CN1889092A - Scan fingerprint image reconfiguration method based on movement estimation - Google Patents
Scan fingerprint image reconfiguration method based on movement estimation Download PDFInfo
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Abstract
The invention relates to reconfiguration method of the scan fingerprint figure based on the sports estimation. It includes the process: dividing the start and the stop position when the location finger is scanned through the sensor; storing and updating the scanning figure continuously; predicting the sports vector of the figure in the condition of the sliding finger moves in the uniform speed or the uniform acceleration speed; according to the vector to select the reference macromodule dynamically and predict the best matching module to get the sports vector; adjusting the domain of the searching matching module using the difference of the sports vector and the predicting vector as the feedback quantity; changing the sports vector of the continuous frame figure to splice the fingerprint figure.
Description
Technical field
The present invention relates to Flame Image Process and matching technique field, the particularly motion compensated prediction technology of video coding adopts the method for the variable-block coupling multiframe estimation of sub-pixel precision, realizes the image reconstruction of sweep fingerprint sensor.
Background technology
Because the uniqueness and the stability of fingerprint characteristic, fingerprint identification technology just is applied in the criminal investigation field very early, and has obtained great success.The demand of various in recent years fields authentication constantly increases, and along with public ground progressively accepting and approve that Automated Fingerprint Identification System (AFIS) technology will obtain using more widely in the commercial market.Automatically the application of fingerprint identification technology and popularization are again closely-related with the development of fingerprint sensor technology.Traditional fingerprint sensor generally by will point near or detect fingerprint on the sensor by being pressed in, so the size of sensor generally wants big with respect to fingerprint.In order to satisfy compact conformation, demand that volume is littler, a kind of microsensor that detects fingerprint by the finger that slides at sensor surface just arises at the historic moment.Sweep fingerprint sensor is as traditional sensor " miniature " version, lateral dimension constant (300 or 256 pixel) is vertically only got 2～32 row, utilizes the inswept sensor of whole finger to form continuous images, use the software rebuild fingerprint image again.This sensor bulk is little, low in energy consumption, low price and tolerance sweat stain influence, is suitable for being applied in occasions such as mobile phone, smart phone, PDA or movable storage device.But the fingerprint image of present existing software reconfiguration exists in various degree distortion and distortion, has influenced the precision of follow-up recognizer, is therefore limiting sweep fingerprint sensor and is further applying.
Summary of the invention
The present invention adopts the method for the variable-block coupling multiframe estimation of sub-pixel precision, calculates the motion vector of continuous sweep image in real time, exactly, and conversion obtains relative displacement discrete between the different frames, rebuilds fingerprint image.
Scan fingerprint image reconfiguration method based on estimation comprises step: buffer memory also upgrades the image of continuous sweep in real time; The motion vector of predicted picture, dynamically choose reference macroblock, determine the frame and the position thereof at prediction match block place, the two field picture at prediction match block place is made interpolation, in the neighborhood of prediction match block, search for best matching blocks, obtain the motion vector of the estimation of sub-pixel precision; Self-adaptation is adjusted motion search range; The motion vector of conversion sequential frame image, the splicing fingerprint image.
Also comprise step: the image of buffer memory continuous sweep, and upgrade in real time, this mode is removed in real time and has been finished spliced image, only preserves the motion vector of respective frame and the fingerprint image of reconstruction, alleviated the pressure of storage effectively, and requirement of real time.
Also comprise step: supposition is in subrange, and the finger of slip is with at the uniform velocity or uniformly accelerated motion, the motion vector of predicted picture.
Also comprise step: according to the numerical value of predicted motion vector, dynamically choose reference macroblock, this method of choosing macro block can obtain the motion vector of fractional form more accurately.
Also comprise step: the picture element interpolation of the estimation of sub-pixel precision, this method can obtain the motion vector of half-pix or 1/4 pixel precision.
Also comprise step: with the difference of motion vector and predicted vector as feedback quantity, self-adaptation is adjusted the scope of search matched piece, the advantage of this method is, when the velocity variations of pointing slip is big, can either guarantee to search apace best matching blocks, can avoid search to be absorbed in the local optimum point again.Also comprise step: the motion vector of conversion sequential frame image, obtain relative displacement discrete between the different frames, the splicing fingerprint image, this method has made full use of the limited vertical resolution of scan image, has solved effectively to be difficult to the problem that is offset about the accurate description scan image because of motion vector horizontal component is less.
Description of drawings
Fig. 1 is based on the implementation procedure figure of the scan fingerprint image reconfiguration method of estimation.
Fig. 2 is a variable-block coupling multiframe estimation synoptic diagram.
Fig. 3 is the motion vector calculation process flow diagram.
Fig. 4 is scan fingerprint image reconfiguration result 1 figure.
Fig. 5 is scan fingerprint image reconfiguration result 2 figure.
Embodiment
The implementation procedure of this scan fingerprint image reconfiguration method based on estimation as shown in Figure 1, concrete steps are as follows:
(1-1) cut apart the reference position that inswept sensor is pointed in the location, method is the contrast histogram of statistics continuous sweep image, and the iteration selected threshold is judged background or fingerprint image with this, the reference position of ancillary hardware detection and location scan fingerprint image;
(1-2) image of buffer memory continuous sweep.With 8 line sensors is example, the image of buffer memory 10 frame continuous sweeps, and upgrade in real time;
(1-3) motion vector of the consecutive image of calculating buffer memory;
(1-4) splicing fingerprint image.Make full use of the limited vertical resolution of scan image, the motion vector of conversion sequential frame image obtains relative displacement discrete between the different frames, splices corresponding frame according to displacement relation, rebuilds fingerprint image.With 8 line sensors is example, and table 1 is depicted as the result of motion vector vertical component conversion, and the horizontal component of corresponding frame superposes, and can obtain the transformation result of horizontal component.In fact,, can set the sample frequency of scan image, make the vertical component of motion vector exist according to the sliding speed of common people's finger
Between, promptly the sliding speed difference of user's finger is 12 times, can satisfy the needs of most application scenarios.The present invention exists to the maximum scope of application of 8 line sensors
Between, can tolerate that promptly maximum differential is 63 times a velocity range.
(1-5) upgrade buffer memory and judge also whether finger scanning stops.Remove and finished spliced image, upgrade buffer memory, the method that adopts same step (1) dynamic threshold to cut apart, and in conjunction with the motion vector judgement, stop to slide as finger, then restructuring procedure finishes, otherwise changes step (2).
The variable-block coupling multiframe estimation of Fig. 2, utilize two width of cloth scan images to illustrate---the frame at present frame and prediction match block place, the estimation of sub-pixel precision need be carried out picture element interpolation to the frame at prediction match block place, reference macroblock is dynamically chosen at present frame, the scope of search best matching blocks is chosen at the neighborhood of prediction match block on the pixel battle array that interpolation obtains, in the motion vector calculation step below, will describe the process of this estimation in detail.
Motion vector calculation:
Suppose that all pixels in every two field picture do same motion, then the motion vector of present frame can be represented with the motion vector of image macro.
Fig. 3 is the motion vector calculation flow process.The specific implementation step is as follows:
(3-1) calculate initial motion vector.Choose the sub-piece of M * N pixel at the present frame of image, as the reference macroblock that initial motion is estimated, the resolution of establishing sensor is C * L, then can get M=C-2P, N=1～L-1, wherein P=8～16.Adopt full-search algorithm (FSA), search the macro block that mates most with reference macroblock at previous frame, the criterion of piece coupling is absolute average error criterion (MAE), promptly seeks the image macro of gray scale absolute average error minimum.The displacement on two dimensional surface of reference macroblock and match block is initial motion vector.If the vertical component of predicted motion vector is less than or equal to 1, then choose reference macroblock again, every the frame search match block, the displacement on two dimensional surface of reference macroblock and match block promptly obtains initial motion vector divided by frame number at interval.
(3-2) predicted motion vector.Suppose that in subrange the finger of slip is with at the uniform velocity or uniformly accelerated motion.With 8 line sensors is example, and in the subrange of 1～18 frame, if be assumed to uniform motion, then predicted motion vector is the weighted mean value of motion vector in the local before present frame; If be assumed to uniformly accelerated motion, the forward direction difference of motion vector in the weighted mean local at first then, result again with present frame before the average summation of motion vector of 1～6 frame, obtain predicted motion vector.Because in the step below, adopt the mechanism of dynamically choosing macro block and search feedback, these two kinds of supposition are equivalent, experimental result has also proved the validity of these two kinds of supposition.If present frame is the frame of initial 3 buffer memorys, then predicted motion vector is chosen initial motion vector.
(3-3) dynamically choose reference macroblock.Owing to adopt the method for sub-pixel precision and multiframe estimation, can choose suitable variable reference macro block according to the numerical value of predicted motion vector.
(3-4) according to definite frame and the position thereof of predicting the match block place of the size of predicted motion vector and reference macroblock.
(3-5) two field picture at prediction match block place is made the picture element interpolation of the estimation of sub-pixel precision.Adopt bilinear interpolation, obtain half-pix or
The point of location of pixels, form with
Pixel or
Pixel is the pixel battle array of spacing.
(3-6) calculation of motion vectors.Adopt the absolute average error criterion, on the pixel battle array that interpolation obtains, search for best matching blocks in the neighborhood of prediction match block.The displacement on two dimensional surface of reference macroblock and best matching blocks is the motion vector of the multiframe estimation of sub-pixel precision.For the match block every frame search, motion vector needs divided by frame number at interval.
(3-7) self-adaptation is adjusted motion search range.As feedback quantity, adjust the scope of motion estimation search best matching blocks with the difference of motion vector and predicted vector adaptively.
The scan fingerprint image reconfiguration result 1 of Fig. 4, the average motion vector vertical component is 1.49 pixel/frame, the sample frequency of the scan image of setting according to us, these data approach common people's finger sliding speed, horizontal component is 0.02 pixel/frame, skew is less about expression, and diagram left side is original continuous sweep image and partial enlarged drawing thereof, and the right side is the result who utilizes our method reconstruct fingerprint image.
The scan fingerprint image reconfiguration result 2 of Fig. 5, the average motion vector vertical component is 2.02 pixel/frame, finger sliding speed with respect to common people is very fast, horizontal component is 0.35 pixel/frame, skew is bigger about showing, the diagram left side is original continuous sweep image and partial enlarged drawing thereof, and the right side is the result who utilizes our method reconstruct fingerprint image.
By the image reconstruction result of Fig. 4 and Fig. 5 as can be seen, it is bigger that the present invention adapts to the scope of pointing scan variations, and reconstruct fingerprint image effective has very strong practicality.
| Motion vector vertical component Vver (pixel) | Transformation results | |
| Vertically opposite displacement (pixel) | Frame at interval | |
| 2.25＜Vver≤2.75 | 5 | 2 |
| 1.75＜Vver≤2.25 | 4 | 2 |
| 1.425＜Vver≤1.75 | 3 | 2 |
| 1.29＜Vver≤1.425 | 4 | 3 |
| 1.125＜Vver≤1.29 | 5 | 4 |
| 0.875≤Vver≤1.125 | 4 | 4 |
| 0.708＜Vver＜0.875 | 3 | 4 |
| 0.583＜Vver≤0.708 | 2 | 3 |
| 0.45≤Vver≤0.583 | 2 | 4 |
| 0.366＜Vver＜0.45 | 2 | 5 |
| 0.31≤Vver≤0.366 | 1 | 3 |
| 0.268≤Vver＜0.31 | 2 | 7 |
| 0.236≤Vver＜0.268 | 1 | 4 |
| 0.211＜Vver＜0.236 | 2 | 9 |
Table 1 motion vector vertical component map table
Claims (9)
1. based on the scan fingerprint image reconfiguration method of estimation, comprise step: buffer memory also upgrades the image of continuous sweep in real time; The motion vector of predicted picture, dynamically choose reference macroblock, determine the frame and the position thereof at prediction match block place, the two field picture at prediction match block place is made interpolation, in the neighborhood of prediction match block, search for best matching blocks, obtain the motion vector of the estimation of sub-pixel precision; Self-adaptation is adjusted motion search range; The motion vector of conversion sequential frame image, the splicing fingerprint image.
2. by the described method of claim 1, it is characterized in that, also comprise step: the image of buffer memory continuous sweep, and upgrade in real time, this mode is removed in real time and has been finished spliced image, only preserve the motion vector of respective frame and the fingerprint image of reconstruction, alleviated the pressure of storage effectively, and requirement of real time.
3. by the described method of claim 1, it is characterized in that, also comprise step: supposition is in subrange, and the finger of slip is with at the uniform velocity or uniformly accelerated motion, the motion vector of predicted picture.
4. by the described method of claim 1, it is characterized in that, also comprise step: according to the numerical value of predicted motion vector, dynamically choose reference macroblock, this method of choosing macro block can obtain the motion vector of fractional form more accurately.
5. by the described method of claim 1, it is characterized in that also comprise step: the picture element interpolation of the estimation of sub-pixel precision, this method can obtain the motion vector of half-pix or 1/4 pixel precision.
6. by the described method of claim 1, it is characterized in that, also comprise step: with the difference of motion vector and predicted vector as feedback quantity, self-adaptation is adjusted the scope of search matched piece, the advantage of this method is, when the velocity variations of pointing slip is big, can either guarantee to search apace best matching blocks, can avoid search to be absorbed in the local optimum point again.
7. by the described method of claim 1, it is characterized in that, also comprise step: the motion vector of conversion sequential frame image, obtain relative displacement discrete between the different frames, the splicing fingerprint image, this method has made full use of the limited vertical resolution of scan image, has solved effectively to be difficult to the problem that is offset about the accurate description scan image because of motion vector horizontal component is less.
8. by the described method of claim 1, its concrete steps are as follows:
(1-1) cut apart the reference position that inswept sensor is pointed in the location, the contrast histogram of statistics continuous sweep image, the iteration selected threshold is judged background or fingerprint image with this;
(1-2) image of buffer memory continuous sweep;
(1-3) motion vector of the consecutive image of calculating buffer memory;
(1-4) the splicing fingerprint image makes full use of the limited vertical resolution of scan image, and the motion vector of conversion sequential frame image obtains relative displacement discrete between the different frames, splices corresponding frame according to displacement relation, rebuilds fingerprint image;
(1-5) upgrade buffer memory and judge also whether finger scanning stops, and removes and has finished spliced image, the renewal buffer memory, the method that adopts same step (1-1) dynamic threshold to cut apart, and in conjunction with the motion vector judgement, stop to slide as finger, then restructuring procedure finishes, otherwise changes step (1-2).
9. press the described method of claim 8, motion vector calculation:
Suppose that all pixels in every two field picture do same motion, then the motion vector of present frame can be represented with the motion vector of image macro, and the specific implementation step is as follows:
(3-1) calculate initial motion vector, choose the sub-piece of M * N pixel at the present frame of image, reference macroblock as the initial motion estimation, if the resolution of sensor is C * L, then can get M=C-2P, N=1～L-1, P=8～16 wherein, adopt full-search algorithm, search the macro block that mates most with reference macroblock at previous frame, the criterion of piece coupling is the absolute average error criterion, promptly seeks the image macro of gray scale absolute average error minimum, and the displacement on two dimensional surface of reference macroblock and match block is initial motion vector, if the vertical component of predicted motion vector is less than or equal to 1, then choose reference macroblock again, every the frame search match block, the displacement on two dimensional surface of reference macroblock and match block promptly obtains initial motion vector divided by frame number at interval;
(3-2) predicted motion vector;
(3-3) dynamically choose reference macroblock;
(3-4) according to definite frame and the position thereof of predicting the match block place of the size of predicted motion vector and reference macroblock;
(3-5) two field picture at prediction match block place is made the picture element interpolation of the estimation of sub-pixel precision, is adopted bilinear interpolation, obtain half-pix or
The point of location of pixels, form with
Pixel or
Pixel is the pixel battle array of spacing;
(3-6) calculation of motion vectors, adopt the absolute average error criterion, on the pixel battle array that interpolation obtains, search for best matching blocks in the neighborhood of prediction match block, the displacement on two dimensional surface of reference macroblock and best matching blocks is the motion vector of the multiframe estimation of sub-pixel precision, for the match block every frame search, motion vector needs divided by frame number at interval;
(3-7) self-adaptation is adjusted motion search range, as feedback quantity, adjusts the scope of motion estimation search best matching blocks with the difference of motion vector and predicted vector adaptively.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN100580706C (en) * | 2008-02-01 | 2010-01-13 | 中国科学院上海技术物理研究所 | Method and system for locating gaze type camera motor point goal |
| CN104281841A (en) * | 2014-09-30 | 2015-01-14 | 深圳市汇顶科技股份有限公司 | Fingerprint identification system and fingerprint processing method and device thereof |
| CN105512587A (en) * | 2014-10-09 | 2016-04-20 | 康耐视公司 | Systems and methods for tracking optical codes |
| CN108509849A (en) * | 2017-02-24 | 2018-09-07 | 三星电子株式会社 | Utilize the electronic equipment and method of the pixel identification sensor position of display |
| CN109544591A (en) * | 2018-10-31 | 2019-03-29 | 北京金山云网络技术有限公司 | A kind of method for estimating, device, electronic equipment and storage medium |
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Family Cites Families (2)
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| FR2749955B1 (en) * | 1996-06-14 | 1998-09-11 | Thomson Csf | FINGERPRINT READING SYSTEM |
| KR100490395B1 (en) * | 2001-10-29 | 2005-05-17 | 삼성전자주식회사 | Motion vector estimation method and apparatus thereof |
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| CN100580706C (en) * | 2008-02-01 | 2010-01-13 | 中国科学院上海技术物理研究所 | Method and system for locating gaze type camera motor point goal |
| CN104281841A (en) * | 2014-09-30 | 2015-01-14 | 深圳市汇顶科技股份有限公司 | Fingerprint identification system and fingerprint processing method and device thereof |
| WO2016049995A1 (en) * | 2014-09-30 | 2016-04-07 | 深圳市汇顶科技股份有限公司 | Fingerprint identification system, and fingerprint processing method therefor and fingerprint processing apparatus thereof |
| CN105512587A (en) * | 2014-10-09 | 2016-04-20 | 康耐视公司 | Systems and methods for tracking optical codes |
| US10628648B2 (en) | 2014-10-09 | 2020-04-21 | Cognex Corporation | Systems and methods for tracking optical codes |
| CN105512587B (en) * | 2014-10-09 | 2020-10-09 | 康耐视公司 | System and method for tracking optical codes |
| CN108509849A (en) * | 2017-02-24 | 2018-09-07 | 三星电子株式会社 | Utilize the electronic equipment and method of the pixel identification sensor position of display |
| CN108509849B (en) * | 2017-02-24 | 2023-10-31 | 三星电子株式会社 | Electronic device and method for recognizing sensor position using pixels of display |
| CN109544591A (en) * | 2018-10-31 | 2019-03-29 | 北京金山云网络技术有限公司 | A kind of method for estimating, device, electronic equipment and storage medium |
| CN109544591B (en) * | 2018-10-31 | 2021-05-28 | 北京金山云网络技术有限公司 | Motion estimation method and device, electronic equipment and storage medium |
| CN110263751A (en) * | 2019-06-27 | 2019-09-20 | Oppo广东移动通信有限公司 | Fingerprint identification method and Related product |
| CN110263751B (en) * | 2019-06-27 | 2021-07-06 | Oppo广东移动通信有限公司 | Fingerprint identification method and related product |
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