CN103679666B - Improve the system of sensor image quality - Google Patents
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Abstract
Improve the system of sensor image quality, comprise sensor, statistics with histogram module, threshold point generation module, acquisition target detection module, select module with reference to electric parameter threshold value, described acquisition target detection module limits the higher limit between threshold point, upper limit threshold point, the first Statistical Area, the higher limit between the second Statistical Area to judge whether that acquisition target touches sensor and gathers face for basis; Describedly select module for judge acquisition target type according to lower threshold point with reference to electric parameter threshold value, according to acquisition target type, picture quality is judged, then according to the electric threshold parameter of result of determination selection reference of picture quality. The present invention be by real time from the reference electric parameter threshold value that should adjust sensor, while making acquisition target occur the phenomenon such as partially dry, partially wet, can both collect image more clearly, thereby reduce the complexity of image processing system.
Description
Technical field
The invention belongs to technical field of image processing, be specifically related to oneImprove the system of sensor image quality.
Background technology
The image useful information collecting when existing sensor wets partially for acquisition target or acquisition target is partially dry very little, causesImage intractability increases, and even can cause some application scenario to occur the phenomenon of erroneous judgement.
Existing image quality improvement technology mainly contains carries out self-adaptive processing based on the image being obtained by sensor and regulates imageContrast etc. Carrying out self-adaptive processing based on the image being obtained by sensor regulates picture contrast not solve from data sourceThe image quality issues collecting, but the image collecting is processed (as gray scale stretches, Nogata image by algorithmFigure adjustment etc.). By all or part of half-tone information of the image collecting is carried out to gradation of image stretching or histogram adjustment,Consumption resource is many, and arithmetic speed is slow, improves DeGrain for a fuzzy image processing.
Summary of the invention
For addressing the above problem, the invention provides oneImprove the system of sensor image quality, comprise sensor, histogramStatistical module, threshold point generation module, acquisition target detection module, select module with reference to electric parameter threshold value,
The histogram of each two field picture that described statistics with histogram module collects for real-time statistics sensor;
Described threshold point generation module for obtaining lower threshold point L, limit threshold value in predefined rule according to histogramHigher limit C1, the higher limit C2 between the second Statistical Area between some M, upper limit threshold point H, the first Statistical Area;
Described acquisition target detection module is for basisHigher limit between middle limit threshold point, upper limit threshold point, the first Statistical Area and Higher limit between the second Statistical AreaJudge whether that acquisition target touches sensor and gathers face;
Describedly select module for judging acquisition target type according to lower threshold point, according to acquisition target with reference to electric parameter threshold valueType is judged picture quality, then is selected with reference to electric parameter threshold value according to the result of determination of picture quality;
The real-time sensors configured of the electric threshold parameter of reference that described sensor selects module to select by reference to electric parameter threshold valueGather required electric parameter threshold value.
Described threshold point generation module, the total number in statistics available gray-scale intervalWherein hist (x)For the histogram that gradation of image value is x, G_TH is available gray-scale threshold value; Described G_TH can according to gradation of image scopeAdjust, and G_TH is less than or equal to gradation of image scope;
OrderI is the gray value that current histogram is corresponding, 0≤i≤K, and described K is gradation of imageMaximum;
To make gray value be n1 to the statistics number in n2 segmentWherein n1 and n2 are figureAny set point value within the scope of picture gray value.
Described predefined rule is:
Work as yi-1≤ VH × LR and yiWhen > VH × LR, the value of i is exactly histogram lower threshold point L,
If when L > G_TH, L=G_TH;
Work as yi-1≤ VH × MR and yiWhen > VH × MR, the value of i is exactly in histogram, to limit threshold point M,
If when M > G_TH, M=G_TH;
Work as yi-1≤ VH × HR and yiWhen > VH × HR, the value of i is exactly histogram upper limit threshold point H,
If when H > G_TH, H=G_TH;
Described LR is the proportionality coefficient of asking for lower threshold point, and described MR is the proportionality coefficient of asking for middle limit threshold point, described inHR is the proportionality coefficient of asking for upper limit threshold point, and 0 < LR < 1,0 < MR < 1,0 < HR < 1,LR＜MR＜HR；
Work as yi-1≤ SUM1 and yiWhen > SUM1, i value is now exactly higher limit C1 between the first Statistical Area, if i=K andyiWhen≤SUM1, C1=K;
Work as yi-1≤ SUM2 and yiWhen > SUM2, i value is now exactly higher limit C2 between the second Statistical Area, if i=KAnd yiWhen≤SUM2, C2=K;
Between described the first Statistical Area for gray value is 0 to a segment of gray value C1, between the second Statistical Area for gray value isA segment of 0 to gray value C2; SUM1 is threshold value between the first Statistical Area, and SUM2 is threshold value between the second Statistical Area,And SUM1 > SUM2.
Described acquisition target detection module detect whether have acquisition target touch sensor gather face according to being:
If middle limit threshold point is more than or equal to higher limit between the first Statistical Area, represent to detect that acquisition target touches sensor and adoptsCollection face;
If upper limit threshold point is less thanHigher limit between the second Statistical AreaTime, represent to detect that acquisition target leaves;
Gather face if do not have acquisition target to touch sensor, without carrying out reference voltage adjustment judgement.
The type of described acquisition target comprise acquisition target for wetting, acquisition target is for dry and acquisition target is normal, its decision method is:
If L < is G1, represent that the acquisition target of present image is for wet;
If L > is G2, represent that the acquisition target of present image is for dry;
If G1 < L < is G2, represent that the acquisition target of present image is normal;
Wherein G1, G2 is adjustable gray scale fiducial value, and G1 < G2.
When described acquisition target is wet, if upper limit threshold point is less than first threshold with the difference HL_DIF of lower threshold point, tableShow and need to carry out with reference to the adjustment of electric parameter threshold value sensor, its method of adjustment is:
If 0≤HL_DIF < HL (1), selects with reference to electric parameter threshold value Z (1);
If HL (q1-1)≤HL_DIF < HL (q1), selects with reference to electric parameter threshold value Z (q1);
The first order reference value that wherein HL (1) is HL_DIF, the q1 level reference value that HL (q1) is HL_DIF,Z (1) be the 1st selectable with reference to electric parameter threshold value, Z (q1) is that q1 is selectable with reference to electric parameter threshold value;1 < q1≤m, 1 < m < num and HL (1) < HL (2) < ... < HL (m);
Described first threshold is empirical value; Described num is with reference to the selectable total number of electric parameter threshold value。
When acquisition target is when dry, if hist_sum is less than Second Threshold, expression need to be carried out with reference to electric parameter sensorThreshold value is adjusted, and its method of adjustment is:
If sum (q2+1)≤hist_sum < sum (q2), selects Z (m+q2);
If 0≤hist_sum < sum (num-m), selects Z (num);
The q2 level reference value that wherein sum (q2) is hist_sum; 1≤q2 < num-m,Sum (num-m) is The num-m level reference value of hist_sum, 1 < m < num;
And sum (1) > sum (2) > ... > sum (num-m);
Described num is with reference to the selectable total number of electric parameter threshold value, and
Z(1)<Z(2)<Z(3)<……<Z(num-1)<Z(num)；
Described Second Threshold is empirical value.
The present invention is the reference electric parameter threshold value by certainly adjusting in real time sensor, acquisition target is occurred partially dry, partially wetWhen the phenomenon, can both collect image more clearly, thereby reduce the complexity of image processing system. The present invention is based on streamWaterline framework real-time adaptive is adjusted the reference electric parameter threshold value of sensor, and its implementation is simple, fast operation, power consumptionLittle, cost is low.
Brief description of the drawings
Fig. 1 is sensor output electrical signals value and the schematic diagram with reference to electric threshold value;
Fig. 2 is image and the corresponding histogram distribution figure thereof that wet finger collects on sensor;
Fig. 3 is image and the corresponding histogram distribution figure thereof that dry finger collects on sensor;
Fig. 4 is image and the corresponding histogram distribution figure thereof that normal finger collects on sensor;
Fig. 5 is with reference to electric parameter threshold value adjustment System block diagram;
Fig. 6 is that dry finger is not adjusted and self adaptation adjustment gathers the comparison diagram of image after with reference to electric parameter threshold value;
Fig. 7 is that wet finger is not adjusted and self adaptation adjustment gathers the comparison diagram of image after with reference to electric parameter threshold value.
Detailed description of the invention
The preferred embodiments of the present invention are described with reference to the accompanying drawings, and specific embodiment described herein is only in order to explain thisBright, be not intended to limit the present invention.
Capacitance type sensor converts measured signal to the signal of telecommunication, and by the fixed cycle sampling signal of telecommunication, by what sampleValue of electrical signals is sent to comparator, and comparator converts the electrical signal to easy-to-handle data signal. Sensor is by measured signalConvert the curve map of the signal of telecommunication to as Fig. 1 a.
The signal of telecommunication curve map that curve in Fig. 1 b 1 produces during than compared with normal for acquisition target, curve 2 is that acquisition target is partially dryTime the signal of telecommunication curve map that produces, curve 3 be the signal of telecommunication curve map of acquisition target generation when partially wet. In the time that acquisition target is normal,The reference electric parameter threshold value arranging is with reference to electric parameter threshold value one, now occurs upset, this point at acquisition time nTGray value is n; In the time that acquisition target is partially dry, arranging with reference to electric parameter threshold value is with reference to electric parameter threshold value two, is now adoptingThere is upset in collection time point nT, the gray value of this point is n; In the time that acquisition target is partially wet, arranges with reference to electric parameter threshold value and beWith reference to electric parameter threshold value three, now there is upset at acquisition time nT, the gray value of this point is n. Hence one can see that, logicalCross that to adjust the difference of sensor suitable for electric parameter (example: voltage, electric current etc.) threshold value, make acquisition target partially dry, inclined to one sideThe grey value profile that the gray value collecting when wet and acquisition target collect when normal is at same interval range.
From Fig. 1 b, different acquisition targets produces different signal of telecommunication curves, and its curve map is nonlinear. Work as sensingWhen reference electric parameter (example: voltage, the electric current etc.) threshold value of device is fixing, acquisition target is partially dry, acquisition target is partially wet etc. relativelyIn normal acquisition target, the fuzzyyer or useful half-tone information of the image ratio that collects very little. The present invention is by adjusting and pass in real timeReference electric parameter (example: voltage, the electric current etc.) threshold value of sensor, makes, acquisition target partially dry for acquisition target partially wet etc.Can both collect image more clearly.
According to above-mentioned principle, by the non-background half-tone information of image backstepping acquisition target type, adjust in real time the reference electricity of sensorGas parameter threshold, makes that acquisition target is partially dry, acquisition target can both collect image more clearly when partially wet.
Due to the dielectric constant of different acquisition object with to the difference of the distance of sensor surface etc., cause the image effect collectingThere is notable difference. Below the partially wet and three kinds of situations of more normal acquisition target of, acquisition target partially dry to acquisition target are entered respectivelyGo analysis:
(1), in the time that acquisition target is partially wet, its dielectric constant is larger than the dielectric constant of air, causes its capacitor discharge speed fast,The non-background value of image gathering is on the low side, and non-background information mainly distributes near the gray value region that is 0. In the present embodiment, wetThe image that collects on capacitance type sensor of finger and histogram distribution thereof as shown in Figure 2, the non-background of image that Real-time Collection arrivesInformation is very many, adds up the upper limit threshold point obtaining, middle limit threshold point, lower threshold point all very little according to histogram distribution, and3 threshold point are distributed in very little interval range.
(2), in the time that acquisition target is partially dry, its dielectric constant is more smaller than dielectric constant of air, causes its capacitor discharge speed slow,The non-background gray levels of image gathering is higher, and main distribution near the region of image background value. In the present embodiment, dry finger existsThe image collecting on capacitive fingerprint sensing device and histogram distribution thereof as shown in Figure 3, the figure that partially dry acquisition target collectsPicture half-tone information on the low side, major part is image background value, according to histogram distribution add up the lower threshold point obtaining bigger than normal, add upGray value is that n1 is also fewer to the pixel number between n2.
(3), when acquisition target is during than compared with normal, its dielectric constant between acquisition target partially dry and acquisition target partially wet between, itsCapacitor discharge speed is moderate, and the non-background information of image collecting is evenly distributed, and its non-background information is also abundant. The present embodimentIn, the image that normal finger collects on capacitance type sensor and corresponding histogram distribution thereof show as Fig. 4, acquisition target is justChang Shi, the image collecting is very clear, adds up the upper limit threshold point obtaining, middle limit threshold point, lower limit according to histogram distributionThreshold point is distributed in a very large interval, and gray value n1 is abundant to the total number of pixel of gray value n2 segment.
As shown in Figure 5, in order to make some special acquisition target can both collect image more clearly, the invention providesA kind ofImprove the system of sensor image quality, comprise sensor, statistics with histogram module, threshold point generation module, gather rightResemble detection module, select module with reference to electric parameter threshold value.
The histogram of each two field picture that statistics with histogram module collects for real-time statistics sensor;
Threshold point generation module for obtaining lower threshold point L, limit threshold point in predefined rule according to histogramHigher limit C2 between higher limit C1, the second Statistical Area between M, upper limit threshold point H, the first Statistical Area;
Acquisition target detection module basisHigher limit between middle limit threshold point, upper limit threshold point, the first Statistical Area and the second statistics Interval higher limitJudge whether that acquisition target touches sensor and gathers face;
Select module for judging acquisition target type according to lower threshold point, according to acquisition target type with reference to electric parameter threshold valuePicture quality is judged, then selected with reference to electric parameter threshold value according to the result of determination of picture quality; When acquisition target is for wetTime, select different reference electric parameter threshold values according to the difference of upper limit threshold point and lower threshold point, when acquisition target is when dry,Be that n1 selects different reference electric parameter threshold values to the statistics number of n2 according to gray value;
Sensor is that the real-time sensors configured of reference electric parameter threshold value of selecting by reference to electric parameter threshold value adjusting module is adoptedThereby collecting required electric parameter threshold value changes it and gathers the quality of image.
Statistics with histogram module statistic histogram, the formula of histogram real-time statistics is as follows:
The vertical coordinate that wherein u is image, the horizontal coordinate that v is image, h is picture altitude, and w is picture traverse, and x isThe gray value of image, img (u, v) is positioned at the gray value of (u, v) for image pixel point coordinates.
Total number in threshold point generation module statistics available gray-scale interval Wherein hist (x) is gray scaleValue is the histogram of x, and G_TH is available gray-scale threshold value; Described G_TH is according to gradation of image scope capable of regulating, andG_TH is less than or equal to gradation of image scope.
OrderI is the gray value that current histogram is corresponding, 0≤i≤K, and described K is gradation of imageMaximum.
Make the statistics number of gray value n1 to gray value n2 segmentWherein n1 and n2 areAny set point value within the scope of gradation of image value.
According to the higher limit between histogram calculation lower threshold point L, middle limit threshold point M, upper limit threshold point H, the first Statistical AreaHigher limit C2 between C1, the second Statistical Area, its decision rule is:
Work as yi-1≤ VH × LR and yiWhen > VH × LR, the value of i is exactly histogram lower threshold point L,
If when L > G_TH, L=G_TH;
Work as yi-1≤ VH × MR and yiWhen > VH × MR, the value of i is exactly in histogram, to limit threshold point M,
If when M > G_TH, M=G_TH;
Work as yi-1≤ VH × HR and yiWhen > VH × HR, the value of i is exactly histogram upper limit threshold point H,
If when H > G_TH, H=G_TH;
Described LR is the proportionality coefficient of asking for lower threshold point, and described MR is the proportionality coefficient of asking for middle limit threshold point, described inHR is the proportionality coefficient of asking for upper limit threshold point, and 0 < LR < 1,0 < MR < 1,0 < HR < 1,LR＜MR＜HR；
Work as yi-1≤ SUM1 and yiWhen > SUM1, i value is now exactly higher limit C1 between the first Statistical Area,
If i=K and yiWhen≤SUM1, C1=K;
Work as yi-1≤ SUM2 and yiWhen > SUM2, i value is now exactly higher limit C2 between the second Statistical Area,
If i=K and yiWhen≤SUM2, C2=K;
Between described the first Statistical Area for gray value is 0 to a segment of gray value C1, between the second Statistical Area for gray value isA segment of 0 to gray value C2; SUM1 is threshold value between the first Statistical Area, and SUM2 is threshold value between the second Statistical Area,And SUM1 > SUM2.
Acquisition target detection module basisHigher limit between middle limit threshold point, upper limit threshold point, the first Statistical Area and the second statistics Interval higher limitJudged whether that acquisition target touches sensor and gathers face, it detects according to being:
By limitting the statistics number below threshold point whether abundant in judgement,
If middle limit threshold point is more than or equal to higher limit between the first Statistical Area, in expression, limit number below threshold point to be greater than or etc.Threshold value between the first Statistical Area, represents to detect that acquisition target touches sensor and gathers face; When upper limit threshold point is less thanThe second system Count interval higher limitTime, represent that the following number of upper limit threshold point is insufficient, represent to detect that acquisition target leaves.
Gather face if do not have acquisition target to touch sensor, without carrying out reference voltage adjustment judgement, directly enter histogramStatistical module is added up the histogram of next frame image, judges whether next frame image needs to adjust reference voltage; Otherwise enterEntering with reference to electric parameter threshold value selects module to selecting with reference to electric parameter threshold value.
Select module according to lower threshold point backstepping acquisition target type with reference to electric parameter threshold value, the type of acquisition target comprises adoptsSet pair resembles as wet, acquisition target is for dry and acquisition target is normal, and its decision method is:
If L < is G1, represent that the non-background information of image of current collection is mainly distributed in the interval range below G1, current figureThe acquisition target of picture is for wet;
If L > is G2, represent that the non-background information of image of current collection is mainly distributed in interval range more than G2, current figureThe acquisition target of picture is for dry;
If G1 < L < is G2, represent that the non-background information of image of current collection is mainly distributed in G1 to the interval range between G2In, the acquisition target of present image is normal;
Wherein G1, G2 is adjustable gray scale fiducial value, and G1 < G2.
According to different acquisition target types, select the decision method of different picture quality, its selection rule is:
A) when acquisition target is when wet, the non-background information of image collecting is very many, by judging upper limit threshold point and lower limitThe distribute spacing of threshold point, judges whether the non-background information of image is distributed in larger interval range, if upper limit threshold pointBe less than first threshold with the difference of lower threshold point, described first threshold is empirical value, represents the non-background ash of image of current collectionDegree information is distributed in a very little interval range, and an ambiguous phenomenon appears in image. Upper limit threshold point and lower limit thresholdThe spacing of value point is less, represents that current picture quality is poorer, need to carry out with reference to the adjustment of electric parameter threshold value sensor.
B) when acquisition target is when dry, the non-background information of image collecting is considerably less, by judging that gray value is that n1 is to n2'sStatistics number, judges that whether the non-background information of image is many, is less than the second threshold if gray value is n1 to the statistics number of n2Value, described Second Threshold is empirical value, represents that the non-background half-tone information of image of current collection is fewer. If statistics number moreFew, represent that the quality of the current image collecting is poorer, need to carry out with reference to the adjustment of electric parameter threshold value sensor.
Select different reference electric parameter threshold values according to picture quality, its selection rule is:
When acquisition target is when wet: if image occur one smudgy, key diagram is distributed in one very as non-background informationIn little interval range, the upper limit threshold point obtaining according to histogram distribution is very little with the interval of lower threshold point, i.e. basisUpper limit threshold point is selected different reference electric parameter threshold values from the difference of lower threshold point.
If 0≤HL_DIF < HL (1), selects with reference to electric parameter threshold value Z (1);
If HL (1)≤HL_DIF < HL (2), selects with reference to electric parameter threshold value Z (2);
In like manner,
If HL (m-1)≤HL_DIF < HL (m), selects with reference to electric parameter threshold value Z (m);
Wherein HL_DIF is the difference of upper limit threshold point and lower threshold point, i.e. HL_DIF=H-L,1＜m＜num。
The first order reference value that HL (1) is HL_DIF;
The second level reference value that HL (2) is HL_DIF;
In like manner,
The m level reference value that HL (m) is HL_DIF; And HL (1) < HL (2) < ... < HL (m).
Num is with reference to the selectable total number of electric parameter threshold value;
Z (1) is that first is selectable with reference to electric parameter threshold value;
Z (2) be second selectable with reference to electric parameter threshold value;
In like manner,
Z (num) is that num is individual selectable with reference to electric parameter threshold value;
And Z (1) < Z (2) < Z (3) < ... < Z (num-1) < Z (num).
When acquisition target is when dry: the non-background information of image collecting is fewer, is mainly image background value, according to statistics ashDegree value be n1 to the total number hist_sum of the pixel between n2, judge the degree that acquisition target is partially dry, thereby select differentReference electric parameter threshold value.
If sum (2)≤hist_sum < sum (1), selects Z (m+1);
If sum (3)≤hist_sum < sum (2), selects Z (m+2);
In like manner,
If sum (num-m)≤hist_sum < sum (num-m-1), selects Z (num-1);
If 0≤hist_sum < sum (num-m), selects Z (num)
The first order reference value that wherein sum (1) is hist_sum;
The second level reference value that sum (2) is hist_sum;
In like manner,
The num-m level reference value that sum (num-m) is hist_sum;
And sum (1) > sum (2) > ... > sum (num-m).
Same acquisition target is to be Z (1) with reference to electric parameter threshold value gather when being Z (num) with reference to electric parameter threshold valueTo the non-background information of image successively increase progressively, same acquisition target collects in the time being Z (2) with reference to electric parameter threshold valueThe non-background information of image more than the non-background information of image collecting in the time being Z (1) with reference to electric parameter threshold value.
Sensor adjusts according to the reference electric parameter threshold value of selecting the reference electric parameter threshold value that next frame gathers.
Referring to Fig. 6, Fig. 7, the present embodiment provides, and dry, wet finger is adjusted by real-time adaptive on capacitive fingerprint sensing deviceThe image of whole sensor reference electric parameter threshold acquisition and the image of not adjusting sensor reference electric parameter threshold acquisition. Fig. 6The image that Zuo Weigan finger gathers while not adjusting with reference to electric parameter threshold value, right is that dry finger real-time adaptive is adjusted with reference to electric ginsengThe fingerprint image gathering after number threshold value; Fig. 7 is the image that wets and gather when finger is not adjusted with reference to electric parameter threshold value, and right is wet handRefer to the fingerprint image gathering after real-time adaptive adjustment is with reference to electric parameter threshold value. As can be seen from the figure the present invention is by certainly real-timeAdapt to adjust the reference electric parameter threshold value of sensor, while making acquisition target occur partially dry, partially wet, dirty, wet goods phenomenon, allCan collect image more clearly, thereby reduce the complexity of image processing system.
Those skilled in the art is not departing under the condition of the definite the spirit and scope of the present invention of claims, can also be rightAbove content is carried out various amendments. Therefore scope of the present invention is not limited in above explanation, but by claimThe scope of book is determined.
Claims (6)
1.Improve the system of sensor image quality, it is characterized in that, comprise sensor, statistics with histogram module, threshold pointGeneration module, acquisition target detection module, select module with reference to electric parameter threshold value,
The histogram of each two field picture that described statistics with histogram module collects for real-time statistics sensor;
Described threshold point generation module for obtaining lower threshold point L, limit threshold value in predefined rule according to histogramHigher limit C1, the higher limit C2 between the second Statistical Area between some M, upper limit threshold point H, the first Statistical Area;
Described acquisition target detection module is for basisHigher limit between middle limit threshold point, upper limit threshold point, the first Statistical Area, Higher limit between the second Statistical AreaJudge whether that acquisition target touches sensor and gathers face;
Describedly select module for judging acquisition target type according to lower threshold point, according to acquisition target with reference to electric parameter threshold valueType is judged picture quality, then is selected with reference to electric parameter threshold value according to the result of determination of picture quality;
The real-time sensors configured of reference electric parameter threshold value that described sensor selects module to select by reference to electric parameter threshold valueGather required electric parameter threshold value.
2. according to claim 1Improve the system of sensor image quality, it is characterized in that, described predefinedRule is:
Work as yi-1≤ VH × LR and yiWhen > VH × LR, the value of i is exactly histogram lower threshold point L,
If when L > G_TH, L=G_TH;
Work as yi-1≤ VH × MR and yiWhen > VH × MR, the value of i is exactly in histogram, to limit threshold point M,
If when M > G_TH, M=G_TH;
Work as yi-1≤ VH × HR and yiWhen > VH × HR, the value of i is exactly histogram upper limit threshold point H,
If when H > G_TH, H=G_TH;
Described LR is the proportionality coefficient of asking for lower threshold point, and described MR is the proportionality coefficient of asking for middle limit threshold point, described inHR is the proportionality coefficient of asking for upper limit threshold point, and 0 < LR < 1,0 < MR < 1,0 < HR < 1,LR＜MR＜HR；
Work as yi-1≤ SUM1 and yiWhen > SUM1, i value is now exactly higher limit C1 between the first Statistical Area, if i=K andyiWhen≤SUM1, C1=K;
Work as yi-1≤ SUM2 and yiWhen > SUM2, i value is now exactly higher limit C2 between the second Statistical Area, if i=KAnd yiWhen≤SUM2, C2=K;
Between described the first Statistical Area for gray value is 0 to a segment of gray value C1, between the second Statistical Area for gray value isA segment of 0 to gray value C2; SUM1 is threshold value between the first Statistical Area, and SUM2 is threshold value between the second Statistical Area,And SUM1 > SUM2;
Described threshold point generation module, the total number in statistics available gray-scale interval
Wherein hist (x)
For the histogram that gradation of image value is x, G_TH is available gray-scale threshold value; Described G_TH can according to gradation of image scope
Adjust, and G_TH is less than or equal to gradation of image scope;
Order I is the gray value that current histogram is corresponding, 0≤i≤K, described K be gradation of image Large value。
3. according to claim 1Improve the system of sensor image quality, it is characterized in that described acquisition target inspectionSurvey module detect whether have acquisition target touch sensor gather face according to being:
If middle limit threshold point is more than or equal to higher limit between the first Statistical Area, represent to detect that acquisition target touches sensor and adoptsCollection face;
If upper limit threshold point is less thanHigher limit between the second Statistical AreaTime, represent to detect that acquisition target leaves;
Gather face if do not have acquisition target to touch sensor, without carrying out reference voltage adjustment judgement.
4. according to claim 1Improve the system of sensor image quality, it is characterized in that, described acquisition targetType comprise acquisition target for wetting, acquisition target is for dry and acquisition target is normal, its decision method is:
If L < is G1, represent that the acquisition target of present image is for wet;
If L > is G2, represent that the acquisition target of present image is for dry;
If G1 < L < is G2, represent that the acquisition target of present image is normal;
Wherein G1, G2 is adjustable gray scale fiducial value, and G1 < G2.
5. according to claim4DescribedImprove the system of sensor image quality, it is characterized in that,
When described acquisition target is wet, if upper limit threshold point is less than first threshold with the difference HL_DIF of lower threshold point, tableShow and need to carry out with reference to the adjustment of electric parameter threshold value sensor, its method of adjustment is:
If 0≤HL_DIF < HL (1), selects with reference to electric parameter threshold value Z (1);
If HL (q1-1)≤HL_DIF < HL (q1), selects with reference to electric parameter threshold value Z (q1);
The first order reference value that wherein HL (1) is HL_DIF, the q1 level reference value that HL (q1) is HL_DIF,Z (1) be the 1st selectable with reference to electric parameter threshold value, Z (q1) is that q1 is selectable with reference to electric parameter threshold value;1 < q1≤m, 1 < m < num and HL (1) < HL (2) < ... < HL (m);
Described first threshold is empirical value; Described num is with reference to the selectable total number of electric parameter threshold value.
6. according to claim4DescribedImprove the system of sensor image quality, it is characterized in that,
When acquisition target is when dry, if hist_sum is less than Second Threshold, expression need to be carried out with reference to electric parameter sensorThreshold value is adjusted, and its method of adjustment is:
If sum (q2+1)≤hist_sum < sum (q2), selects Z (m+q2);
If 0≤hist_sum < sum (num-m), selects Z (num);
To make gray value be n1 to the statistics number in n2 segment Wherein n1 and n2 are figure Any set point value within the scope of picture gray value;The q2 level reference value that wherein sum (q2) is hist_sum;1≤q2＜num-m,The num-m level reference value that sum (num-m) is hist_sum, 1 < m < num;And sum (1) > sum (2) > ... > sum (num-m);
Described num is with reference to the selectable total number of electric parameter threshold value, and
Z(1)<Z(2)<Z(3)<……<Z(num-1)<Z(num)；
Described Second Threshold is empirical value.
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| "Adaptive fingerprint image enhancement with fingerprint image quality analysis";Eun-Kyung Yun,Sung-Bae Cho;《Image and Vision Computing》;20060101;第24卷(第1期);101-110 * |
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