CN100517371C - Fingerprint image frame sequence combination method based on wave form match - Google Patents
Fingerprint image frame sequence combination method based on wave form match Download PDFInfo
- Publication number
- CN100517371C CN100517371C CNB2007101000085A CN200710100008A CN100517371C CN 100517371 C CN100517371 C CN 100517371C CN B2007101000085 A CNB2007101000085 A CN B2007101000085A CN 200710100008 A CN200710100008 A CN 200710100008A CN 100517371 C CN100517371 C CN 100517371C
- Authority
- CN
- China
- Prior art keywords
- waveform
- image
- image frame
- saltus step
- frame
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Images
Landscapes
- Image Analysis (AREA)
- Collating Specific Patterns (AREA)
Abstract
The invention relates to a finger print image jointing method for image processing control. For each picture, it only selects part of it as the reference area to get the grey binary wave and to extract the wave jumping information of the current picture with the jointed image overlapping area to realize the jointing. It has small amount of computation, simple in realization, quick to complete the jointing of finger print image, applicable for all kinds of scrape finger print image collection module.
Description
Technical field
The present invention relates to a kind of image processing process control method, is a kind of joining method of fingerprint image frame specifically.
Background technology
The range of application of Automated Fingerprint Identification System is more and more wider now, as mobile phone and computing machine, particularly when Automated Fingerprint Identification System is applied to mobile phone, needs to adopt little fingerprint sensor, otherwise will influence the outward appearance layout and the volume size of mobile phone.On cost of products, the area of the integrated circuit (IC) chip that little fingerprint sensor needs is littler, and cost is lower.Therefore, the scratch type sensor has obtained application more and more widely.
The principle of work of scratch type fingerprint sensor is: gather the fingerprint image of a lot of frames, certain overlapping region is arranged between consecutive frame, need each two field picture be spliced into a complete fingerprint image by image mosaic.Therefore the fingerprint image stitching algorithm is significant for the scratch type fingerprint sensor.
In actual applications, require the response time of Automated Fingerprint Identification System shorter, so require fingerprint image stitching algorithm fast operation, stitching image can satisfy the requirement of algorithm for recognizing fingerprint.
Find through retrieval the prior art document, Chinese patent publication number CN1694118A, open day on November 9th, 2005, the name of innovation and creation is called " the relevant sliding fingerprint sequence seamless joint method of expansion phase place ", and this application case discloses a kind of relevant sliding fingerprint sequence seamless joint method of phase place of expanding.Its weak point is to carry out Fourier transform to realize splicing to each picture frame.
Chinese patent publication number CN 1804862A, in open day on July 19th, 2006, the name of innovation and creation is called " joining method of fingerprint image frame ", and this application case discloses a kind of joining method of fingerprint image frame.Its weak point is to calculate gray variance to realize splicing to each picture frame.
Summary of the invention
The present invention has overcome above-mentioned shortcoming, a kind of reference zone of only handling each picture frame through binaryzation in the fingerprint image splicing is provided, thereby has reduced calculated amount, accelerates the joining method of the fingerprint image frame of splicing speed.
The present invention solves the technical scheme that its technical matters takes: a kind of joining method of fingerprint image frame, to every two field picture, only the binary waveform saltus step information that extracts according to its reference zone is spliced.
Can comprise the steps:
1) receive the fingerprint image frame that the fingerprint image acquisition module collects after, read in first two field picture;
2) picture frame is reduced processing, piece together to go into stitching image, adopt each reference zone to extract template extraction reference zone successively, the waveform saltus step information in the reference zone that calculating is extracted, if can obtain reference area waveform saltus step information, read in the next frame image, enter step 3); If can't obtain reference area waveform saltus step information, read in the next frame image, return step 2);
3) picture frame is reduced processing, the reference zone that adopts a last picture frame to be adopted extracts the reference zone of template extraction current image frame, calculates the waveform saltus step information of reference zone;
4) determine the overlapping region of current image frame and stitching image;
5) existence can be as the image-region of reference area in the above image-region of repeated rows if the current image frame reference zone is demarcated, it as new reference area, is upgraded reference area waveform saltus step information, current image frame is pieced together into stitching image, read in next picture frame, change step 3) over to; Otherwise, enter step 6);
6) select other the new reference of reference zone template extraction zone for use, calculate new reference zone waveform saltus step information, obtain new reference area waveform saltus step information, extract new reference zone, calculate the waveform saltus step information of new reference zone, up to by step 4) and 5) enter step 3); Otherwise,, then enter step 7) and finish splicing if after all reference zones extraction templates are all used, still can not enter step 3);
7) if all images frame all can't extract reference area waveform saltus step information, perhaps handle all images frame, perhaps certain picture frame can not be pieced together into stitching image, and perhaps the stitching image size has reached predetermined threshold value, stops stitching algorithm; If splice successfully, the output stitching image, otherwise, output splicing failure.
It is picture frame deletion the top and bottom each delegation that the fingerprint image acquisition module is collected that the reduction of described picture frame is handled.
Described reference zone is meant in picture frame or the stitching image and extracts the image-region that template extraction is come out by reference zone that size is 1/6～1/3 of a picture frame.
Described step 4) realizes as follows:
1) current image frame is covered on the stitching image, the lastrow of its lastrow and reference area is overlapped, calculate the wave-form similarity of the overlapping part of current image frame and reference area and reference area;
2) current image frame that moves up, each mobile delegation overlaps up to the next line of current image frame bottom line and reference area; Whenever move once, calculate the wave-form similarity of the overlapping part of current image frame and reference area and reference area;
3) the current image frame zone of the maximal value correspondence of All Ranges wave-form similarity is the demarcation repeat region;
4) image line of demarcating the capable wave-form similarity maximum of reference row pairing with it in the repeat region is the demarcation repeated rows of current image frame, the benchmark behavior demarcation reference row corresponding with it;
5) move the waveform of demarcating the repeated rows correspondence in the horizontal direction, whenever move a pixel, calculate once and the capable wave-form similarity of demarcating reference row, the amount of moving horizontally of the pairing demarcation repeated rows of the maximal value of the capable wave-form similarity of gained waveform is the horizontal offset of current image frame.
When piecing together current image frame into stitching image in the described step 5), the weighted mean value that lap is got two superposition image vegetarian refreshments gray-scale values is as the splicing result, and the weights of two superposition image vegetarian refreshments gray-scale values are non-negative and be 1.
Described reference area is meant the continuous 3 row images in the stitching image reference zone, and wherein every capable image all comprises a waveform saltus step information at least.
Described waveform saltus step information is meant in the pairing binary waveform of each image line by 0 and changes to 1 or by 1 position and the order that changes to 0 waveform saltus step.
Described waveform saltus step information is meant in the binary waveform position and the order that changes to continuous two 0 waveform saltus step by 1.
The calculating of described capable wave-form similarity is to be determined by the position of two waveform saltus steps that waveform comprised, number and order, and each two waveforms that participate in calculating belong to reference area and current image frame reference zone respectively.
The computation rule of described capable wave-form similarity is as follows:
1) if two saltus step positions differ 3 or 4, similarity adds 1, and if two saltus steps order in waveform separately identical, similarity adds 1;
2) if two saltus step positions differ 2, similarity adds 2, and if two saltus steps order in waveform separately identical, similarity adds 1;
3) if two saltus step positions differ 1, similarity adds 3, and if two saltus steps order in waveform separately identical, similarity adds 2;
4) if two saltus step positions are identical, similarity adds 4, and if two saltus steps order in waveform separately identical, similarity adds 2;
5) if satisfy rule 1)～rule 4) in the saltus step number that comprises of two waveforms of one or more rules identical, similarity adds 2.
Description of drawings
Fig. 1 is a workflow diagram of the present invention
Fig. 2 calculates the program flow diagram of reference area waveform saltus step information during for program initialization
Fig. 3 is the program flow diagram of splicing single image frame
The sequence of image frames that Fig. 4 is collected for the Authentec AES2510 of company scratch type sensor of the present invention
Fig. 5 is joining method embodiment 1 resulting splicing according to the present invention
Really
Fig. 6 is joining method embodiment 2 resulting splicing results according to the present invention
Fig. 7 is joining method embodiment 3 resulting splicing results according to the present invention
Embodiment
The invention will be further described below in conjunction with embodiment.
The number of the picture frame that the scratch type fingerprint sensor collects at every turn is indefinite, and having in the two adjacent images frame coincide or can be similar to regards identical overlapping region as.This identical degree is weighed by wave-form similarity.The foundation of weighing is the waveform saltus step information of current image frame and the wave-form similarity of reference area.Described wave-form similarity is meant the similarity degree of the corresponding waveform of current picture frame and the corresponding waveform of reference area, determines that according to wave-form similarity the demarcation repeated rows of current image frame and horizontal offset are to locate the overlapping region.The similarity that is adopted in the present embodiment is by waveform saltus step side-play amount, number and ordinal number decision.
In the process of picture frame splicing, deleted picture frame the top and bottom each delegation of being subject to noise, sweat stain and stain influence, in the degree of accuracy that improves stitching algorithm, also reduced calculated amount.
Picture frame after deleting is extracted its subregion splice computing, further reduced calculated amount.
Wherein, hereinafter described picture frame reduction processing is picture frame deletion the top and bottom each delegation that the fingerprint image acquisition module is collected.
The computation rule of described capable wave-form similarity is as follows:
1) if two saltus step positions differ 3 or 4, similarity adds 1, and if two saltus steps order in waveform separately identical, similarity adds 1;
2) if two saltus step positions differ 2, similarity adds 2, and if two saltus steps order in waveform separately identical, similarity adds 1;
3) if two saltus step positions differ 1, similarity adds 3, and if two saltus steps order in waveform separately identical, similarity adds 2;
4) if two saltus step positions are identical, similarity adds 4, and if two saltus steps order in waveform separately identical, similarity adds 2;
5) if satisfy rule 1)～rule 4) in the saltus step number that comprises of two waveforms of one or more rules identical, similarity adds 2.
Embodiment 1
Below in conjunction with as among Fig. 1,2,3, specifically describe image mosaic process in the present embodiment.
At first, suppose that every two field picture size is 16 row, 192 row, gray level 0～255, maximum 192 row of normal spliced image, 192 row.The reference zone that adopts extracts totally 3 of templates, extracts the 65th in picture frame the 1st to the 14th row of reduction back respectively and is listed as the 128th row, the 1st and is listed as the 64th row and the 129th and is listed as 192 row.
After receiving first picture frame, it is reduced processing, remainder is pieced together into stitching image below.Select a reference zone to extract template extraction reference zone, calculate the binaryzation gray threshold and deduct 16 for the reference zone gray average.With reference zone binaryzation, each image line is converted into binary sequence according to this threshold value, obtains corresponding binary waveform.Each waveform is scanned,, write down first position of 0 when running into when jumping to continuous two 0 situation by 1.If the waveform of triplex row image correspondence all comprises waveform saltus step information continuously, as reference area, the waveform saltus step information that it comprises is reference area waveform saltus step information with this triplex row image.
After receiving second two field picture, the reference zone that adopts the previous frame image to be adopted extracts the template extraction reference zone, calculates the binaryzation gray threshold, with the reference zone binaryzation, obtains corresponding binary waveform.Each waveform is scanned,, write down first position of 0 when running into when jumping to continuous two 0 situation by 1.Obtain the waveform saltus step information of each row of reference zone.
Calculate the wave-form similarity of reference area waveform saltus step information and reference zone waveform saltus step information.Calculate the similarity of any continuous three waveforms of reference zone and reference zone waveform saltus step information respectively, continuous three image lines in pairing continuous three the waveform corresponding reference zones of the maximal value of all wave-form similarities are the demarcation repeat region of second picture frame.Three respectively corresponding three capable wave-form similarities of waveform, the pairing image line of maximal value wherein is the demarcation repeated rows of second picture frame, and pairing reference row is the demarcation reference row.Move the waveform saltus step information of demarcating the repeated rows correspondence in the horizontal direction, calculate each row wave-form similarity respectively, the amount of movement of the waveform saltus step information of the maximal value correspondence of all similarities is the horizontal offset of second picture frame.
After obtaining the demarcation repeated rows position and horizontal offset of second picture frame, determined the overlapping region of second picture frame, from the reference zone of second picture frame, select continuous three to be positioned at the image line of demarcating on the repeated rows, and each image provisional capital comprises waveform saltus step information, thereby obtains new reference area and new reference area waveform saltus step information.Second picture frame pieced together into stitching image, at first be that the demarcation repeated rows is overlapped with the demarcation reference row, move second two field picture to the left or to the right according to horizontal offset then, Non-overlapping Domain directly pieces together to go into stitching image, to the overlapping region, stitching image pixel gray-scale value weights are 0.6 when calculating the gray-scale value weighted mean value, and current image frame pixel gray-scale value weights are 0.4.The white space that moves the stitching image that is caused owing to picture frame is 0 pixel filling with gray scale.
After second two field picture is finished dealing with, read in follow-up picture frame, disposal route is with second frame.Output is as the image of Fig. 5 at last.
Embodiment 2
Below in conjunction with as among Fig. 1,2,3, specifically describe image mosaic process in the present embodiment.
At first, suppose that every two field picture size is 16 row, 192 row, gray level 0～255, maximum 192 row of normal spliced image, 192 row.The reference zone that adopts extracts totally 3 of templates, extracts the 73rd in picture frame the 1st to the 14th row of reduction back respectively and is listed as the 120th row, the 25th and is listed as the 72nd row and the 121st and is listed as 168 row.
After receiving first picture frame, it is reduced processing, remainder is pieced together into stitching image below.Select a reference zone to extract template extraction reference zone, calculate the binaryzation gray threshold and deduct 16 for the reference zone gray average.With reference zone binaryzation, each image line is converted into binary sequence according to this threshold value, obtains corresponding binary waveform.Each waveform is scanned,, write down first position of 0 when running into when jumping to continuous two 0 situation by 1.If the waveform of triplex row image correspondence all comprises waveform saltus step information continuously, as reference area, the waveform saltus step information that it comprises is reference area waveform saltus step information with this triplex row image.
After receiving second two field picture, the reference zone that adopts the previous frame image to be adopted extracts the template extraction reference zone, calculates the binaryzation gray threshold, with the reference zone binaryzation, obtains corresponding binary waveform.Each waveform is scanned,, write down first position of 0 when running into when jumping to continuous two 0 situation by 1.Obtain the waveform saltus step information of each row of reference zone.
Calculate the wave-form similarity of reference area waveform saltus step information and reference zone waveform saltus step information.Calculate the similarity of any continuous three waveforms of reference zone and reference zone waveform saltus step information respectively, continuous three image lines in pairing continuous three the waveform corresponding reference zones of the maximal value of all wave-form similarities are the demarcation repeat region of second picture frame.Three respectively corresponding three capable wave-form similarities of waveform, the pairing image line of maximal value wherein is the demarcation repeated rows of second picture frame, and pairing reference row is the demarcation reference row.Move the waveform saltus step information of demarcating the repeated rows correspondence in the horizontal direction, calculate each row wave-form similarity respectively, the amount of movement of the waveform saltus step information of the maximal value correspondence of all similarities is the horizontal offset of second picture frame.
After obtaining the demarcation repeated rows position and horizontal offset of second picture frame, determined the overlapping region of second picture frame, from the reference zone of second picture frame, select continuous three to be positioned at the image line of demarcating on the repeated rows, and each image provisional capital comprises waveform saltus step information, thereby obtains new reference area and new reference area waveform saltus step information.Second picture frame pieced together into stitching image, at first be that the demarcation repeated rows is overlapped with the demarcation reference row, move second two field picture to the left or to the right according to horizontal offset then, Non-overlapping Domain directly pieces together to go into stitching image, to the overlapping region, stitching image pixel gray-scale value weights are 0.5 when calculating the gray-scale value weighted mean value, and current image frame pixel gray-scale value weights are 0.5.The white space that moves the stitching image that is caused owing to picture frame is 0 pixel filling with gray scale.
After second two field picture is finished dealing with, read in follow-up picture frame, disposal route is with second frame.Output is as the image of Fig. 6 at last.
Embodiment 3
Below in conjunction with as among Fig. 1,2,3, specifically describe image mosaic process in the present embodiment.
At first, suppose that every two field picture size is 16 row, 192 row, gray level 0～255, maximum 192 row of normal spliced image, 192 row.The reference zone that adopts extracts totally 3 of templates, extracts the 81st in picture frame the 1st to the 14th row of reduction back respectively and is listed as the 112nd row, the 49th and is listed as the 80th row and the 113rd and is listed as 144 row.
After receiving first picture frame, it is reduced processing, remainder is pieced together into stitching image below.Select a reference zone to extract template extraction reference zone, calculate the binaryzation gray threshold and deduct 16 for the reference zone gray average.With reference zone binaryzation, each image line is converted into binary sequence according to this threshold value, obtains corresponding binary waveform.Each waveform is scanned,, write down first position of 0 when running into when jumping to continuous two 0 situation by 1.If the waveform of triplex row image correspondence all comprises waveform saltus step information continuously, as reference area, the waveform saltus step information that it comprises is reference area waveform saltus step information with this triplex row image.
After receiving second two field picture, the reference zone that adopts the previous frame image to be adopted extracts the template extraction reference zone, calculates the binaryzation gray threshold, with the reference zone binaryzation, obtains corresponding binary waveform.Each waveform is scanned,, write down first position of 0 when running into when jumping to continuous two 0 situation by 1.Obtain the waveform saltus step information of each row of reference zone.
Calculate the wave-form similarity of reference area waveform saltus step information and reference zone waveform saltus step information.Calculate the similarity of any continuous three waveforms of reference zone and reference zone waveform saltus step information respectively, continuous three image lines in pairing continuous three the waveform corresponding reference zones of the maximal value of all wave-form similarities are the demarcation repeat region of second picture frame.Three respectively corresponding three capable wave-form similarities of waveform, the pairing image line of maximal value wherein is the demarcation repeated rows of second picture frame, and pairing reference row is the demarcation reference row.Move the waveform saltus step information of demarcating the repeated rows correspondence in the horizontal direction, calculate each row wave-form similarity respectively, the amount of movement of the waveform saltus step information of the maximal value correspondence of all similarities is the horizontal offset of second picture frame.
After obtaining the demarcation repeated rows position and horizontal offset of second picture frame, determined the overlapping region of second picture frame, from the reference zone of second picture frame, select continuous three to be positioned at the image line of demarcating on the repeated rows, and each image provisional capital comprises waveform saltus step information, thereby obtains new reference area and new reference area waveform saltus step information.Second picture frame pieced together into stitching image, at first be that the demarcation repeated rows is overlapped with the demarcation reference row, move second two field picture to the left or to the right according to horizontal offset then, Non-overlapping Domain directly pieces together to go into stitching image, to the overlapping region, stitching image pixel gray-scale value weights are 0.3 when calculating the gray-scale value weighted mean value, and current image frame pixel gray-scale value weights are 0.7.The white space that moves the stitching image that is caused owing to picture frame is 0 pixel filling with gray scale.
After second two field picture is finished dealing with, read in follow-up picture frame, disposal route is with second frame.Output is as the image of Fig. 7 at last.
The number of greyscale levels of described each picture frame can be an any range, as 0～255 or 0～15, the picture frame for non-0～255 only needs that its grey level range is transformed into 0～255 and gets final product, for gray level is 0～1 bianry image, does not then need binaryzation directly to extract waveform saltus step information and gets final product.The present invention also is applicable to and adopts other image acquisition imaging processes that are similar to scratch type fingerprint image acquisition mode.
More than the joining method of the fingerprint image frame based on Waveform Matching provided by the present invention is described in detail, used specific embodiment in the literary composition principle of the present invention and embodiment are set forth, the explanation of above embodiment is used for helping to understand method of the present invention and thought.In sum, this description should not be construed as limitation of the present invention.
Claims (10)
1. the joining method of a fingerprint image frame, it is characterized in that: at first fingerprint image frame to be spliced is reduced processing, from the picture frame after the reduction, select reference zone again, extract reference zone waveform saltus step information and carry out the splicing of fingerprint image frame, comprise the steps:
1) receive the fingerprint image frame that the fingerprint image acquisition module collects after, read in first two field picture;
2) picture frame is reduced processing, piece together to go into stitching image, adopt each reference zone to extract template extraction reference zone successively, the waveform saltus step information in the reference zone that calculating is extracted, if can obtain reference area waveform saltus step information, read in the next frame image, enter step 3); If can't obtain reference area waveform saltus step information, read in the next frame image, return step 2);
3) picture frame is reduced processing, the reference zone that adopts a last picture frame to be adopted extracts the reference zone of template extraction current image frame, calculates the waveform saltus step information of reference zone;
4) determine the overlapping region of current image frame and stitching image;
5) existence can be as the image-region of reference area in the above image-region of repeated rows if the current image frame reference zone is demarcated, it as new reference area, is upgraded reference area waveform saltus step information, current image frame is pieced together into stitching image, read in next picture frame, change step 3) over to; Otherwise, enter step 6);
6) select other the new reference of reference zone template extraction zone for use, calculate new reference zone waveform saltus step information, obtain new reference area waveform saltus step information, extract new reference zone, calculate the waveform saltus step information of new reference zone, up to by step 4) and 5) enter step 3); Otherwise,, then enter step 7) and finish splicing if after all reference zones extraction templates are all used, still can not enter step 3);
7) if all images frame all can't extract reference area waveform saltus step information, perhaps handle all images frame, perhaps certain picture frame can not be pieced together into stitching image, and perhaps the stitching image size has reached predetermined threshold value, stops stitching algorithm; If splice successfully, the output stitching image, otherwise, output splicing failure.
2. the joining method of fingerprint image frame according to claim 1 is characterized in that: the reduction of described picture frame handle be picture frame deletion that the fingerprint image acquisition module is collected topmost and bottom each delegation.
3. the joining method of fingerprint image frame according to claim 1 is characterized in that: described reference zone is meant in picture frame or the stitching image and extracts the image-region that template extraction is come out by reference zone that size is 1/6～1/3 of a picture frame.
4. the joining method of fingerprint image frame according to claim 1, it is characterized in that: described step 4) realizes as follows:
1) current image frame is covered on the stitching image, the lastrow of its lastrow and reference area is overlapped, calculate the wave-form similarity of the overlapping part of current image frame and reference area and reference area;
2) current image frame that moves up, each mobile delegation overlaps up to the next line of current image frame bottom line and reference area; Whenever move once, calculate the wave-form similarity of the overlapping part of current image frame and reference area and reference area;
3) the current image frame zone of the maximal value correspondence of All Ranges wave-form similarity is the demarcation repeat region;
4) image line of demarcating the capable wave-form similarity maximum of reference row pairing with it in the repeat region is the demarcation repeated rows of current image frame, the benchmark behavior demarcation reference row corresponding with it;
5) move the waveform of demarcating the repeated rows correspondence in the horizontal direction, whenever move a pixel, calculate once and the capable wave-form similarity of demarcating reference row, the amount of moving horizontally of the pairing demarcation repeated rows of the maximal value of the capable wave-form similarity of gained waveform is the horizontal offset of current image frame.
5. the joining method of fingerprint image frame according to claim 1, it is characterized in that: when piecing together current image frame into stitching image in the described step 5), lap is got the weighted mean value of two superposition image vegetarian refreshments gray-scale values as the splicing result, the weights of two superposition image vegetarian refreshments gray-scale values are non-negative and be 1.
6. the joining method of fingerprint image frame according to claim 1 is characterized in that: described reference area is meant the continuous 3 row images in the stitching image reference zone, and wherein every capable image all comprises a waveform saltus step information at least.
7. the joining method of fingerprint image frame according to claim 1 is characterized in that: described waveform saltus step information is meant in the pairing binary waveform of each image line by 0 and changes to 1 or by 1 position and the order that changes to 0 waveform saltus step.
8. the joining method of fingerprint image frame according to claim 7 is characterized in that: described waveform saltus step information is meant in the binary waveform position and the order that changes to continuous two 0 waveform saltus step by 1.
9. the joining method of fingerprint image frame according to claim 4, it is characterized in that: the calculating of described capable wave-form similarity is to be determined by the position of two waveform saltus steps that waveform comprised, number and order, and each two waveforms that participate in calculating belong to reference area and current image frame reference zone respectively.
10. the joining method of fingerprint image frame according to claim 9, it is characterized in that: the computation rule of described capable wave-form similarity is as follows:
1) if two saltus step positions differ 3 or 4, similarity adds 1, and if two saltus steps order in waveform separately identical, similarity adds 1;
2) if two saltus step positions differ 2, similarity adds 2, and if two saltus steps order in waveform separately identical, similarity adds 1;
3) if two saltus step positions differ 1, similarity adds 3, and if two saltus steps order in waveform separately identical, similarity adds 2;
4) if two saltus step positions are identical, similarity adds 4, and if two saltus steps order in waveform separately identical, similarity adds 2;
5) if satisfy rule 1)～rule 4) in the saltus step number that comprises of two waveforms of one or more rules identical, similarity adds 2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB2007101000085A CN100517371C (en) | 2007-06-04 | 2007-06-04 | Fingerprint image frame sequence combination method based on wave form match |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB2007101000085A CN100517371C (en) | 2007-06-04 | 2007-06-04 | Fingerprint image frame sequence combination method based on wave form match |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101086766A CN101086766A (en) | 2007-12-12 |
| CN100517371C true CN100517371C (en) | 2009-07-22 |
Family
ID=38937715
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNB2007101000085A Expired - Fee Related CN100517371C (en) | 2007-06-04 | 2007-06-04 | Fingerprint image frame sequence combination method based on wave form match |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN100517371C (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012163112A1 (en) * | 2011-05-27 | 2012-12-06 | 汉王科技股份有限公司 | Frame-skipping scanning and recognizing device and method |
Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102063611B (en) * | 2010-01-21 | 2013-05-29 | 汉王科技股份有限公司 | Method and system for inputting characters |
| CN102602294B (en) * | 2012-03-23 | 2014-12-10 | 潍柴动力股份有限公司 | Method and device for displaying fuel economy state of car engine |
| CN103679179A (en) * | 2012-09-18 | 2014-03-26 | 成都方程式电子有限公司 | High-speed local relevance calculation method and device |
| CN103136517B (en) * | 2013-03-04 | 2015-11-11 | 杭州景联文科技有限公司 | A kind of real-time joining method of rolling fingerprint image sequence selected based on key column |
| CN106062778B (en) * | 2016-04-01 | 2019-05-07 | 深圳市汇顶科技股份有限公司 | Fingerprint identification method, device and terminal |
| CN106104575B (en) * | 2016-06-13 | 2019-09-17 | 北京小米移动软件有限公司 | Fingerprint template generation method and device |
| CN106326869B (en) * | 2016-08-26 | 2021-01-12 | Oppo广东移动通信有限公司 | Fingerprint identification method and device and mobile terminal |
| CN106993157A (en) * | 2017-04-05 | 2017-07-28 | 宇龙计算机通信科技(深圳)有限公司 | A kind of intelligent control method and device based on dual camera |
| US11281886B2 (en) | 2018-02-12 | 2022-03-22 | Huawei Technologies Co., Ltd. | Fingerprint enrollment method and terminal |
| CN111209872B (en) * | 2020-01-09 | 2022-05-03 | 浙江工业大学 | Real-time rolling fingerprint splicing method based on dynamic programming and multi-objective optimization |
| CN111524067B (en) * | 2020-04-01 | 2023-09-12 | 北京东软医疗设备有限公司 | Image processing method, device and equipment |
-
2007
- 2007-06-04 CN CNB2007101000085A patent/CN100517371C/en not_active Expired - Fee Related
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012163112A1 (en) * | 2011-05-27 | 2012-12-06 | 汉王科技股份有限公司 | Frame-skipping scanning and recognizing device and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101086766A (en) | 2007-12-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN100517371C (en) | Fingerprint image frame sequence combination method based on wave form match | |
| US8433109B2 (en) | Direction controlling system and method of an electronic device | |
| CN102103753B (en) | Use method and the terminal of real time camera estimation detect and track Moving Objects | |
| JP5229050B2 (en) | Document area extraction apparatus, method, and program from image | |
| CN109829467A (en) | Image labeling method, electronic device and non-transient computer-readable storage medium | |
| CN105260733A (en) | Method and device for processing image information | |
| CN102360419A (en) | Method and system for computer scanning reading management | |
| CN101807257A (en) | Method for identifying information of image tag | |
| CN103530590A (en) | DPM (direct part mark) two-dimensional code recognition system | |
| EP2309421A1 (en) | Image processing method for locating and recognizing barcodes in image frame, computer readable storage medium, and image processing apparatus | |
| JP5449329B2 (en) | Method and system for enhanced image alignment | |
| CN101908136A (en) | Table identifying and processing method and system | |
| CN101896920A (en) | Image processing method and device based on motion scan | |
| CN101315668A (en) | Automatic detection method for test paper form | |
| CN102841676A (en) | Webpage browsing control system and method | |
| US10055668B2 (en) | Method for the optical detection of symbols | |
| JP2017120503A (en) | Information processing device, control method and program of information processing device | |
| CN101256630B (en) | Denoising apparatus and method for improving document image binaryzation performance | |
| CN100373393C (en) | Scan fingerprint image reconfiguration method based on movement estimation | |
| CN102782705A (en) | Resolution adjustment of an image that includes text undergoing an OCR process | |
| CN100363940C (en) | Document image geometry fault correction method | |
| CN113628113A (en) | Image splicing method and related equipment thereof | |
| CN102855484A (en) | Target detection method, device and system based on local integral image processing | |
| CN115376132A (en) | Data processing method and device for scanning pen, storage medium and scanning pen | |
| CN107194391A (en) | A kind of method for the intellectual analysis positioning electronic ballot paper for resisting image stretch skew |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| DD01 | Delivery of document by public notice |
Addressee: Wang Peng Document name: Notification to Pay the Fees |
|
| DD01 | Delivery of document by public notice |
Addressee: Wang Peng Document name: Notification of Termination of Patent Right |
|
| C17 | Cessation of patent right | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20090722 Termination date: 20100604 |