is specific
Title is also only to facilitate mutually distinguish, the protection domain being not intended to limit the invention.
It will appreciated by the skilled person that all or part of step in realization the various embodiments described above method is can
Relevant hardware to be instructed to complete by program, corresponding program can be stored in a computer read/write memory medium
In, the storage medium, such as ROM/RAM, disk or CD.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
All any modification, equivalent and improvement made within refreshing and principle etc., should all be included in the protection scope of the present invention.
Claims (10)
- A kind of 1. method of fingerprint image analysis, which is characterized in that the described method includes：Gather the fingerprint image data of user；Frequency-domain transform is carried out to the fingerprint image data, and calculates the line of the fingerprint image data after the frequency-domain transform Linear distance；Signature analysis is carried out according to the ridge distance, determines the identity attribute classification of the user.
- 2. according to the method described in claim 1, it is characterized in that, described carry out signature analysis according to the ridge distance, really The identity attribute classification of the fixed user includes：The fingerprint characteristic of the user is determined according to the ridge distance, wherein, the fingerprint characteristic includes fingerprint density, fingerprint Fineness degree and finger wear degree at least one or any combination；The group property of the user is judged according to the fingerprint characteristic.
- 3. method according to claim 1 or 2, which is characterized in that described that frequency domain change is carried out to the fingerprint image data It changes, and before calculating the ridge distance of the fingerprint image data after the frequency-domain transform, the method further includes：The fingerprint image data is normalized, obtains identical with pre-set dimension scope and predetermined luminance range return One changes image data；The normalized image data are filtered, remove noise jamming；Binary conversion treatment is carried out to the normalized image data after filtering process, obtains binary image data.
- 4. method according to claim 1 or 2, which is characterized in that described that frequency domain change is carried out to the fingerprint image data It changes, and the ridge distance for calculating the fingerprint image data after the frequency-domain transform includes：According to the gray value of each pixel in the binary image data, two-dimensional discrete Fu is carried out to each pixel In leaf transformation, obtain the frequency spectrum data of the fingerprint image data, wherein, the frequency spectrum data be the fingerprint image data in The distributed data of identical frequency circumference；According to the frequency spectrum data, the ridge distance of the fingerprint image data is calculated.
- 5. according to the method described in claim 4, it is characterized in that, described according to the frequency spectrum data, the fingerprint image is calculated As the ridge distance of data includes：Spectral centroid point is determined according to the frequency spectrum data；Using the spectral centroid point as dot, the frequency spectrum annulus of the pixel composition of same frequency spectrum is determined；The ridge distance of the fingerprint image data is calculated by formula d=W/R, wherein, d is the ridge distance, and W is the frequency The width of the corresponding fingerprint image of modal data, R are the average value of the radius of the frequency spectrum annulus.
- 6. a kind of device of fingerprint image analysis, which is characterized in that described device includes：Acquisition module, for gathering the fingerprint image data of user；Computing module for carrying out frequency-domain transform to the fingerprint image data, and calculates the finger after the frequency-domain transform The ridge distance of print image data；Identification module for carrying out signature analysis according to the ridge distance, determines the identity attribute classification of the user.
- 7. device according to claim 6, which is characterized in that the identification module includes：Feature determination sub-module, for determining the fingerprint characteristic of the user according to the ridge distance, wherein, the fingerprint is special Sign includes fingerprint density, fingerprint fineness degree and finger wear degree at least one or any combination；Determined property submodule, for judging the group property of the user according to the fingerprint characteristic.
- 8. the device according to claim 6 or 7, which is characterized in that described device further includes：Normalize module, for the fingerprint image data to be normalized, obtain with pre-set dimension scope and preset The identical normalized image data of brightness range；Filter module for being filtered to the normalized image data, removes noise jamming；Binarization block for carrying out binary conversion treatment to the normalized image data after filtering process, obtains binaryzation Image data.
- 9. the device according to claim 6 or 7, which is characterized in that the computing module includes：Fourier transformation submodule, for the gray value according to each pixel in the binary image data, to described every A pixel carries out two dimensional discrete Fourier transform, obtains the frequency spectrum data of the fingerprint image data, wherein, the spectrum number According to the distributed data for identical frequency circumference in the fingerprint image data；Ridge distance computational submodule, for according to the frequency spectrum data, calculating the ridge distance of the fingerprint image data.
- 10. device according to claim 9, which is characterized in that the ridge distance computational submodule includes：Center determination unit, for determining spectral centroid point according to the frequency spectrum data；Annulus determination unit, for using the spectral centroid point as dot, determining the frequency spectrum circle of the pixel of same frequency spectrum composition Ring；Metrics calculation unit, for pressing the ridge distance that formula d=W/R calculates the fingerprint image data, wherein, d is described Ridge distance, W are the width of the corresponding fingerprint image of the frequency spectrum data, and R is the average value of the radius of the frequency spectrum annulus.
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| CN109815935A (en) * | 2019-02-20 | 2019-05-28 | Oppo广东移动通信有限公司 | Electronic device, fingerprint authentication method and Related product |
| CN112232159A (en) * | 2020-09-30 | 2021-01-15 | 墨奇科技（北京）有限公司 | Fingerprint identification method, device, terminal and storage medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109711259A (en) * | 2018-11-27 | 2019-05-03 | Oppo广东移动通信有限公司 | Fingerprint input method and relevant device |
| CN109815935A (en) * | 2019-02-20 | 2019-05-28 | Oppo广东移动通信有限公司 | Electronic device, fingerprint authentication method and Related product |
| CN112232159A (en) * | 2020-09-30 | 2021-01-15 | 墨奇科技（北京）有限公司 | Fingerprint identification method, device, terminal and storage medium |
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