CN107169471B - A kind of fingerprint recognition system based on image co-registration - Google Patents
A kind of fingerprint recognition system based on image co-registration Download PDFInfo
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- CN107169471B CN107169471B CN201710421000.2A CN201710421000A CN107169471B CN 107169471 B CN107169471 B CN 107169471B CN 201710421000 A CN201710421000 A CN 201710421000A CN 107169471 B CN107169471 B CN 107169471B
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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
- G06V40/13—Sensors therefor
- G06V40/1318—Sensors therefor using electro-optical elements or layers, e.g. electroluminescent sensing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/50—Image enhancement or restoration by the use of more than one image, e.g. averaging, subtraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/30—Noise filtering
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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
Abstract
The present invention provides a kind of fingerprint recognition systems based on image co-registration, including finger print acquisition module, D/A converter module, fingerprint image processing module, fingerprint database module and result verification module, the finger print acquisition module is used to acquire the infrared image and ultraviolet image of target fingerprint；The D/A converter module is used to carry out digital-to-analogue conversion respectively with ultraviolet image to the infrared image of target fingerprint；The fingerprint image processing module is used to carry out denoising, decomposition and synthesis with ultraviolet image to the infrared image of target fingerprint to handle, and obtains target fingerprint image；The fingerprint image of standard is stored in the fingerprint database module；Target fingerprint image and the fingerprint image of standard are carried out contrast verification by the result verification module, obtain fingerprint authentication as a result, and being shown to result.The present invention merges the infrared image of target fingerprint with ultraviolet image, carries out fingerprint recognition using the fingerprint image after fusion, improves the accuracy of fingerprint recognition.
Description
Technical field
The present invention relates to fingerprint recognition fields, and in particular to a kind of fingerprint recognition system based on image co-registration.
Background technology
Fingerprint recognition system generally use single camera in the prior art or single sensor adopt target fingerprint
Collection, the fingerprint recognition system of single camera or single sensor disclosure satisfy that some required precisions not and are very high applied field
Scape, such as fingerprint is unlocked, fingerprint is checked card, fingerprint access control etc., if but it is very high for some accuracy, and fingerprint is endless
Whole application scenarios cannot usually be coped with using the fingerprint recognition system of single camera or single sensor.
Invention content
In view of the above-mentioned problems, the present invention is intended to provide a kind of fingerprint recognition system based on image co-registration.
The purpose of the present invention is realized using following technical scheme：
A kind of fingerprint recognition system based on image co-registration, including finger print acquisition module, D/A converter module, fingerprint image
Processing module, fingerprint database module and result verification module, the finger print acquisition module is for acquiring the infrared of target fingerprint
Image and ultraviolet image；The D/A converter module is used to carry out digital-to-analogue respectively with ultraviolet image to the infrared image of target fingerprint
Conversion；The fingerprint image processing module is used to carry out denoising, decomposition and conjunction with ultraviolet image to the infrared image of target fingerprint
At processing, target fingerprint image is obtained；The fingerprint image of standard is stored in the fingerprint database module；The result verification
Target fingerprint image and the fingerprint image of standard are carried out contrast verification by module, obtain fingerprint authentication as a result, and being carried out to result
Display.
Beneficial effects of the present invention are：The present invention merges the infrared image of target fingerprint with ultraviolet image, utilizes
Fingerprint image after fusion carries out fingerprint recognition, is greatly improved the accuracy of fingerprint recognition.
Description of the drawings
Using attached drawing, the invention will be further described, but the embodiment in attached drawing does not constitute any limit to the present invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the frame construction drawing of the present invention；
Fig. 2 is the frame construction drawing of the fingerprint image processing module of the present invention.
Reference numeral：
Finger print acquisition module 1, D/A converter module 2, fingerprint image processing module 3, fingerprint database module 4, result are tested
It demonstrate,proves module 5, fingerprint image preprocessing submodule 31, fingerprint image resolution process submodule 32 and fingerprint image and merges submodule
33。
Specific implementation mode
In conjunction with following application scenarios, the invention will be further described.
Referring to Fig. 1, including finger print acquisition module 1, D/A converter module 2, fingerprint image processing module 3, fingerprint database
Module 4 and result verification module 5,1 rear of the finger print acquisition module connects the D/A converter module 2, for acquiring target
The infrared image and ultraviolet image of fingerprint；The D/A converter module 2 is used for infrared image and ultraviolet image to target fingerprint
Digital-to-analogue conversion is carried out respectively；The fingerprint image processing module 3 is used to carry out the infrared image of target fingerprint with ultraviolet image
Denoising, decomposition and synthesis processing, obtain target fingerprint image；The fingerprint image of standard is stored in the fingerprint database module 4
Picture；The result verification module 5 is connect with the fingerprint image processing module 3 and the fingerprint database module 4, is used for mesh
The fingerprint image for marking fingerprint image and standard carries out contrast verification, obtains fingerprint authentication as a result, and being shown to result.
Preferably, it when the finger print acquisition module is acquired the infrared image and ultraviolet image of target fingerprint, uses
Infrared COMS imaging lens are acquired the infrared image of target fingerprint, using ultraviolet CCD imaging lens to target fingerprint
Ultraviolet image is acquired, and LED exciter components are connected in front of ultraviolet CCD imaging lens, and rear is connected with ultraviolet image enhancing
Device, finally connects infrared COMS imaging lens, all camera lens light path coaxials and is placed in parallel.
Preferably, the infrared COMS imaging lens and ultraviolet CCD imaging lens are all double-colored integrated structure.
The above embodiment of the present invention merges the infrared image of target fingerprint with ultraviolet image, after fusion
Fingerprint image carries out fingerprint recognition, is greatly improved the accuracy of fingerprint recognition.
Preferably, as shown in Fig. 2, the fingerprint image processing module includes fingerprint image preprocessing submodule, fingerprint image
As resolution process submodule and fingerprint image merge submodule；The fingerprint image preprocessing submodule is by the infrared figure with noise
Picture and ultraviolet image carry out wavelet transform process, obtain corresponding wavelet coefficient, the wavelet coefficient obtained at this time includes noiseless
Then wavelet coefficient and noise wavelet coefficients utilize the infrared image of improved wavelet threshold function pair target fingerprint and ultraviolet
Image carries out denoising, specially：
(1) obtained wavelet coefficient is carried out by thresholding processing using improved threshold function table, to filter out noise wavelet system
Number, obtain noiseless wavelet coefficient, the improved threshold function table used for：
In formula,Indicate that noiseless wavelet coefficient, ψ are that the infrared image with noise and ultraviolet image carry out at wavelet transformation
The wavelet coefficient obtained after reason, sgn () are sign function, and i is the variable of sign function, and p and q are adjustable parameter, and υ is small echo
Coefficient threshold, ε are that noise criteria is poor；
As p=0 or q=∞, this improved threshold function table is hard threshold function, and as p=1 and q=1, this is improved
Threshold function table is soft-threshold function；
(2) noiseless wavelet coefficient is obtained after being handled using thresholding carries out the infrared image to target fingerprint and ultraviolet figure
As being reconstructed, noiseless infrared image and noiseless ultraviolet image are obtained.
The above embodiment of the present invention passes through the infrared image and ultraviolet image of fingerprint image by improved threshold function table
Band noise wavelet coefficients in the wavelet coefficient obtained after wavelet transform process are filtered out, then using filter out band noise wavelet
Wavelet coefficient after coefficient carries out image reconstruction, obtains side noiseless infrared image and ultraviolet image, carries out fingerprint image and locates in advance
Reason filters out the noise in fingerprint image, to obtain the target fingerprint image graph of high quality in target fingerprint image co-registration
Picture, and improved threshold function table can by adjust p and q value, make improved threshold function table between soft, hard threshold function it
Between, flexibility when enhancing filters out wavelet coefficient.
Preferably, the fingerprint image resolution process submodule is first to passing through the fingerprint image preprocessing resume module
Afterwards, the noiseless infrared image X obtained1With noiseless ultraviolet image X2It is carried out respectively using non-downsampling Contourlet conversion
Resolution process obtains a respective low frequency sub-band coefficient and a series of high-frequency sub-band coefficient, i.e., With
X1 Low(j, k) and X2 Low(j, k) indicates noiseless infrared image X respectively1With noiseless ultraviolet image X2At pixel (j, k)
Low frequency sub-band coefficient,WithIndicate noiseless infrared image X1With the ultraviolet figure of noiseless
As X2The high-frequency sub-band coefficient in n-th of direction of m-th of scale at pixel (j, k), M are scale parameter, and m is indicated m-th
Scale, n are n-th of direction, nmFor the direction number under m-th of scale；
Then the sub-band coefficients and 4 pixels of surrounding pixel at (j, k) obtained after NSCT carries out resolution process
The subband coefficient values of point are compared, with the work of two width noise-free picture pixel of self-defined liveness calculation formula node-by-node algorithm
Jerk utilizes noiseless infrared image X1With noiseless ultraviolet image X2High-frequency sub-band coefficient carry out liveness calculating, obtain picture
The high-frequency sub-band liveness of vegetarian refreshments (j, k), self-defined liveness calculation formula are：
In formula,WithNoiseless infrared image X is indicated respectively1It is ultraviolet with noiseless
Image X2In at (j, k) n-th of direction of m-th of scale of pixel high-frequency sub-band liveness,WithIndicate noiseless infrared image X1With noiseless ultraviolet image X2M-th of scale, n-th of side at (j, k)
To high-frequency sub-band coefficient, Table respectively
Show noiseless infrared image X1With noiseless ultraviolet image X2It is adjacent with the up, down, left and right four directions of pixel at (j, k)
The high-frequency sub-band coefficient in m-th of scale, n-th of direction of pixel；
Similarly, high-frequency sub-band coefficient is changed into low frequency sub-band coefficient, using self-defined liveness calculation formula, to two width
The liveness of the low frequency sub-band of noise-free picture is calculated, and noiseless infrared image X is obtained1With noiseless ultraviolet image X2
The liveness W of the low frequency sub-band of pixel at (j, k)1 Low(j, k) and W2 Low(j,k)。
The above embodiment of the present invention goes out noiseless infrared image and nothing by self-defined liveness calculation formula node-by-node algorithm
The liveness of pixel in noise ultraviolet image reflects that the readability of pixel, the liveness of pixel are got over liveness
High then the point clarity is higher, when according to liveness to infrared image and UV Image Fusion, is conducive to choose and arrives clarity
Higher pixel, obtain quality is higher, more merged comprising minutia after target fingerprint image.
Preferably, the fingerprint image merges submodule first to noiseless infrared image X1With noiseless ultraviolet image X2
Liveness at point (j, k) is compared, and corresponding liveness comparison result is obtained, according to liveness comparison result, antithetical phrase
Band coefficient carries out value again, obtains new high-frequency sub-band coefficient and new low frequency sub-band coefficient, and new sub-band coefficients are made
For the sub-band coefficients of the target fingerprint image after fusion, specially：
In formula, X (j, k) is target fingerprint image after the fusion sub-band coefficients after value again at the point (j, k), X1
(j, k) and X2(j, k) is respectively noiseless infrared image X1With noiseless ultraviolet image X2Sub-band coefficients at point (j, k), W1
(j, k) and W2(j, k) is respectively noiseless infrared image X1With noiseless ultraviolet image X2In at (j, k) pixel liveness,
W1(j, k) includes W1 Low(j, k) andW2(j, k) includes W2 Low(j, k) andX1(j,
K) include X1 Low(j, k) andX2(j, k) includes X2 Low(j, k) andWork as X1(j, k)=
X1 LowWhen (j, k), X2(j, k)=X2 Low(j, k), W1(j, k)=W1 Low(j, k), W2(j, k)=W2 Low(j, k), whenWhen, To adjust threshold value,It is set as 0.5, X1 Low(j, k) and X2 Low(j, k) indicates the infrared figure of noiseless respectively
As X1With noiseless ultraviolet image X2Low frequency sub-band coefficient at pixel (j, k),WithIndicate noiseless infrared image X1With noiseless ultraviolet image X2M-th of scale at pixel (j, k)
N-th of direction high-frequency sub-band coefficient, J and K indicate the width and height of two width noise-free pictures respectively；
Using new high-frequency sub-band coefficient and new low frequency sub-band coefficient as the high-frequency sub-band coefficient of composograph with it is low
Frequency sub-band coefficients, by NSCT inverse transformation reconstructed images, the target fingerprint image after being merged, and exported.
The above embodiment of the present invention, to noiseless infrared image and noiseless ultraviolet image pixel liveness size ratio
Compared with, according to comparison result, different values is taken to the target fingerprint Image Sub-Band coefficient after fusion, be conducive to noise infrared image and
The details of noiseless ultraviolet image is complementary so that and the target fingerprint image after fusion can include the minutia of two images,
When carrying out fingerprint recognition verification, accuracy of identification is greatly improved.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although being explained in detail to the present invention with reference to preferred embodiment, those skilled in the art answer
Work as understanding, technical scheme of the present invention can be modified or replaced equivalently, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (3)
1. a kind of fingerprint recognition system based on image co-registration, characterized in that including finger print acquisition module, D/A converter module,
Fingerprint image processing module, fingerprint database module and result verification module, the finger print acquisition module refer to for acquiring target
The infrared image and ultraviolet image of line；The D/A converter module is used to distinguish the infrared image of target fingerprint with ultraviolet image
Carry out digital-to-analogue conversion；The fingerprint image processing module be used for the infrared image of target fingerprint and ultraviolet image carry out denoising,
It decomposes and synthesis is handled, obtain target fingerprint image；The fingerprint image of standard is stored in the fingerprint database module；It is described
Target fingerprint image and the fingerprint image of standard are carried out contrast verification by result verification module, obtain fingerprint authentication as a result, and right
As a result it is shown；
When the finger print acquisition module is acquired the infrared image and ultraviolet image of target fingerprint, it is imaged using infrared COMS
Camera lens is acquired the infrared image of target fingerprint, is carried out to the ultraviolet image of target fingerprint using ultraviolet CCD imaging lens
Acquisition, ultraviolet CCD imaging lens front are connected with LED exciter components, and rear is connected with ultraviolet image booster, finally connects red
Outer COMS imaging lens, all camera lens light path coaxials and are placed in parallel；
The infrared COMS imaging lens and ultraviolet CCD imaging lens are all double-colored integrated structure；
The fingerprint image processing module includes fingerprint image preprocessing submodule, fingerprint image resolution process submodule and fingerprint
Image co-registration submodule；Infrared image with noise and ultraviolet image are carried out small echo change by the fingerprint image preprocessing submodule
Processing is changed, corresponding wavelet coefficient is obtained, the wavelet coefficient obtained at this time includes noiseless wavelet coefficient and noise wavelet system
Then number carries out denoising, specifically using the infrared image and ultraviolet image of improved wavelet threshold function pair target fingerprint
For：
(1) the progress thresholding processing of obtained wavelet coefficient is obtained with filtering out noise wavelet coefficients using improved threshold function table
To noiseless wavelet coefficient, the improved threshold function table that uses for：
In formula,Noiseless wavelet coefficient is indicated, after ψ is the infrared image with noise and ultraviolet image progress wavelet transform process
Obtained wavelet coefficient, sgn () are sign function, and i is the variable of sign function, and p and q are adjustable parameter, and υ is wavelet coefficient
Threshold value, ε are that noise criteria is poor；
(2) obtained after being handled using thresholding noiseless wavelet coefficient carry out to the infrared image of target fingerprint and ultraviolet image into
Row reconstruct, obtains noiseless infrared image and noiseless ultraviolet image.
2. a kind of fingerprint recognition system based on image co-registration according to claim 1, characterized in that the fingerprint image
Noiseless infrared image X of the resolution process submodule first to after the fingerprint image preprocessing resume module, obtaining1With
Noiseless ultraviolet image X2Resolution process is carried out using non-downsampling Contourlet conversion respectively, obtains a respective low frequency
Sub-band coefficients and a series of high-frequency sub-band coefficient, i.e.,
WithX1 Low(j, k) and X2 Low(j, k) is indicated respectively
Noiseless infrared image X1With noiseless ultraviolet image X2Low frequency sub-band coefficient at pixel (j, k),
WithIndicate noiseless infrared image X1With noiseless ultraviolet image X2M-th of ruler at pixel (j, k)
The high-frequency sub-band coefficient in n-th of direction of degree, M are scale parameter, and m indicates that m-th of scale, n are n-th of direction, nmFor m-th of ruler
Direction number under degree；
Then sub-band coefficients pixel at (j, k) obtained after NSCT carries out resolution process and 4 pixels of surrounding
Subband coefficient values are compared, with enlivening for self-defined two width noise-free picture pixel of liveness calculation formula node-by-node algorithm
Degree, utilizes noiseless infrared image X1With noiseless ultraviolet image X2High-frequency sub-band coefficient carry out liveness calculating, obtain pixel
The liveness of the high-frequency sub-band of point (j, k), self-defined liveness calculation formula are：
In formula,WithNoiseless infrared image X is indicated respectively1With noiseless ultraviolet image
X2In at (j, k) n-th of direction of m-th of scale of pixel high-frequency sub-band liveness,WithIndicate noiseless infrared image X1With noiseless ultraviolet image X2M-th of scale, n-th of side at (j, k)
To high-frequency sub-band coefficient, Noiseless infrared image X is indicated respectively1With the ultraviolet figure of noiseless
As X2The high frequency in m-th of scale, n-th of direction of adjacent pixel with the up, down, left and right four directions of pixel at (j, k)
Sub-band coefficients；
Similarly, high-frequency sub-band coefficient is changed into low frequency sub-band coefficient, using self-defined liveness calculation formula, to two width without making an uproar
The liveness of the low frequency sub-band of acoustic image is calculated, and noiseless infrared image X is obtained1With noiseless ultraviolet image X2At (j, k)
Locate the liveness W of the low frequency sub-band of pixel1 Low(j, k) and W2 Low(j,k)。
3. a kind of fingerprint recognition system based on image co-registration according to claim 2, characterized in that the fingerprint image
Submodule is merged first to noiseless infrared image X1With noiseless ultraviolet image X2Liveness at point (j, k) is compared,
Corresponding liveness comparison result is obtained, according to liveness comparison result, value again is carried out to sub-band coefficients, obtains new height
Frequency sub-band coefficients and new low frequency sub-band coefficient, and using new sub-band coefficients as the subband system of the target fingerprint image after fusion
Number, specially：
In formula, X (j, k) is target fingerprint image after the fusion sub-band coefficients after value again at the point (j, k), X1(j, k) and
X2(j, k) is respectively noiseless infrared image X1With noiseless ultraviolet image X2Sub-band coefficients at point (j, k), W1(j, k) and
W2(j, k) is respectively noiseless infrared image X1With noiseless ultraviolet image X2In at (j, k) pixel liveness, W1(j,k)
Including W1 Low(j, k) andW2(j, k) includes W2 Low(j, k) andX1(j, k) includes
X1 Low(j, k) andX2(j, k) includes X2 Low(j, k) andWork as X1(j, k)=X1 Low(j,
When k), X2(j, k)=X2 Low(j, k), W1(j, k)=W1 Low(j, k), W2(j, k)=W2 Low(j, k), when When, To adjust threshold value,X1 Low(j, k) and X2 Low(j, k) indicates that noiseless is red respectively
Outer image X1With noiseless ultraviolet image X2Low frequency sub-band coefficient at pixel (j, k),WithIndicate noiseless infrared image X1With noiseless ultraviolet image X2M-th of scale at pixel (j, k)
N-th of direction high-frequency sub-band coefficient, J and K indicate the width and height of two width noise-free pictures respectively；
Using new high-frequency sub-band coefficient and new low frequency sub-band coefficient as the high-frequency sub-band coefficient of composograph and low frequency
Band coefficient, by NSCT inverse transformation reconstructed images, the target fingerprint image after being merged, and exported.
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