CN109978803A - Image processing method and device - Google Patents
Image processing method and device Download PDFInfo
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- CN109978803A CN109978803A CN201910162690.3A CN201910162690A CN109978803A CN 109978803 A CN109978803 A CN 109978803A CN 201910162690 A CN201910162690 A CN 201910162690A CN 109978803 A CN109978803 A CN 109978803A
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- 238000003672 processing method Methods 0.000 title claims abstract description 22
- 238000010606 normalization Methods 0.000 claims description 19
- 238000001914 filtration Methods 0.000 claims description 7
- 230000000750 progressive effect Effects 0.000 claims description 6
- 238000000034 method Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 10
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
Classifications
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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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- G06T5/70—
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
- G06V40/1347—Preprocessing; Feature extraction
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20024—Filtering details
Abstract
It include: to judge whether collected original fingerprint image has common-mode noise the invention discloses a kind of image processing method；When the original fingerprint image has common-mode noise, splicing in row is carried out to the original fingerprint image and obtains the first fingerprint image；Splicing in the ranks is carried out to first fingerprint image and obtains the second fingerprint image.The present invention also provides a kind of image processing apparatus, by carrying out splicing in row to the fingerprint image with common-mode noise and in the ranks splicing obtains relatively clear fingerprint image, solves fingerprint image fuzzy problem caused by the interference due to common-mode noise.
Description
Technical field
The present invention relates to fingerprint sensing systems technical fields, and in particular to a kind of image processing method and device.
Background technique
Fingerprint is the texture of the uneven formation of finger surface skin.The texture features of fingerprint have uniqueness, stability,
Therefore it is usually used to the foundation as identification.Fingerprint sensing systems are exactly a kind of sensing system that identity is identified by fingerprint
System, including capacitance type fingerprint sensor-based system.But it is non-when carrying out the identification of fingerprint image using capacitance type fingerprint sensor-based system
It is often easy the interference by common-mode noise (such as charger noise, transformer noise and switching power supply noise), will lead to fingerprint
Image recognition is abnormal.And the randomness of common-mode noise is not easy image recovery, and it also can not be extensive by normal filtering method
It is multiple.
Summary of the invention
In order to solve the above-mentioned technical problems, the present invention provides a kind of image processing method and devices, it can be determined that fingerprint
Whether sensor-based system fingerprint image collected has the interference by common-mode noise, and can solve since common-mode noise causes
Fingerprint image fuzzy problem.
A kind of image processing method provided according to the present invention characterized by comprising judge collected original fingerprint
Whether image has common-mode noise；When the original fingerprint image has common-mode noise, the original fingerprint image is carried out
Splicing obtains the first fingerprint image in row；Splicing in the ranks is carried out to first fingerprint image and obtains the second fingerprint image
Picture.
Preferably, splicing includes: to be grouped in each traveling every trade to the original fingerprint image in the row；It obtains
Take the edge slope being respectively grouped in same a line；One of grouping is indulged according to the edge slope of adjacent two grouping of same a line
To stretching；And one grouping is translated according to the brim height difference of adjacent two grouping of same a line.
Preferably, the longitudinal stretching makes the edge slope with adjacent two grouping of a line identical.
Preferably, the translation is so that the brim height difference of adjacent two grouping is zero with a line.
Preferably, the splicing in the ranks includes: to obtain the mean value and standard of every a line in first fingerprint image
Difference；Standard deviation normalized, which is carried out, according to the mean value of every a line and standard deviation obtains third fingerprint image；To third fingerprint image
As carrying out mean normalization processing.
Preferably, the standard deviation normalized includes: to obtain the standard deviation of other rows with a wherein standard of behaviour row
Ratio between the standard deviation of reference row；The difference between every row of the first fingerprint image and corresponding line mean value is obtained, and will
The difference obtains third fingerprint image multiplied by the ratio.
Preferably, the mean normalization processing includes: by every row of third fingerprint image plus the equal of the reference row
Value is to obtain the second fingerprint image.
It is preferably, described that judge whether collected original fingerprint image has common-mode noise include: to the original finger
Grouping in each traveling every trade of print image；It obtains with the edge slope being respectively grouped in a line；According to the edge slope of each grouping
The brim height for obtaining adjacent two grouping is poor；It sums all brim height differences to obtain offset distance；When the offset distance
When greater than preset threshold, the original fingerprint image has common-mode noise.
Preferably, further includes: gaussian filtering is carried out to the second fingerprint image.
Preferably, the original fingerprint image is obtained in a manner of progressively scanning.
Preferably, the common-mode noise includes charger noise, transformer noise and switching power supply noise.
A kind of image processing apparatus provided according to the present invention characterized by comprising judgment module is adopted for judging
Whether the original fingerprint image collected has common-mode noise；First processing module, for having altogether when the original fingerprint image
When mode noise, splicing in row is carried out to the original fingerprint image and obtains the first fingerprint image；Second processing module is used for
Splicing in the ranks is carried out to first fingerprint image and obtains the second fingerprint image.
Preferably, first processing module includes: grouped element, for each traveling every trade to the original fingerprint image
Interior grouping；Edge slope unit, for obtaining with the edge slope being respectively grouped in a line；Draw unit, for according to same a line
Carry out longitudinal stretching of the edge slope of adjacent two grouping to one of grouping；And translation unit, for according to same a line
It is adjacent two grouping brim height differences to one be grouped translate.
Preferably, the longitudinal stretching makes the edge slope with adjacent two grouping of a line identical.
Preferably, the translation is so that the brim height difference of adjacent two grouping is zero with a line.
Preferably, Second processing module includes: acquiring unit, for obtaining the equal of every a line in first fingerprint image
Value and standard deviation；First normalization unit is obtained for carrying out standard deviation normalized according to the mean value and standard deviation of every a line
To third fingerprint image；Second normalization unit, for carrying out mean normalization processing to third fingerprint image.
Preferably, first normalization unit be used to obtain with the wherein standard of behaviour row standard deviations of other rows with
Ratio between the standard deviation of reference row；And the difference between the every row and corresponding line mean value of the first fingerprint image of acquisition, and
The difference is obtained into third fingerprint image multiplied by the ratio.
Preferably, second normalization unit is used to add every row of third fingerprint image the mean value of the reference row
To obtain the second fingerprint image.
Preferably, the judgment module is used for being grouped in each traveling every trade of the original fingerprint image；It obtains same
The edge slope being respectively grouped in a line；The brim height for obtaining adjacent two grouping according to the edge slope of each grouping is poor；To own
Brim height difference sum to obtain offset distance；When the offset distance is greater than preset threshold, the original fingerprint image tool
There is common-mode noise.
Preferably, further includes: filter module, for carrying out gaussian filtering to the second fingerprint image.
Preferably, the original fingerprint image is obtained in a manner of progressively scanning.
Preferably, the common-mode noise includes charger noise, transformer noise and switching power supply noise.
The beneficial effects of the present invention are: the invention discloses a kind of image processing method and devices, by fingerprint sensing
The collected fingerprint image of device institute carries out noise measuring, and carries out splicing in row to the fingerprint image with common-mode noise
And in the ranks splicing, available more clear fingerprint image, caused by solving the interference due to common-mode noise
Fingerprint image fuzzy problem.
Detailed description of the invention
By referring to the drawings to the description of the embodiment of the present invention, above-mentioned and other purposes of the invention, feature and
Advantage will be apparent from.
Fig. 1 shows the flow chart of image processing method provided in an embodiment of the present invention；
Fig. 2 shows the flow charts of step S100 in the embodiment of the present invention；
Fig. 3 a- Fig. 3 c shows the waveform diagram of the fingerprint image of the embodiment of the present invention；
Fig. 4 shows the flow chart of step S200 in the embodiment of the present invention；
Fig. 5 shows the flow chart of step S300 in the embodiment of the present invention；
Fig. 6 shows the structural block diagram of image processing apparatus provided in an embodiment of the present invention；
Fig. 7 shows the structural schematic diagram of first processing module in image processing apparatus provided in an embodiment of the present invention；
Fig. 8 shows the structural schematic diagram of Second processing module in image processing apparatus provided in an embodiment of the present invention.
Specific embodiment
To facilitate the understanding of the present invention, a more comprehensive description of the invention is given in the following sections with reference to the relevant attached drawings.In attached drawing
Give presently preferred embodiments of the present invention.But the present invention can realize in different forms, however it is not limited to described herein
Embodiment.Opposite, purpose of providing these embodiments is makes the disclosure of the present invention more thorough and comprehensive.
Unless otherwise defined, all technical and scientific terms used herein and belong to technical field of the invention
The normally understood meaning of technical staff is identical.Used term is intended merely to description specifically in the description of the invention herein
The purpose of ground embodiment, it is not intended that in the limitation present invention.
In the following, referring to attached drawing, the present invention is described in detail.
Fig. 1 shows the flow chart of image processing method provided in an embodiment of the present invention.As shown in Figure 1, provided by the invention
Image processing method includes the following steps.
In the step s 100, judge whether collected original fingerprint image has common-mode noise.
In the present embodiment, the corresponding operatings such as fingerprint typing or unlock are being carried out with relevant devices such as fingerprint sensing systems
When, sometimes one of major reason of this failure situation can be caused to be there is a situation where fingerprint typing or unlock failure
Because fingerprint sensing systems fingerprint image collected may receive extraneous common-mode noise, (such as charger noise, transformer are made an uproar
Sound and switching power supply noise) interference.
In the embodiment of the present invention, original fingerprint image, and original fingerprint figure collected are collected in fingerprint sensor
As carrying out noise detection step after carrying out typing/unlock failure, noise measuring is carried out to original fingerprint image, judges to be acquired
Original fingerprint image whether there is common-mode noise.
Specific steps are as shown in Fig. 2, step S100 includes step S110 to step S150.
In step s 110, to being grouped in each traveling every trade of original fingerprint image.
In the embodiment of the present invention, the mode that capacitance type fingerprint sensor-based system acquires original fingerprint image is progressive scan,
During progressive scan, each row carries out multi collect, can acquire multiple pixels each time.With a line acquisition 5 times, adopt every time
For collecting 8 pixels, every row of original fingerprint image can be divided into 5 groupings by we, and each grouping includes 8 pixels.
Due to multiple pixels common-mode noise N1 having the same in collected one grouping；And next point acquired
Common-mode noise possessed by multiple pixels of group is N2, and so on, possessed common mode between two neighboring grouping in every row
Noise is all different.
Fingerprint image collected for fingerprint sensing systems, in same a line of acquired fingerprint image, due to adjacent
Multiple pixels between keep original trend, then can have certain offset between two groups of adjacent pixels, need to estimate
Calculation and record-shifted value d.
Step S120: it obtains with the edge slope being respectively grouped in a line.
In the present embodiment, after acquired fingerprint image has common-mode noise, original fingerprint image can become k*X+ from X
d.Wherein, k is the slope of fingerprint image, and d is deviant (or brim height is poor), and the two is any real number.
Fig. 3 a shows the waveform diagram of original fingerprint image.Wherein, for the first row, in the first grouping and second packet phase
Adjacent edge calculates the edge slope k11 of the first grouping and the edge slope k12 of second packet.And so on, it obtains original
Edge slope k11~the k1n being respectively grouped in the first row in fingerprint image.
And so on, obtain the edge slope km1~kmn being respectively grouped in the m row in original fingerprint image.
Step S130: the brim height for obtaining adjacent two grouping according to the edge slope of each grouping is poor.
According to the edge slope of one of grouping, predict that a pixel adjacent with the grouping in next grouping may
The position of appearance；Then record actual acquisition to fingerprint image in the pixel physical location, calculate predicted position and reality
Difference in height between the position of border is poor as brim height.
In fig. 3 a, first is predicted in next grouping according to the edge slope k11 of the first grouping for the first row
The position that pixel is likely to occur obtains between two positions further according to the physical location of first pixel in next grouping
Difference in height is as brim height difference d11.And so on, it obtains in the first row in original fingerprint image between adjacent two grouping
Brim height difference d11-d1 (n-1).
And so on, obtain the brim height difference dm1-dm in the m row in original fingerprint image between adjacent two grouping
(n-1)。
Step S140: it sums all brim height differences to obtain offset distance.
In this step, obtain every a line be respectively grouped in all two adjacent groups brim height it is poor, calculate in every a line own
The sum of brim height difference, wherein the sum of brim height difference of the first row d1=d11+d12+ ...+d1 (n-1), the second row
The sum of brim height difference d2=d21+d22+ ...+d2 (n-1), the sum of brim height difference of m row are dm=dm1+dm2
+……+dm(n-1).So sum the brim height difference of adjacent packets in all rows to obtain the offset distance of the original fingerprint image
From d, d=d1+d2+ ...+dm.
Step S150: when offset distance is greater than preset threshold, original fingerprint image has common-mode noise.
In this step, compare the size of gained offset distance d and preset threshold dx, judges that the collected fingerprint image of institute is
The no interference having by common-mode noise.Specifically, when offset distance d is greater than preset threshold dx, then illustrate the collected fingerprint of institute
Image has the interference by common-mode noise；When offset distance d is less than or equal to preset threshold dx, then illustrate the collected fingerprint of institute
Image is not by the interference of common-mode noise.
If discovery fingerprint image does not have common-mode noise after tested, the original of common mold noise interference can be excluded
Cause is not described herein with facilitating further problem to detect.
In step s 200, when original fingerprint image has common-mode noise, splicing in row is carried out to original fingerprint image
Processing obtains the first fingerprint image.
In the embodiment of the present invention, there is signal joining method in the row of the fingerprint image of noise jamming to be mainly used in each
In multiple adjacent pixels of collected fingerprint image, the general trend by signal and original signal after common mold noise interference
Identical situation.
Specific steps are as shown in figure 4, step S200 includes step S210 to step S250.
In step S210, to being grouped in each traveling every trade of the original fingerprint image with common-mode noise.
In step S220, obtain with the edge slope being respectively grouped in a line.
Fig. 3 a shows the waveform diagram of original fingerprint image.Wherein, for the first row, in the first grouping and second packet phase
Adjacent edge calculates the edge slope k11 of the first grouping and the edge slope k12 of second packet.And so on, it obtains original
Edge slope k11~the k1n being respectively grouped in the first row in fingerprint image.
And so on, obtain the edge slope km1~kmn being respectively grouped in the m row in original fingerprint image.
In step S230, longitudinal drawing is carried out to one of grouping according to the edge slope of adjacent two grouping of same a line
It stretches.
In the present embodiment, the longitudinal stretching makes the edge slope with adjacent two grouping of a line identical.
Fig. 3 b shows the waveform diagram after original fingerprint image longitudinal stretching.For the first row, with the edge of the first grouping
On the basis of slope k 11, longitudinal stretching is carried out to second packet, so that the first grouping is identical with the edge slope of second packet.
Step S240, according to same a line it is adjacent two grouping brim height difference to one be grouped translate.
In the present embodiment, the brim height for obtaining adjacent two grouping according to the edge slope of each grouping is poor, then basis
With a line the brim height differences of adjacent two grouping to one be grouped translate so that the edge of adjacent two grouping is high with a line
Spending difference is zero.
As shown in Figure 3c, for the first row, by second packet progress longitudinal translation make the first grouping and second packet it
Between brim height difference be zero.
In step S300, splicing in the ranks is carried out to the first fingerprint image and obtains the second fingerprint image.
In the present embodiment, there is the joining method of signal in the ranks of the fingerprint image of noise jamming to be mainly used between line by line
Noise is random, and the case where mutual also no similar Slope relationship.
Specific steps are as shown in figure 5, step S300 includes step S310 to step S330.
In step s310, the mean value and standard deviation of every a line in the first fingerprint image are obtained.
In step s 320, standard deviation normalized is carried out according to the mean value of every a line and standard deviation and obtains third fingerprint
Image.
In the present embodiment, with a wherein standard of behaviour row, obtain other rows standard deviation and reference row standard deviation it
Between ratio；Obtain the difference between every row of the first fingerprint image and corresponding line mean value, and by difference multiplied by ratio to obtain
Third fingerprint image.The reference row can be the first row, be also possible to any a line.
Step S330 carries out mean normalization processing to third fingerprint image.
In the present embodiment, every row of third fingerprint image is added into the mean value of reference row to obtain the second fingerprint image.
In a preferred embodiment, described image processing method further includes in step S400
In rapid S400, gaussian filtering is carried out to the second fingerprint image.
In the present embodiment, due to splicing in the line and in the ranks during splicing, such as burr, disconnected can be generated
It the interference such as splits, needs to be filtered the second fingerprint image.
The embodiment of the invention also discloses a kind of image processing apparatus.Fig. 6, Fig. 7 and Fig. 8 is please referred to be understood.
Fig. 6 shows the structural block diagram of image processing apparatus provided in an embodiment of the present invention.
As shown in fig. 6, in the present embodiment, image processing apparatus includes sequentially connected fingerprint sensor 100, judges mould
Block 200, first processing module 300, Second processing module 400 and filter module 500.
In the present embodiment, fingerprint sensor 100 is for acquiring original fingerprint image, and by original fingerprint collected
Image is sent to judgment module 200.
Preferably, fingerprint sensor 100 obtains original fingerprint image in a manner of progressive scan.
In the present embodiment, judgment module 200 is used to receive the original fingerprint image of the acquisition of fingerprint sensor 100, and right
The original fingerprint image is detected, and judges whether it has common-mode noise.
It is grouped in each traveling every trade for the original fingerprint image that judgment module 200 is used to acquire fingerprint sensor 100；
It obtains with the edge slope being respectively grouped in a line；The brim height for obtaining adjacent two grouping according to the edge slope of each grouping is poor；
It sums all brim height differences to obtain offset distance；When offset distance is greater than preset threshold, the original fingerprint figure is determined
As having common-mode noise.
In the present embodiment, first processing module 300 is used to receive the judging result and original finger that judgment module 200 is sent
Print image, and when original fingerprint image has common-mode noise, splicing in row is carried out to original fingerprint image and obtains first
Fingerprint image.
First processing module 300 mainly every time collected fingerprint image multiple adjacent pixels in, by common mode
The general trend of signal and original signal after noise jamming mutually works at the same time.
In the present embodiment, Second processing module 400 is used to receive the first fingerprint image of the transmission of first processing module 300
Picture, and splicing in the ranks is carried out to the first fingerprint image and obtains the second fingerprint image.
The noise that Second processing module 400 is mainly used between line by line is random, and between each other also without similar oblique
It works when rate relationship.
The second fingerprint image that filter module 500 is then sent for receiving Second processing module 400, and to the second fingerprint image
As carrying out gaussian filtering, filters splicing in the line and in the ranks such as burr of generation, fracture are dry in the process for splicing
It disturbs.
Fig. 7 shows the structural schematic diagram of first processing module in image processing apparatus provided in an embodiment of the present invention.
As shown in fig. 7, in the present embodiment, first processing module 300 includes sequentially connected grouped element 310, edge
Slope unit 320, draw unit 330 and translation unit 340.
In the present embodiment, grouped element 310 is used to receive original fingerprint image, and to every a line of original fingerprint image
Pixel carries out grouping in row.
It is acquired 5 times with a line when the progressive scan of fingerprint sensor 100, for acquiring 8 pixels every time, grouped element 310
Every row of original fingerprint image can be divided into 5 groupings, each grouping includes 8 pixels.
In the present embodiment, edge slope unit 320 is for obtaining with the edge slope being respectively grouped in a line.
For the first row, the edge slope k11 of the first grouping is calculated in the first grouping edge adjacent with second packet
With the edge slope k12 of second packet.And so on, obtain the edge slope being respectively grouped in the first row in original fingerprint image
K11~k1n.
And so on, obtain the edge slope km1~kmn being respectively grouped in the m row in original fingerprint image.
In the present embodiment, draw unit 330 is used for the edge slope according to two grouping adjacent with a line to one of them
The carry out longitudinal stretching of grouping, so that identical with the edge slope of adjacent two grouping of a line.
In the present embodiment, translation unit 340 is used for the brim height difference according to two grouping adjacent with a line to one point
Group translate, so that the brim height difference of adjacent two grouping is zero with a line.
Fig. 8 shows the structural schematic diagram of Second processing module in image processing apparatus provided in an embodiment of the present invention.
As shown in figure 8, Second processing module 400 is returned including sequentially connected acquiring unit 410, first in the present embodiment
One changes unit 420 and the second normalization unit 430.
In the present embodiment, acquiring unit 410 is used to receive the first fingerprint image of the output of first processing module 300, and
Obtain the mean value and standard deviation of every a line pixel in first fingerprint image.
In the present embodiment, the first normalization unit 420 is used to carry out standard deviation according to the mean value and standard deviation of every a line
Normalized obtains third fingerprint image.
Specifically, with a wherein standard of behaviour row, the ratio between the standard deviation of other rows and the standard deviation of reference row is obtained
Value；The difference between every row of the first fingerprint image and corresponding line mean value is obtained, and difference is referred to multiplied by ratio with obtaining third
Print image.The reference row can be the first row, be also possible to any a line.
Preferably, the first row or center row are chosen in the present embodiment as reference row.
In the present embodiment, the second normalization unit 430 is used to carry out mean normalization processing to third fingerprint image.
Specifically, the second naturalization unit 430 is used to every row of third fingerprint image adding the mean value of reference row to obtain
Second fingerprint image.
In embodiments of the present invention, by carrying out noise measuring to the collected fingerprint image of fingerprint sensor institute, and
The interior splicing of row and in the ranks splicing, available more clear finger are carried out to the fingerprint image with common-mode noise
Print image solves fingerprint image fuzzy problem caused by the interference due to common-mode noise, reduces common mode to a certain extent and makes an uproar
Sound (such as charger noise, transformer noise and switching power supply noise) receives image to capacitance type fingerprint sensor-based system and does
It disturbs.
It should be noted that herein, contained the terms "include", "comprise" or its any other variant are intended to
Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that
There is also other identical elements in process, method, article or equipment including the element.
Finally, it should be noted that obviously, the above embodiment is merely an example for clearly illustrating the present invention, and simultaneously
The non-restriction to embodiment.For those of ordinary skill in the art, it can also do on the basis of the above description
Other various forms of variations or variation out.There is no necessity and possibility to exhaust all the enbodiments.And thus drawn
The obvious changes or variations that Shen goes out are still in the protection scope of this invention.
Claims (22)
1. a kind of image processing method characterized by comprising
Judge whether collected original fingerprint image has common-mode noise；
When the original fingerprint image has common-mode noise, splicing in row is carried out to the original fingerprint image and obtains the
One fingerprint image；
Splicing in the ranks is carried out to first fingerprint image and obtains the second fingerprint image.
2. image processing method according to claim 1, which is characterized in that splicing includes: in the row
To being grouped in each traveling every trade of the original fingerprint image；
It obtains with the edge slope being respectively grouped in a line；
Longitudinal stretching is carried out to one of grouping according to the edge slope of adjacent two grouping of same a line；
And one grouping is translated according to the brim height difference of adjacent two grouping of same a line.
3. image processing method according to claim 2, which is characterized in that the longitudinal stretching makes same a line adjacent two
The edge slope of grouping is identical.
4. image processing method according to claim 2, which is characterized in that the translation is so that adjacent two grouping with a line
Brim height difference be zero.
5. image processing method according to claim 1, which is characterized in that the splicing in the ranks includes:
Obtain the mean value and standard deviation of every a line in first fingerprint image；
Standard deviation normalized, which is carried out, according to the mean value of every a line and standard deviation obtains third fingerprint image；
Mean normalization processing is carried out to third fingerprint image.
6. image processing method according to claim 5, which is characterized in that the standard deviation normalized includes:
With a wherein standard of behaviour row, the ratio between the standard deviation of other rows and the standard deviation of reference row is obtained；
Obtain the difference between every row of the first fingerprint image and corresponding line mean value, and by the difference multiplied by the ratio with
To third fingerprint image.
7. image processing method according to claim 6, which is characterized in that the mean normalization, which is handled, includes:
Every row of third fingerprint image is added into the mean value of the reference row to obtain the second fingerprint image.
8. image processing method according to claim 1, which is characterized in that the collected original fingerprint image of judgement
Whether with common-mode noise include:
To being grouped in each traveling every trade of the original fingerprint image；
It obtains with the edge slope being respectively grouped in a line；
The brim height for obtaining adjacent two grouping according to the edge slope of each grouping is poor；
It sums all brim height differences to obtain offset distance；
When the offset distance is greater than preset threshold, the original fingerprint image has common-mode noise.
9. image processing method according to claim 1, which is characterized in that further include:
Gaussian filtering is carried out to the second fingerprint image.
10. image processing method according to claim 1 to 9, which is characterized in that the original fingerprint image
It is obtained in a manner of progressive scan.
11. image processing method according to claim 1 to 9, which is characterized in that the common-mode noise includes
Charger noise, transformer noise and switching power supply noise.
12. a kind of image processing apparatus characterized by comprising
Judgment module, for judging whether collected original fingerprint image has common-mode noise；
First processing module, for being carried out to the original fingerprint image when the original fingerprint image has common-mode noise
Splicing obtains the first fingerprint image in row；
Second processing module obtains the second fingerprint image for carrying out splicing in the ranks to first fingerprint image.
13. image processing apparatus according to claim 12, which is characterized in that first processing module includes:
Grouped element, for being grouped in each traveling every trade to the original fingerprint image；
Edge slope unit, for obtaining with the edge slope being respectively grouped in a line；
Draw unit, the carry out longitudinal stretching for being grouped according to the edge slope of two grouping adjacent with a line to one of them；
And
Translation unit, for according to a line it is adjacent two grouping brim height differences to one be grouped translate.
14. image processing apparatus according to claim 13, which is characterized in that the longitudinal stretching makes same a line adjacent
The edge slope of two groupings is identical.
15. image processing apparatus according to claim 13, which is characterized in that the translation is so that adjacent two points with a line
The brim height difference of group is zero.
16. image processing apparatus according to claim 12, which is characterized in that Second processing module includes:
Acquiring unit, for obtaining the mean value and standard deviation of every a line in first fingerprint image；
First normalization unit refers to for obtaining third according to the mean value and standard deviation of every a line progress standard deviation normalized
Print image；
Second normalization unit, for carrying out mean normalization processing to third fingerprint image.
17. image processing apparatus according to claim 16, which is characterized in that first normalization unit is used for it
In a standard of behaviour row, obtain the ratio between the standard deviation of other rows and the standard deviation of reference row；And obtain the first fingerprint
Difference between the every row and corresponding line mean value of image, and the difference is obtained into third fingerprint image multiplied by the ratio.
18. image processing apparatus according to claim 16, which is characterized in that second normalization unit is used for the
Every row of three fingerprint images adds the mean value of the reference row to obtain the second fingerprint image.
19. image processing apparatus according to claim 12, which is characterized in that the judgment module is used for described original
Grouping in each traveling every trade of fingerprint image；It obtains with the edge slope being respectively grouped in a line；Edge according to each grouping is oblique
The brim height that rate obtains adjacent two grouping is poor；It sums all brim height differences to obtain offset distance；When the offset distance
When from being greater than preset threshold, the original fingerprint image has common-mode noise.
20. image processing apparatus according to claim 12, which is characterized in that further include:
Filter module, for carrying out gaussian filtering to the second fingerprint image.
21. device at image described in any one of 2-20 according to claim 1, which is characterized in that the original fingerprint image
It is obtained in a manner of progressive scan.
22. image processing apparatus described in any one of 2-20 according to claim 1, which is characterized in that the common-mode noise packet
Include charger noise, transformer noise and switching power supply noise.
Priority Applications (1)
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