CN107273851A - A kind of fingerprint sensing systems - Google Patents

A kind of fingerprint sensing systems Download PDF

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CN107273851A
CN107273851A CN201710453478.3A CN201710453478A CN107273851A CN 107273851 A CN107273851 A CN 107273851A CN 201710453478 A CN201710453478 A CN 201710453478A CN 107273851 A CN107273851 A CN 107273851A
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fingerprint
msub
moment
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CN107273851B (en
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杨林
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Taizhou Longze Environmental Technology Co., Ltd.
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Shenzhen Sen Yang Environmental Protection Mstar Technology Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/12Fingerprints or palmprints
    • G06V40/13Sensors therefor
    • G06V40/1306Sensors therefor non-optical, e.g. ultrasonic or capacitive sensing

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  • Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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  • Theoretical Computer Science (AREA)
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Abstract

The invention provides a kind of fingerprint sensing systems, including fingerprint sensor module, analog-to-digital conversion module, finger print data processing module and memory module, the fingerprint sensor module is used to obtain target fingerprint image;The analog-to-digital conversion module is used to target fingerprint image being transformed into data signal from analog signal, obtains digital fingerprint signal;The Fingerprint Processing Module is compressed for digital fingerprint signal, the digital fingerprint signal after being compressed;The memory module is used to store the digital fingerprint signal after compression.The fingerprint image that the present invention collects sensor is converted into data signal, and stored again after being compressed processing, increase the data volume that fixed storage space can be stored, reduce carrying cost, it can be applied to multiple fields, such as huge system of fingerprint reading card device, fingerprint ID authentication system data volume or device.

Description

A kind of fingerprint sensing systems
Technical field
The present invention relates to fingerprint sensing field, and in particular to a kind of fingerprint sensing systems.
Background technology
Fingerprint sensing systems or fingerprint sensing device are logical when needing storage in face of huge finger print data in correlation technique Often need huge memory space, and with finger print identifying, the popularization of checking, and fingerprint image definition raising, it is necessary to Memory space will be increasing, cause the replacing of memory very frequent, but in fact can by filter out some it is inessential or Person influences little details in fingerprint information, and reduction, which is accounted for, deposits and will not improve validation error to fingerprint authentication.
The content of the invention
In view of the above-mentioned problems, a kind of the present invention is intended to provide fingerprint sensing systems.
The purpose of the present invention is realized using following technical scheme:
A kind of fingerprint sensing systems, a kind of fingerprint sensing systems, it is characterized in that, including fingerprint sensor module, modulus turn Change the mold block, finger print data processing module and memory module, the fingerprint sensor module and the wired company of the mode conversion module Connect, for obtaining target fingerprint image;The analog-to-digital conversion module and the Fingerprint Processing Module wired connection, for by target Fingerprint image is transformed into data signal from analog signal, obtains digital fingerprint signal;The Fingerprint Processing Module and the storage Module wired connection, is compressed for digital fingerprint signal, the digital fingerprint signal after being compressed;The memory module is used Digital fingerprint signal after storage compression.
Beneficial effects of the present invention are:The fingerprint image that the present invention collects sensor is converted into data signal, goes forward side by side Stored again after row compression processing, increase the data volume that fixed storage space can be stored, reduce carrying cost, can answer For multiple fields, such as huge system of fingerprint reading card device, fingerprint ID authentication system data volume or device.
Brief description of the drawings
Using accompanying drawing, the invention will be further described, but the embodiment in accompanying drawing does not constitute any limit to the present invention System, for one of ordinary skill in the art, on the premise of not paying creative work, can also be obtained according to the following drawings Other accompanying drawings.
Fig. 1 is the frame construction drawing of the present invention;
Fig. 2 is the frame construction drawing of the finger print data processing module of the present invention.
Reference:
Fingerprint sensor module 1, analog-to-digital conversion module 2, finger print data processing module 3, processing of memory module 4, first Module 301, second processing submodule 302 and Error processing submodule 303.
Embodiment
With reference to following application scenarios, the invention will be further described.
Referring to Fig. 1, a kind of fingerprint sensing systems of the present embodiment, a kind of fingerprint sensing systems, it is characterized in that, including fingerprint Sensor assembly 1, analog-to-digital conversion module 2, finger print data processing module 3 and memory module 4, the fingerprint sensor module 1 with The wired connection of mode conversion module 2, for obtaining target fingerprint image;At the analog-to-digital conversion module 2 and the fingerprint The wired connection of module 3 is managed, for target fingerprint image to be transformed into data signal from analog signal, digital fingerprint signal is obtained; The Fingerprint Processing Module 3 and the wired connection of memory module 4, are compressed for digital fingerprint signal, obtain after compression Digital fingerprint signal;The memory module 4 is used to store the digital fingerprint signal after compression.
Preferably, the fingerprint sensor module includes fingerprint reading device, and the fingerprint reading device is electrostatic capacitance Type finger print reading sensor, its liquid crystal board is arranged as the transparent substrates liquid crystal board of two-dimensional array using detection electrode.
Preferably, the detection electrode is transparency electrode.
The above embodiment of the present invention, is converted into data signal, and be compressed place by the fingerprint image that sensor is collected Stored again after reason, increase the data volume that fixed storage space can be stored, reduce carrying cost, can be applied to a variety of The huge system of field, such as fingerprint reading card device, fingerprint ID authentication system data volume or device.
Preferably, as shown in Fig. 2 the finger print data processing module includes the first processing submodule, second processing submodule Block and Error processing submodule;
The first processing submodule calculates the time of digital fingerprint signal using self-defined boundary operator calculation formula The fingerprint boundary operator of data point in sequence, then carries out convolution fortune by the data point in fingerprint boundary operator and time series Calculate, obtain the edge amplitude of each data point, be specially:
(1) member in target fingerprint image construction the time series N, N that the analog-to-digital conversion module is changed within x cycle Element includes finger print data value and moment, note N={ n1=(g11),n2=(g22),n3=(g33),…,nx=(gxx), It is abbreviated N={ n1,n2,n3,…,nx, x is time series N length, nx=(gxx) represent time series in τxMoment fingerprint number It is g according to valuexFinger print data point;
The fingerprint boundary operator of data point in time series N is calculated one by one, defines the fingerprint side of data point in time series N Edge operator is:
T(a)u=(nu+a-na)
In formula, T (a)uRepresent fingerprint boundary operator when u-th of moment incremental time is a, nu+aAnd naRespectively time sequence U+a and the finger print data point at a-th of moment in N are arranged, u represents u-th of time, and a represents incremental time, 1≤u≤x ,-b≤a ≤ b, is boundary operator detection window length, and b is set as 3;
(2) edge amplitude of each data point in time series N, the self-defined edge amplitude calculation formula of use are calculated For:
wu=Σ (nu+a*T(a)u-na*T(a)u)
In formula, wuRepresent the edge amplitude at u-th of moment, nu+aFor the finger print data at u+a moment in time series N Point, * represents discrete convolution, T (a)uRepresent fingerprint boundary operator when u-th of moment incremental time is a;
Edge amplitude is represented near the variation tendency of sequence in the finger print data vertex neighborhood, the more big then point of edge amplitude Finger print data fluctuation is more violent;Less edge amplitude represents that the finger print data point in its neighborhood lies substantially in same change and become Gesture.
The above embodiment of the present invention, using by calculating fingerprint boundary operator, then by fingerprint boundary operator and fingerprint number Strong point carries out convolution algorithm, is conducive to filtering out target fingerprint picture noise, and the time series of digital fingerprint signal is smoothed, and The data point in time series to be processed, which will be needed, when carrying out convolution algorithm carries out cooperate computing, certain journey with other data points Operand is reduced on degree, it is to avoid the single computing complex situations occurred when being calculated.
Preferably due to which the target fingerprint image of fingerprint sensor module collection is obtained after mode conversion module is changed Data constitute time series N be a time-varying non-stationary random process, over time, data characteristics may Change, so that the judgement to time series data marginal point and selection are influenceed, to avoid the generation of such case, described Two processing modules are by edge amplitude wuDigital quantization processing is carried out, edge strength is obtained, the big finger print data of edge strength is chosen Point as target fingerprint image border point, wherein the self-defined edge strength calculation formula used for:
In formula, QuFor the edge strength at u-th of moment, b is the boundary operator detection window length of setting, b ≠ 0, h () For selection function, z is the variable of selection function, wuAnd wzFor the edge amplitude at u-th of moment and z-th of moment;
Choose the edge strength Q in the range of detection windowuTarget fingerprint image border point is used as the data point of extreme value.
The above embodiment of the present invention, carries out digital quantization processing by edge amplitude and obtains edge strength, utilize edge strength Rather than edge amplitude is chosen to target fingerprint image border point, it is to avoid when the feature of target fingerprint image changes The point mistake selection of target fingerprint image border is caused, while directly being carried out using edge strength to target fingerprint image border point Selection, reduces the operand of second processing submodule so that this fingerprint sensing systems can be run on limited hardware resource.
Preferably, the Error processing module is used in the case of edge strength identical, chooses interpolation error less Point as target fingerprint image border point, the interpolation error calculation formula used for:
In formula, C represents interpolation error, 0<p<s<q<X, x are time series N length, when q, p, s represent q, p, s respectively Carve, nq、np、nsThe finger print data point at q, p, s moment is represented respectively;
ns LRepresent to calculate obtained fitting data point at the s moment using linear interpolation method, L represents linear interpolation;
It is M to calculate required target fingerprint sum of image edge points mesh, and M=x × (1- μ), x is time series N length, μ For the compression ratio of setting, and the less M data point of interpolation error is chosen as the target fingerprint image border point finally determined;
Finally obtain a new time series N '={ n1′,n2′,n3′,…,nx', nx' represent the xth after overcompression Individual finger print data point.
The above embodiment of the present invention, it is contemplated that to the selection of target fingerprint marginal point in the case of edge strength identical, have It is not lost beneficial to important information in the original target fingerprint image of guarantee, it is ensured that carry out accuracy when fingerprint authentication or certification, And remain the Main Morphology of time series during to the compression of digital fingerprint signal and minor details are compressed, reduce this Data traffic in fingerprint sensing systems, reduces communication energy consumption, can adapt to the time series of different fluctuation characteristics.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than to present invention guarantor The limitation of scope is protected, although being explained with reference to preferred embodiment to the present invention, one of ordinary skill in the art should Work as understanding, technical scheme can be modified or equivalent substitution, without departing from the reality of technical solution of the present invention Matter and scope.

Claims (6)

1. a kind of fingerprint sensing systems, it is characterized in that, including the processing of fingerprint sensor module, analog-to-digital conversion module, finger print data Module and memory module, the fingerprint sensor module and the mode conversion module wired connection, for obtaining target fingerprint Image;The analog-to-digital conversion module and the Fingerprint Processing Module wired connection, for by target fingerprint image from analog signal Data signal is transformed into, digital fingerprint signal is obtained;The Fingerprint Processing Module and the memory module wired connection, for counting Word fingerprint signal is compressed, the digital fingerprint signal after being compressed;The memory module is used to store the numeral after compression Fingerprint signal.
2. a kind of fingerprint sensing systems according to claim 1, it is characterized in that, the fingerprint sensor module includes fingerprint Reading device, the fingerprint reading device is capacitance type finger print reading sensor, and its liquid crystal board is arranged using detection electrode For the transparent substrates liquid crystal board of two-dimensional array.
3. a kind of fingerprint sensing systems according to claim 2, it is characterized in that, the detection electrode is transparency electrode.
4. a kind of fingerprint sensing systems according to claim 1, it is characterized in that, the finger print data processing module includes the One processing submodule, second processing submodule and Error processing submodule;
The first processing submodule calculates the time series of digital fingerprint signal using self-defined boundary operator calculation formula The fingerprint boundary operator of middle data point, then carries out convolution algorithm by the data point in fingerprint boundary operator and time series, obtains The edge amplitude of each data point is obtained, is specially:
(1) the element bag in target fingerprint image construction the time series N, N that the analog-to-digital conversion module is changed within x cycle Include finger print data value and moment, note N={ n1=(g11),n2=(g22),n3=(g33),…,nx=(gxx), brief note N={ n1,n2,n3..., nx, x is time series N length, nx=(gxx) represent time series in τxMoment finger print data value For gxFinger print data point;
The fingerprint boundary operator of fingerprint data point in time series N is calculated one by one, defines the fingerprint side of data point in time series N Edge operator is:
T(a)u=(nu+a-na)
In formula, T (a)uRepresent fingerprint boundary operator when u-th of moment incremental time is a, nu+aAnd naRespectively time series N In u+a and the finger print data point at a-th of moment, u represents u-th of moment, and a represents incremental time, 1≤u≤x ,-b≤a≤b, B is boundary operator detection window length;
(2) calculate the edge amplitude of each data point in time series N, the self-defined edge amplitude calculation formula used for:
wu=Σ (nu+a*T(a)u-na*T(a)u)
In formula, wuRepresent the edge amplitude at u-th of moment, nu+aFor the finger print data point at u+a moment in time series N, * is represented Discrete convolution, T (a)uRepresent fingerprint boundary operator when u-th of moment incremental time is a.
5. a kind of fingerprint sensing systems according to claim 4, it is characterized in that, the Second processing module is used for edge Amplitude wuDigital quantization processing is carried out, edge strength is obtained, the big data point of edge strength is chosen and is used as target fingerprint image side Edge point, wherein the self-defined edge strength calculation formula used for:
<mrow> <msub> <mi>Q</mi> <mi>u</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>u</mi> <mo>-</mo> <mi>b</mi> </mrow> <mrow> <mi>u</mi> <mo>+</mo> <mi>b</mi> </mrow> </munderover> <mo>&amp;lsqb;</mo> <mi>h</mi> <mrow> <mo>(</mo> <mi>u</mi> <mo>+</mo> <mfrac> <mi>b</mi> <mn>2</mn> </mfrac> <mo>)</mo> </mrow> <mo>+</mo> <mi>h</mi> <mrow> <mo>(</mo> <mi>u</mi> <mo>-</mo> <mfrac> <mi>b</mi> <mn>2</mn> </mfrac> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow>
<mrow> <mi>h</mi> <mrow> <mo>(</mo> <mi>z</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mn>1</mn> </mtd> <mtd> <mrow> <msub> <mi>w</mi> <mi>u</mi> </msub> <mo>-</mo> <msub> <mi>w</mi> <mi>z</mi> </msub> <mo>&gt;</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </mtd> <mtd> <mrow> <msub> <mi>w</mi> <mi>u</mi> </msub> <mo>-</mo> <msub> <mi>w</mi> <mi>z</mi> </msub> <mo>&lt;</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow>
In formula, QuFor the edge strength at u-th of moment, b is the boundary operator detection window length of setting, and b ≠ 0, h () is choosing Function is selected, z is the variable of selection function, wuAnd wzFor the edge amplitude at u-th of moment and z-th of moment;
Choose the edge strength Q in the range of detection windowuTarget fingerprint image border point is used as the data point of extreme value.
6. a kind of fingerprint sensing systems according to claim 5, it is characterized in that, the Error processing module is used at edge In the case of intensity identical, choose the less point of interpolation error and be used as target fingerprint image border point, the interpolation error meter of use Calculating formula is:
<mrow> <mi>C</mi> <mo>=</mo> <msqrt> <mrow> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>s</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>x</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mi>s</mi> </msub> <mo>-</mo> <msup> <msub> <mi>n</mi> <mi>s</mi> </msub> <mi>L</mi> </msup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>s</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>x</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mrow> <mi>s</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>-</mo> <msup> <msub> <mi>n</mi> <mi>s</mi> </msub> <mi>L</mi> </msup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow>
<mrow> <msup> <msub> <mi>n</mi> <mi>s</mi> </msub> <mi>L</mi> </msup> <mo>=</mo> <msub> <mi>n</mi> <mrow> <mi>s</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>+</mo> <mfrac> <mrow> <msub> <mi>n</mi> <mi>q</mi> </msub> <mo>-</mo> <msub> <mi>n</mi> <mi>p</mi> </msub> </mrow> <mrow> <mi>q</mi> <mo>-</mo> <mi>p</mi> </mrow> </mfrac> <mo>&amp;times;</mo> <mrow> <mo>(</mo> <mi>s</mi> <mo>-</mo> <mi>p</mi> <mo>)</mo> </mrow> </mrow>
In formula, C represents interpolation error, 0<p<s<q<X, x are time series N length, and q, p, s represent q, p, s moment, n respectivelyq、 np、nsThe finger print data point at q, p, s moment is represented respectively;
ns LRepresent to calculate obtained fitting data point at the s moment using linear interpolation method, L represents linear interpolation;
It is M to calculate required target fingerprint sum of image edge points mesh, and M=x × (1- μ), x is time series N length, and μ is to set Fixed compression ratio, and the less M data point of interpolation error is chosen as the target fingerprint image border point finally determined;
Finally obtain a new time series N '={ n1′,n2′,n3′,…,nx', nx' represent x-th after overcompression finger Line data point.
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CN101819630A (en) * 2010-04-09 2010-09-01 浙江理工大学 Fingerprint identification system and identification method based on pressure sensitivity fingerprint acquisition and DSP (Digital Signal Processing) algorithm
CN101925091A (en) * 2010-07-29 2010-12-22 中国地质大学(武汉) Data compression method of wireless sensor network nodes based on non-threshold
CN105491614A (en) * 2016-01-22 2016-04-13 中国地质大学(武汉) Wireless sensor network abnormal event detection method and system based on secondary mixed compression
EP3051700A1 (en) * 2015-01-29 2016-08-03 HGST Netherlands B.V. Hardware efficient fingerprinting
CN106056119A (en) * 2016-05-24 2016-10-26 深圳市至高通信技术发展有限公司 Fingerprint photograph compression transmission method and system
CN106203303A (en) * 2016-06-30 2016-12-07 北京小米移动软件有限公司 Fingerprint identification device and method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1841406A (en) * 2005-03-31 2006-10-04 芯微技术(深圳)有限公司 Binary processing method for decreasing fingerprint collection data volume
CN101819630A (en) * 2010-04-09 2010-09-01 浙江理工大学 Fingerprint identification system and identification method based on pressure sensitivity fingerprint acquisition and DSP (Digital Signal Processing) algorithm
CN101925091A (en) * 2010-07-29 2010-12-22 中国地质大学(武汉) Data compression method of wireless sensor network nodes based on non-threshold
EP3051700A1 (en) * 2015-01-29 2016-08-03 HGST Netherlands B.V. Hardware efficient fingerprinting
CN105844210A (en) * 2015-01-29 2016-08-10 Hgst荷兰有限公司 Hardware efficient fingerprinting
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