CN105447956A - Spliced banknote detection method - Google Patents
Spliced banknote detection method Download PDFInfo
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- CN105447956A CN105447956A CN201510752539.7A CN201510752539A CN105447956A CN 105447956 A CN105447956 A CN 105447956A CN 201510752539 A CN201510752539 A CN 201510752539A CN 105447956 A CN105447956 A CN 105447956A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
- G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
- G07D7/20—Testing patterns thereon
- G07D7/2016—Testing patterns thereon using feature extraction, e.g. segmentation, edge detection or Hough-transformation
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
- G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
- G07D7/20—Testing patterns thereon
- G07D7/2008—Testing patterns thereon using pre-processing, e.g. de-blurring, averaging, normalisation or rotation
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Inspection Of Paper Currency And Valuable Securities (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a spliced banknote detection method. The method specifically comprises the steps of acquiring the image of a banknote, rotating and correcting the image of the banknote so as to further recognize the basic information; based on the obtained basic information, positioning a to-be-detected region; figuring out the gradient graph of the positioned region through the sub-sampling process, and measuring a step signal at the spliced part of the banknote based on the sum of first norms at various differential dimensions; selecting an image-binary threshold for the gradient graph and conducting the binarization treatment through selecting a hard threshold; converting the Hough transformation on the binarized image of the gradient graph in the form of polar coordinates; conducting the straight line detection: in the Hough space, searching out all maximum values, wherein the number of maximum values represents the number of linear abnormal signals in the original image space and the values of the maximum values represent the lengths of the linear abnormal signals in the original image space. According to the technical scheme of the invention, various spliced banknotes can be effectively detected, and the anti-counterfeiting means of a money detector is improved. Meanwhile, the detection efficiency of a bill sorting machine is improved. The method can be applied to the detection of various weak straight line signals.
Description
Technical field
The present invention relates to image procossing correlative technology field, refer in particular to a kind of detection method of splicing bank note.
Background technology
At present, for the detect counterfeit money machine module of circulation all-in-one machine, mainly contain the functions such as false distinguishing, sorting, crown word number identification, abnormal data preservation.Splicing paper money is artificial by two pieces of paper coin, by technical finesse, is well connected into a piece of paper coin.Splicing paper money is divided three classes according to true and false coin connecting method: counterfeit money spells counterfeit money, counterfeit money spells genuine notes, genuine notes spell genuine notes.Splicing the detecting of banknote is cleaning-sorting machine, the difficult point of encountering of ATM, especially for genuine notes splicing genuine notes detect.For first two, because there is part counterfeit money, can false distinguishing means be passed through, utilize infrared, the technological means such as ultraviolet, plain edge ink, magnetic to differentiate.Spell genuine notes for genuine notes, namely splicing paper money is respectively get by two (or multiple) different genuine notes the detection that part is spliced, and technology is not very ripe.And genuine notes are spelled to this banknote of genuine notes, bank is that requirement detects.
Summary of the invention
There is above-mentioned deficiency to overcome in prior art in the present invention, provides a kind of effective detection and the detection method of the splicing bank note of raising counterfeit protection measures.
To achieve these goals, the present invention is by the following technical solutions:
Splice a detection method for bank note, concrete operation step is as follows:
(1) gather banknote image, rotation correction is carried out to image, and then identify Back ground Information;
(2) according to the Back ground Information obtained, the region that will detect is located;
(3) gradient map is asked for the region navigated to, gradient map ask for employing sub sampling, and utilize each dimension difference first norm sum tolerance stitching portion step signal;
(4) the choosing of gradient map binary-state threshold, chooses hard threshold and carries out binaryzation;
(5) binary picture of gradient map is adopted to the hough conversion of polar coordinate mode;
(6) straight-line detection: in hough space, search maximum value, the number of maximum value represents the number of original image space wire abnormal signal, and the size of maximum value represents the length of original image space wire abnormal signal.
By applying the detection method of this splicing bank note in cash recycling system, effectively can detect various splicing paper money, improve detect counterfeit money machine counterfeit protection measures; The result of splicing paper money can also be informed host computer, host computer preserves current banknote image simultaneously, and bank can avoid the Transaction Disputes because splicing coin causes; This detection method can be applied to the detection of various weak line signals, such as leather, the detection of the linear shape signal such as the tearing of the body surfaces such as cloth, cut; In addition, by applying the detection method of this splicing bank note in cleaning-sorting machine, the verification and measurement ratio of cleaning-sorting machine can be improved.
As preferably, in step (1), open the acquisition module acquisition of transmission image of detect counterfeit money machine, after being collected image, start the banknote image process basic algorithm of detect counterfeit money machine, and then identify Back ground Information.Bank note, through detect counterfeit money machine, because splicing signal is more responsive to transmitted light, therefore opens the acquisition module acquisition of transmission image of detect counterfeit money machine; After being collected image, start the banknote image process basic algorithm of detect counterfeit money machine, calculate the value of money of bank note, towards, version, the coordinate of bank note four angle point, the Back ground Information such as the position of magnetic stripe.
As preferably, in step (2), locate the region that will detect and get rid of magnetic stripe and crown word number image-region.Mask the disturbing effect that magnetic stripe and crown word number image-region bring, when namely later step calculates, during surface sweeping image, avoid magnetic stripe and crown word number image-region.
As preferably, in step (3), utilize the difference specifically utilizing step-length-2 ,+2 of the step signal of the first norm sum tolerance stitching portion of the difference of each dimension, and utilize two dimensions simultaneously, formula is as follows:
dx＝abs(I(i，j+2)-I(i，j-2))
dy＝abs(I(i+2，j)-I(i-2，j))。
T(i，j)＝dx+dy
Because splicing signal is general all elongated, contiguous difference can weaken the detection of splicing signal, so present invention utilizes the difference of step-length-2 ,+2, and utilizes two dimensions simultaneously, the effective detection strengthening splicing signal, and non-splicing signal is not enhanced simultaneously; In addition, present invention utilizes the first norm to measure the splicing signal of difference, effectively raise arithmetic speed.
As preferably, in step (5), the basic skills that hough converts detection of straight lines is in the picture: the possible track being gone the reference point in calculating parameter space by the marginal point in image space, and in a totalizer, provide the reference point counting of calculating, finally selects peak value.Hough conversion is in fact a kind of voting mechanism, discrete point in parameter space is voted, if ballot value exceedes a certain threshold value, then think that on have abundant picture point to be positioned at straight line that this parameter point determines by noise and straight line, this method occurs that the impact be interrupted is less.
The invention has the beneficial effects as follows: be applied in cash recycling system, effectively can detect various splicing paper money, improve detect counterfeit money machine counterfeit protection measures, inform that host computer preserves current banknote image simultaneously, bank can avoid the Transaction Disputes because splicing coin causes; Be applied in cleaning-sorting machine, the verification and measurement ratio of cleaning-sorting machine can be improved; The detection of various weak line signals can also be applied to.
Accompanying drawing explanation
Fig. 1 is processing flow chart of the present invention;
Fig. 2 is the cumulative number picture group in parameter space of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention will be further described.
In embodiment as described in Figure 1, a kind of detection method of splicing bank note, concrete operation step is as follows:
(1) bank note is through detect counterfeit money machine, because splicing signal is more responsive to transmitted light, therefore opens the acquisition module acquisition of transmission image of detect counterfeit money machine.After being collected banknote image, rotation correction is carried out to image, starts the banknote image process basic algorithm of detect counterfeit money machine, calculate the value of money of bank note, towards, version, the coordinate of bank note four angle point, the Back ground Information such as the position of magnetic stripe.
(2) according to the Back ground Information that step (1) obtains, locate the region that will detect, mainly mask the impact of magnetic stripe and crown word number image-region.Namely, when later step calculates, during surface sweeping image, magnetic stripe and crown word number image-region is avoided.
(3) located the region that will detect by step (2), in order to reduce operand, carrying out on the original image gathered during compute gradient figure, arithmetic speed can be improved to a great extent.The gradient map of the present invention's definition is as described in formula 1.Because splicing signal is general all elongated, contiguous difference can weaken the detection of splicing signal.Present invention utilizes the difference of step-length-2 ,+2, and utilize two dimensions simultaneously, the effective detection strengthening splicing signal, non-splicing signal is not enhanced simultaneously.In addition, present invention utilizes the first norm to measure the splicing signal of difference, effectively raise arithmetic speed.
dx＝abs(I(i，j+2)-I(i，j-2))
Dy=abs (I (i+2, j)-I (i-2, j)) (formula 1)
T(i，j)＝dx+dy
(4) binaryzation of gradient map because hough of the present invention conversion has the advantage of anti-noise, therefore threshold value choose relatively more flexible, the present invention chooses hard threshold and carries out binaryzation.
(5) hough conversion, carries out hough conversion, for angle θ to the binary picture that step (4) obtains: Δ θ=π/N
θ, N
θget 72, namely the resolution of angle is 2.5.; ρ: Δ ρ=L/N
ρ, N
ρfor L, namely the resolution of ρ is 1.The elementary tactics utilizing hough to convert detection of straight lines is in the picture exactly: the possible track being gone the reference point in calculating parameter space by the marginal point in image space, and in a totalizer, provide the reference point counting of calculating, finally selects peak value.Hough conversion is in fact a kind of voting mechanism, votes to the discrete point in parameter space, if ballot value exceedes a certain threshold value, then thinks on have abundant picture point to be positioned at straight line that this parameter point determines.By noise and straight line, this method occurs that the impact be interrupted is less.
In concrete computation process, need, by discrete for the parameter space M-C cumulative array turning to two dimension, if this array is (m, c), as shown in Figure 2, to establish [m simultaneously
min, m
max] and [c
min, c
max] be respectively the span of slope and intercept.Putting array A during beginning is zero entirely, then to the given marginal point in each image space, allows m get all over [m
min, m
max] interior all possible value, and the computing formula corresponding to formula hough conversion calculates corresponding c.Again according to the value (establish and all round) of m and c to array element A (m, c)=A (m, c)+I.After cumulative end, detect splicing signal by detecting local peaking's point in array A.
(6) straight-line detection, can obtain the array A of parameter space by step (5).In A, search for maximum value, the number of maximum value represents the number of original image space wire abnormal signal, and the size of maximum value represents the length of original image space wire abnormal signal.Such as banknote image is the corresponding 1mm of known 4 pixels of the resolution of 100DPI, then according to the slight crack of coin, splicing, the requirement such as to tear and arranges threshold value, such as do not allow the length of slight crack more than 1cm, namely the maximal value of all maximum value in corresponding A space can not more than 40.
Claims (5)
1. splice a detection method for bank note, it is characterized in that, concrete operation step is as follows:
(1) gather banknote image, rotation correction is carried out to image, and then identify Back ground Information;
(2) according to the Back ground Information obtained, the region that will detect is located;
(3) gradient map is asked for the region navigated to, gradient map ask for employing sub sampling, and utilize each dimension difference first norm sum tolerance stitching portion step signal;
(4) the choosing of gradient map binary-state threshold, chooses hard threshold and carries out binaryzation;
(5) binary picture of gradient map is adopted to the hough conversion of polar coordinate mode;
(6) straight-line detection: in hough space, search maximum value, the number of maximum value represents the number of original image space wire abnormal signal, and the size of maximum value represents the length of original image space wire abnormal signal.
2. a kind of detection method of splicing bank note according to claim 1, is characterized in that, in step (1), open the acquisition module acquisition of transmission image of detect counterfeit money machine, after being collected image, start the banknote image process basic algorithm of detect counterfeit money machine, and then identify Back ground Information.
3. a kind of detection method of splicing bank note according to claim 1, is characterized in that, in step (2), locates the region that will detect and gets rid of magnetic stripe and crown word number image-region.
4. a kind of detection method of splicing bank note according to claim 1, it is characterized in that, in step (3), what utilize the step signal of the first norm sum tolerance stitching portion of the difference of each dimension specifically utilizes step-length-2, the difference of+2, and utilize two dimensions simultaneously, formula is as follows:
dx＝abs(I(i，j+2)-I(i，j-2))
dy＝abs(I(i+2，j)-I(i-2，j))
T(i，j)＝dx+dy。
5. a kind of detection method of splicing bank note according to claim 1, it is characterized in that, in step (5), the basic skills that hough converts detection of straight lines is in the picture: the possible track being gone the reference point in calculating parameter space by the marginal point in image space, and in a totalizer, provide the reference point counting of calculating, finally select peak value.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106296974A (en) * | 2016-07-29 | 2017-01-04 | 广州广电运通金融电子股份有限公司 | A kind of stickup paper money detection method and device |
| CN106548558A (en) * | 2016-11-07 | 2017-03-29 | 广州广电运通金融电子股份有限公司 | A kind of detection method and device of bill one-dimensional signal |
| CN106652169A (en) * | 2016-12-28 | 2017-05-10 | 深圳怡化电脑股份有限公司 | Method and device for identifying paper money |
| CN106815923A (en) * | 2016-12-29 | 2017-06-09 | 深圳怡化电脑股份有限公司 | A kind of recognition methods of bank note version and device |
| CN106875544A (en) * | 2017-02-13 | 2017-06-20 | 深圳怡化电脑股份有限公司 | A kind of paper money discrimination method and device |
| CN106934921A (en) * | 2017-02-22 | 2017-07-07 | 广州广电运通金融电子股份有限公司 | Paper foreign matter pastes detection method and device |
| CN107170108A (en) * | 2017-04-17 | 2017-09-15 | 深圳怡化电脑股份有限公司 | One kind splicing paper money detection method and system |
| CN107742357A (en) * | 2017-10-10 | 2018-02-27 | 深圳怡化电脑股份有限公司 | A kind of recognition methods of paper money number and device |
| CN108074324A (en) * | 2016-11-16 | 2018-05-25 | 深圳怡化电脑股份有限公司 | A kind of paper money discrimination method and device |
| WO2019001191A1 (en) * | 2017-06-26 | 2019-01-03 | 广州广电运通金融电子股份有限公司 | Method and device for detecting spliced banknote |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11110561A (en) * | 1997-09-30 | 1999-04-23 | Advantest Corp | Image information processor |
| US6181813B1 (en) * | 1997-09-29 | 2001-01-30 | Xerox Corporation | Method for counterfeit currency detection using orthogonal line comparison |
| CN101214851A (en) * | 2008-01-10 | 2008-07-09 | 黄席樾 | Intelligent all-weather actively safety early warning system and early warning method thereof for ship running |
| CN101593292A (en) * | 2009-05-07 | 2009-12-02 | 长沙融威电子科技有限公司 | Contactless bank note, ticket are said good-bye and are counted method for anti-counterfeit and device |
| CN102096962A (en) * | 2010-12-23 | 2011-06-15 | 北京新岸线软件科技有限公司 | Paper currency detecting method and device |
| CN102385702A (en) * | 2011-07-06 | 2012-03-21 | 中公高科（北京）养护科技有限公司 | Method for removing notches from pavement image |
| CN102760286A (en) * | 2012-06-07 | 2012-10-31 | 广东威创视讯科技股份有限公司 | Identification method and elimination method for splicing seams of spliced wall |
| CN102912714A (en) * | 2012-10-24 | 2013-02-06 | 华东交通大学 | Machine vision system used for acquiring and processing road crack images |
| CN103738243A (en) * | 2013-10-29 | 2014-04-23 | 惠州华阳通用电子有限公司 | Early warning method for lane departure |
| CN104361672A (en) * | 2014-10-14 | 2015-02-18 | 深圳怡化电脑股份有限公司 | Method for detecting folded corners of paper money |
| WO2015036120A1 (en) * | 2013-09-13 | 2015-03-19 | Giesecke & Devrient Gmbh | Method and device for examining value documents for irregularities |
| CN104504802A (en) * | 2014-10-23 | 2015-04-08 | 深圳怡化电脑股份有限公司 | Detection method for paper money splicing signal |
| CN104751559A (en) * | 2015-03-25 | 2015-07-01 | 深圳怡化电脑股份有限公司 | Money detector and money detecting method |
| CN104809800A (en) * | 2015-04-14 | 2015-07-29 | 深圳怡化电脑股份有限公司 | Preprocessing method for extracting banknote splicing mark, spliced banknote recognition method and device |
-
2015
- 2015-11-06 CN CN201510752539.7A patent/CN105447956A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6181813B1 (en) * | 1997-09-29 | 2001-01-30 | Xerox Corporation | Method for counterfeit currency detection using orthogonal line comparison |
| JPH11110561A (en) * | 1997-09-30 | 1999-04-23 | Advantest Corp | Image information processor |
| CN101214851A (en) * | 2008-01-10 | 2008-07-09 | 黄席樾 | Intelligent all-weather actively safety early warning system and early warning method thereof for ship running |
| CN101593292A (en) * | 2009-05-07 | 2009-12-02 | 长沙融威电子科技有限公司 | Contactless bank note, ticket are said good-bye and are counted method for anti-counterfeit and device |
| CN102096962A (en) * | 2010-12-23 | 2011-06-15 | 北京新岸线软件科技有限公司 | Paper currency detecting method and device |
| CN102385702A (en) * | 2011-07-06 | 2012-03-21 | 中公高科（北京）养护科技有限公司 | Method for removing notches from pavement image |
| CN102760286A (en) * | 2012-06-07 | 2012-10-31 | 广东威创视讯科技股份有限公司 | Identification method and elimination method for splicing seams of spliced wall |
| CN102912714A (en) * | 2012-10-24 | 2013-02-06 | 华东交通大学 | Machine vision system used for acquiring and processing road crack images |
| WO2015036120A1 (en) * | 2013-09-13 | 2015-03-19 | Giesecke & Devrient Gmbh | Method and device for examining value documents for irregularities |
| CN103738243A (en) * | 2013-10-29 | 2014-04-23 | 惠州华阳通用电子有限公司 | Early warning method for lane departure |
| CN104361672A (en) * | 2014-10-14 | 2015-02-18 | 深圳怡化电脑股份有限公司 | Method for detecting folded corners of paper money |
| CN104504802A (en) * | 2014-10-23 | 2015-04-08 | 深圳怡化电脑股份有限公司 | Detection method for paper money splicing signal |
| CN104751559A (en) * | 2015-03-25 | 2015-07-01 | 深圳怡化电脑股份有限公司 | Money detector and money detecting method |
| CN104809800A (en) * | 2015-04-14 | 2015-07-29 | 深圳怡化电脑股份有限公司 | Preprocessing method for extracting banknote splicing mark, spliced banknote recognition method and device |
Non-Patent Citations (2)
| Title |
|---|
| 李俊山: "《数字图像处理》", 30 November 2013 * |
| 龚声蓉: "《数字图像处理与分析》", 31 May 2014 * |
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| WO2018082540A1 (en) * | 2016-11-07 | 2018-05-11 | 广州广电运通金融电子股份有限公司 | Bank note one-dimensional signal detection method and device |
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| CN108074324B (en) * | 2016-11-16 | 2020-04-07 | 深圳怡化电脑股份有限公司 | Paper money counterfeit distinguishing method and device |
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| CN106815923A (en) * | 2016-12-29 | 2017-06-09 | 深圳怡化电脑股份有限公司 | A kind of recognition methods of bank note version and device |
| CN106875544A (en) * | 2017-02-13 | 2017-06-20 | 深圳怡化电脑股份有限公司 | A kind of paper money discrimination method and device |
| CN106875544B (en) * | 2017-02-13 | 2019-10-11 | 深圳怡化电脑股份有限公司 | A kind of paper money discrimination method and device |
| CN106934921B (en) * | 2017-02-22 | 2019-12-31 | 广州广电运通金融电子股份有限公司 | Method and device for detecting sticking of paper foreign matter |
| CN106934921A (en) * | 2017-02-22 | 2017-07-07 | 广州广电运通金融电子股份有限公司 | Paper foreign matter pastes detection method and device |
| CN107170108A (en) * | 2017-04-17 | 2017-09-15 | 深圳怡化电脑股份有限公司 | One kind splicing paper money detection method and system |
| CN107170108B (en) * | 2017-04-17 | 2019-08-23 | 深圳怡化电脑股份有限公司 | A kind of splicing paper money detection method and system |
| WO2019001191A1 (en) * | 2017-06-26 | 2019-01-03 | 广州广电运通金融电子股份有限公司 | Method and device for detecting spliced banknote |
| CN107742357A (en) * | 2017-10-10 | 2018-02-27 | 深圳怡化电脑股份有限公司 | A kind of recognition methods of paper money number and device |
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