CN107170108A - One kind splicing paper money detection method and system - Google Patents
One kind splicing paper money detection method and system Download PDFInfo
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- CN107170108A CN107170108A CN201710248567.4A CN201710248567A CN107170108A CN 107170108 A CN107170108 A CN 107170108A CN 201710248567 A CN201710248567 A CN 201710248567A CN 107170108 A CN107170108 A CN 107170108A
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- image
- pixel
- counterfeiting
- paper money
- banknote
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Classifications
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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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
-
- 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
- G07D7/202—Testing patterns thereon using pattern matching
- G07D7/2041—Matching statistical distributions, e.g. of particle sizes orientations
Abstract
The present invention is applied to financial technology field, and there is provided one kind splicing paper money detection method and system.The present invention obtains residual pixel by removing the object pixel in banknote image in anti-counterfeiting image feature region, and the characteristic value at least one other region in the characteristic value and banknote image of residual pixel is compared, whether be splicing paper money, deterministic process is simple and is easily achieved if can accurately judge the true bank note corresponding to banknote image.
Description
Technical field
The invention belongs to financial technology field, more particularly to a kind of splicing paper money detection method and system.
Background technology
It is artificial by multiple bank note to splice paper money, is connected into a piece of paper coin by technical finesse.Splice paper money according to true and false coin
Connecting method is divided into three classes：Counterfeit money spells counterfeit money, counterfeit money and spells genuine notes, genuine notes spelling genuine notes.Criminal is made by illegal means and spelled
Connect paper money to extract complete genuine notes, serious negative effect is brought to money flow.
However, the paper money identification equipment such as existing cash inspecting machine, is typically only capable to recognize the true and false of bank note, without that can accurately know
Do not splice paper money, how fast and effectively to recognize splicing paper money, prevent criminal with splicing paper money malice exchange genuine notes turn into urgently solve
Certainly the problem of.
The content of the invention
The embodiments of the invention provide one kind splicing paper money detection method and system, it is intended to solves the bank note such as existing cash inspecting machine
Identification equipment, is typically only capable to recognize the true and false of bank note, without that can accurately recognize the problem of splicing paper money.
The first aspect of the embodiment of the present invention provides a kind of splicing paper money detection method, including：
Position of the positioning anti-fake characteristics of image in banknote image；
Algorithm is removed according to the position and presetted pixel, the target picture in the anti-counterfeiting image feature region is removed
Element, obtains the residual pixel in the anti-counterfeiting image feature region；
Compare the characteristic value and the pixel at least one predeterminable area in the banknote image of the residual pixel
Whether characteristic value matches, and at least one described predeterminable area does not include the anti-counterfeiting image feature region；
If mismatching, judge the true bank note corresponding to the banknote image as splicing paper money；Otherwise, it is determined that the bank note
True bank note corresponding to image is not splicing paper money.
The second aspect of the embodiment of the present invention provides a kind of splicing paper money detecting system, including：
Locating module, for position of the positioning anti-fake characteristics of image in banknote image；
Processes pixel module, for removing algorithm according to the position and presetted pixel, removes the anti-counterfeiting image feature
Object pixel in region, obtains the residual pixel in the anti-counterfeiting image feature region；
Matching detection module, for compare the characteristic value of the residual pixel with the banknote image at least one is pre-
If whether the characteristic value of the pixel in region matches, at least one described predeterminable area is not included where the anti-counterfeiting image feature
Region；
Result judgement module, if for mismatching, judging the true bank note corresponding to the banknote image as splicing paper money；
Otherwise, it is determined that the true bank note corresponding to the banknote image is not splicing paper money.
The beneficial effect that the embodiment of the present invention exists compared with prior art is：By removing anti-counterfeiting image in banknote image
Object pixel in feature region obtains residual pixel, and by least one in the characteristic value and banknote image of residual pixel
The characteristic value in other individual regions is compared, and can accurately judge whether the true bank note corresponding to banknote image is splicing
Paper money, deterministic process is simple and is easily achieved.
Brief description of the drawings
Technical scheme in order to illustrate the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
In required for the accompanying drawing that uses be briefly described, it should be apparent that, drawings in the following description are only some of the present invention
Embodiment, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these
Accompanying drawing obtains other accompanying drawings.
Fig. 1 is a kind of implementation process figure for splicing paper money detection method that one embodiment of the present of invention is provided；
Fig. 2 is the implementation process figure of step S102 in Fig. 1 that one embodiment of the present of invention is provided；
Fig. 3 is the implementation process figure of step S103 in Fig. 1 that one embodiment of the present of invention is provided；
Fig. 4 is a kind of structured flowchart for splicing paper money detecting system that one embodiment of the present of invention is provided；
Fig. 5 is the structured flowchart of processes pixel module in Fig. 4 that one embodiment of the present of invention is provided；
Fig. 6 is the structured flowchart of matching detection module in Fig. 4 that one embodiment of the present of invention is provided.
Embodiment
In describing below, in order to illustrate rather than in order to limit, it is proposed that such as tool of particular system structure, technology etc
Body details, thoroughly to understand the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention can also be realized in the other embodiments of details.In other situations, omit to well-known system, device, electricity
Road and the detailed description of method, in case unnecessary details hinders description of the invention.
In order to illustrate technical solutions according to the invention, illustrated below by specific embodiment.
As shown in figure 1, a kind of splicing paper money detection method provided for one embodiment of the present of invention, it includes：
Step S101, position of the positioning anti-fake characteristics of image in banknote image.
Specifically, anti-counterfeiting image feature includes at least one of following characteristics：Serial number, photochromatic printing ink character, watermark,
Offset printing microfilm of characters, holographic magnetic opened window safety line, offset printing are to being patterned, hand engraving head portrait, stealthy denomination numeral or engraving
Intaglio printing.
Specifically, the present embodiment also includes：
(1) region that is likely to occur of the anti-counterfeiting image feature in banknote image, as Probability Area are obtained, interception may
Region, and binary conversion treatment is carried out to the gray level image of Probability Area.For example for the rmb paper currency that face amount is 100 yuan, if
Determine during the region where photochromatic printing ink " 100 " printed words is the gray level image after Probability Area, binary conversion treatment in the region
The gray value of " 100 " printed words is 0, and the gray value of remaining area is 1.
(2) on the bianry image of Probability Area, move a moving window in order line by line, obtain moving window
The pixel accumulated value of region after each movement, moving window spreads all over all positions of Probability Area, according to pixel accumulated value
Change determine position of the anti-counterfeiting image feature in banknote image.
In one embodiment, it is further comprising the steps of before step S101：
A. the banknote image of bank note to be detected is obtained；
B. the border of the anti-counterfeiting image feature is worth to according to the texture and gray scale of banknote image；
C. anti-counterfeiting image feature is obtained according to border.
Specifically, step a can by shooting or scan mode is realized, with infrared light or ultraviolet light shoot function or
The terminal taking or scanning bank note to be measured of person's white light or multispectral shoot function, obtain banknote image.For example, can by with
White light or multispectral image shoot function or camera with ultraviolet light, single irradiation shoot function of infrared light are realized；It is many
Spectrograph refers to that being mixed into one kind using the light source of multiple Single wavelengths simultaneously mixes light source, and can obtain target several do not share the same light
The photo of irradiation is composed, wherein spectral region is visible ray, ultraviolet light and infrared light.
It should be noted that in stepb, texture is a kind of visual signature for reflecting homogeneity phenomenon in image, it embodies
Body surface has a slowly varying or periodically variable surface textural alignment attribute.Specifically, can use
A variety of methods extract the textural characteristics of banknote image, such as statistical method, geometric method, modelling or signal transacting method.Gray value
Acquisition is to obtain gray value according to the red, green, blue color component of banknote image.
Further, because both characteristic values of anti-counterfeiting image feature and the characteristic value of its periphery background image have difference
Not, therefore the border of anti-counterfeiting image feature can be obtained using picture edge characteristic extraction algorithm.Picture edge characteristic extraction algorithm
Specifically include following steps：
(1) filter, processing is filtered to banknote image；
(2) strengthen, target area and other regions Zhong Te are highlighted by strengthening in image correspondence gradient magnitude
The significant changes of value indicative；
(3) detect, by judging that threshold size obtains rim detection in gradient magnitude；
(4) position, the accurate position for determining edge.
Specifically, in step c, the image of border inner is anti-counterfeiting image feature.
Step S102, removes algorithm according to the position and presetted pixel, removes in anti-counterfeiting image feature region
Object pixel, obtains the residual pixel in anti-counterfeiting image feature region.
In the present embodiment, it is to remove specific single or multiple pictures according to the different characteristic of each pixel that pixel, which removes algorithm,
Vegetarian refreshments.Object pixel refers to all pixels of anti-counterfeiting image feature in itself.Residual pixel is removal anti-counterfeiting image feature location
After object pixel in domain, the residual pixel in region.
For example for the rmb paper currency that face amount is 100 yuan, photochromatic printing ink " 100 " character is set as anti-counterfeiting image feature,
A FX on bank note where " 100 " printed words is anti-counterfeiting image feature region, the shape of the FX,
Long or wide equidimension is in advance default.Then object pixel is " 100 " character included all pixels in itself, residual pixel
To remove the pixel of the residual image after " 100 " character in the FX.
It should be noted that anti-counterfeiting image feature, such as serial number, photochromatic printing ink character, frequently include font or
Decorative pattern, due to its special printing technology so that its optical signature is very special, it is difficult to obtain stable characteristic value and carried out to it
Detection.Therefore, the object pixel removed in the present embodiment in anti-counterfeiting image feature region obtains residual pixel, it is to avoid anti-
Influence of the unstability of pseudo- characteristics of image to feature extraction in subsequent step in itself, improves accuracy in detection.
Specifically, as a preferred embodiment, it is adaptive threshold Binarization methods that presetted pixel, which removes algorithm,.
Adaptive threshold is that the binaryzation threshold on the location of pixels is determined according to the pixel Distribution value of the neighborhood block of pixel
Value.This have the advantage that the binary-state threshold of each pixel position is not changeless, but by its surrounding neighbors
The distribution of pixel is determined.The binary-state threshold of the higher image-region of brightness would generally be higher, and the relatively low image of brightness
The binary-state threshold in region then can adaptably diminish.Different brightness, contrast, the local image region of texture will possess phase
Corresponding local binarization threshold value.Conventional adaptive threshold has：1) average of local neighborhood block, 2) local neighborhood block Gauss
Weighted sum.
Due to bank note there are problems that it is new and old and, interference is had to its gray level image, passes through adaptive threshold two-value
Change algorithm, binary conversion treatment is carried out to the gray level image of the intercepted Probability Area, compared to passing through fixed threshold algorithm
Handle obtained bianry image more accurate.
Step S103, compares pixel at least one predeterminable area in the characteristic value and banknote image of residual pixel
Whether characteristic value matches, and at least one described predeterminable area does not include anti-counterfeiting image feature region.
In one embodiment, before step S103, in addition to：According to default feature extraction algorithm, residual pixel is obtained
Characteristic value and banknote image at least one predeterminable area in pixel characteristic value.
Specifically, the default feature extraction algorithm is gray feature extracting method or texture characteristic extracting method.
At least one in the characteristic value and banknote image of the residual pixel obtained using gray feature extracting method is preset
The characteristic value of pixel in region is image intensity value.
At least one in the characteristic value and banknote image of the residual pixel obtained using texture characteristic extracting method is preset
The characteristic value of pixel in region is texture eigenvalue.Specifically, texture eigenvalue includes k rank moment of the origns, such as second moment, three
Rank square etc..
The feature of residual pixel is obtained in the present embodiment using the object pixel removed in anti-counterfeiting image feature region
Value, it is to avoid the unstability of anti-counterfeiting image feature in itself make it that the result of feature extraction is inaccurate, results in a feature that value
With the inaccurate of result, using the spy of the pixel at least one predeterminable area in the characteristic value and banknote image of residual pixel
Value indicative is compared, it is ensured that the stability that characteristic value is obtained, and improves the characteristic matching degree of accuracy.
Step S104, if mismatching, judges the true bank note corresponding to the banknote image as splicing paper money；Otherwise, sentence
True bank note corresponding to the fixed banknote image is not splicing paper money.
Specifically, step S104 also includes：
By statistic algorithm, the scope of the characteristic value of pixel at least one predeterminable area in banknote image is obtained；
Judge the characteristic value of residual pixel whether in the scope；
If not in the scope, being judged to mismatching；If in the scope, being determined as matching.
In a particular application, judge that bank note refers to that bank note is that genuine notes and counterfeit money are spliced as splicing paper money.When judgement bank note
It is not splicing paper money, in addition it is also necessary to verify whether this bank note is that counterfeit money could complete the inspection of forge or true or paper money using forge or true or paper money detection method
Survey.
As shown in Fig. 2 in one embodiment of the invention, the step S102 in the embodiment corresponding to Fig. 1 is specifically wrapped
Include：
Step S201, according to the position, by having including the anti-counterfeiting image feature in the banknote image
The predeterminable area of default solid shape is used as the anti-counterfeiting image feature region.
Step S202, image binaryzation processing is carried out to anti-counterfeiting image feature region.
Step S203, the result handled according to image binaryzation removes the target picture in anti-counterfeiting image feature region
Element, obtains the residual pixel in anti-counterfeiting image feature region.
In a particular application, in step S201, the predeterminable area with default solid shape refers to the shape and chi in region
Very little size is default fixed value.For example, predeterminable area is rectangle, its width and height are fixed value, then anti-counterfeiting image feature
Region just can determine that.Predeterminable area can also be other shapes, such as circular, triangle.
Specifically, step S202 includes：The predeterminable area of banknote image is carried out according to adaptive threshold Binarization methods
Image binaryzation processing.
The object pixel removed in the present embodiment in anti-counterfeiting image feature region obtains residual pixel, it is to avoid false proof
Influence of the unstability of characteristics of image to feature extraction in subsequent step in itself, improves accuracy in detection.
As shown in figure 3, in one embodiment of the invention, the step S103 in the embodiment corresponding to Fig. 1 is specifically wrapped
Include：
Step S301, according to default feature extraction algorithm, obtains residual pixel in anti-counterfeiting image feature region
Characteristic value.
Step S302, according to default feature extraction algorithm, obtains the picture at least one predeterminable area in banknote image
The characteristic value of element；
Step S303, removes the extreme value in the characteristic value of the pixel at least one predeterminable area in banknote image；
Step S304, by the characteristic value of residual pixel with removing at least one predeterminable area in the banknote image after extreme value
In the characteristic value of pixel be compared.
Specifically, the default feature extraction algorithm is gray feature extracting method or texture characteristic extracting method.
Specifically, in step S303, remove extreme value using gymnastics point-score, remove the N number of value of highest and minimum N number of
Value.Due to there is dirty or fold on bank note unavoidably, change violent on the gray level image of various wave bands, have impact on the spy of extraction
Value indicative.And most of dirty or fold will not spread all over whole bank note, and often simply some locally lies in, and results in a feature that value
In have maximum value or minimum value presence.In the characteristic value for removing the pixel at least one predeterminable area in banknote image
Extreme value, can exclude most dirty or fold influences.
The embodiment of the present invention is remained by removing the object pixel in banknote image in anti-counterfeiting image feature region
After image element, and the characteristic value at least one other region in the characteristic value and banknote image of residual pixel is compared, can
Accurately to judge whether the true bank note corresponding to banknote image is splicing paper money, and deterministic process is simple and is easily achieved.
As shown in figure 4, a kind of splicing paper money detecting system 100 provided for one embodiment of the present of invention, for performing Fig. 1
Method and step in corresponding embodiment, it includes：
Locating module 101, for position of the positioning anti-fake characteristics of image in banknote image；
Processes pixel module 102, for removing algorithm according to the position and presetted pixel, removes the anti-counterfeiting image special
The object pixel in region is levied, the residual pixel in the anti-counterfeiting image feature region is obtained；
Matching detection module 103, for comparing the characteristic value of the residual pixel and at least one in the banknote image
Whether the characteristic value of the pixel in individual predeterminable area matches, and at least one described predeterminable area does not include the anti-counterfeiting image feature
Region；
Result judgement module 104, if for mismatching, judging the true bank note corresponding to the banknote image as splicing
Paper money；Otherwise, it is determined that the true bank note corresponding to the banknote image is not splicing paper money.
In a particular application, during above-mentioned each module included by splicing paper money detecting system 100 can be picture processing chip
Software program module, the function that user can be according to actual needs to these program modules is adjusted.
As shown in figure 5, in one embodiment of the invention, the processes pixel module 102 in Fig. 4 includes being used to perform figure
The structure of the method and step in embodiment corresponding to 2, it includes：
Region setup unit 201, for according to the position, the anti-counterfeiting image feature being included in the banknote image
The predeterminable area with default solid shape inside is used as the anti-counterfeiting image feature region；
Binary conversion treatment unit 202, for carrying out image binaryzation processing to the anti-counterfeiting image feature region；
Pixel removal unit 203, for the result according to described image binary conversion treatment, removes the anti-counterfeiting image feature
Object pixel in region, obtains the residual pixel in the anti-counterfeiting image feature region.
As shown in fig. 6, in one embodiment of the invention, the matching detection module 103 in Fig. 4 includes being used to perform figure
The structure of the method and step in embodiment corresponding to 3, it includes：
Fisrt feature extraction unit 301, for according to default feature extraction algorithm, obtaining the anti-counterfeiting image feature place
The characteristic value of residual pixel in region；
Second feature extraction unit 302, for according to default feature extraction algorithm, obtaining in the banknote image at least
The characteristic value of pixel in one predeterminable area；
Extreme value processing unit 303, the spy for removing the pixel at least one predeterminable area in the banknote image
Extreme value in value indicative；
Feature comparing unit 304, for the characteristic value of the residual pixel and the banknote image after extreme value will to be removed
In at least one predeterminable area in the characteristic value of pixel be compared.
The feature of residual pixel is obtained in the present embodiment using the object pixel removed in anti-counterfeiting image feature region
Value, it is to avoid the unstability of anti-counterfeiting image feature in itself make it that the result of feature extraction is inaccurate, results in a feature that value
With the inaccurate of result, using the spy of the pixel at least one predeterminable area in the characteristic value and banknote image of residual pixel
Value indicative is compared, it is ensured that the stability that characteristic value is obtained, and improves the characteristic matching degree of accuracy.
In one embodiment, splicing paper money detecting system 100 also includes：
Image collection module, the banknote image for obtaining bank note to be measured；
Border acquisition module, the anti-counterfeiting image feature is worth to for the texture and gray scale according to the banknote image
Border；
Anti-counterfeiting image acquisition module, for obtaining the anti-counterfeiting image feature according to the border.
Specifically, the anti-counterfeiting image feature includes at least one of following characteristics：Serial number, photochromatic printing ink character,
Watermark, offset printing microfilm of characters, holographic magnetic opened window safety line, offset printing are to being patterned, hand engraving head portrait, stealthy denomination numeral or
Intaglio ink.
Module or unit in all embodiments of the invention, can pass through universal integrated circuit, such as CPU (Central
Processing Unit, central processing unit), or pass through ASIC (Application Specific Integrated
Circuit, application specific integrated circuit) realize.
Step in present invention method can be sequentially adjusted, merged and deleted according to actual needs.
Module or unit in system of the embodiment of the present invention can be combined, divided and deleted according to actual needs.
One of ordinary skill in the art will appreciate that realize all or part of flow in above-described embodiment method, being can be with
The hardware of correlation is instructed to complete by computer program, described program can be stored in a computer read/write memory medium
In, the program is upon execution, it may include such as the flow of the embodiment of above-mentioned each method.Wherein, described storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
Any modifications, equivalent substitutions and improvements made within refreshing and principle etc., should be included in the scope of the protection.
Claims (10)
1. one kind splicing paper money detection method, it is characterised in that including：
Position of the positioning anti-fake characteristics of image in banknote image；
Algorithm is removed according to the position and presetted pixel, the object pixel in the anti-counterfeiting image feature region is removed,
Obtain the residual pixel in the anti-counterfeiting image feature region；
Compare the feature of the characteristic value and the pixel at least one predeterminable area in the banknote image of the residual pixel
Whether value matches, and at least one described predeterminable area does not include the anti-counterfeiting image feature region；
If mismatching, judge the true bank note corresponding to the banknote image as splicing paper money；Otherwise, it is determined that the banknote image
Corresponding true bank note is not splicing paper money.
2. a kind of splicing paper money detection method as claimed in claim 1, it is characterised in that described according to the position and default picture
Element removes algorithm, removes the object pixel in the anti-counterfeiting image feature region, obtains the anti-counterfeiting image feature place
Residual pixel in region, is specifically included：
According to the position, having including the anti-counterfeiting image feature in the banknote image is preset into solid shape
Predeterminable area is used as the anti-counterfeiting image feature region；
Image binaryzation processing is carried out to the anti-counterfeiting image feature region；
According to the result of described image binary conversion treatment, the object pixel in the anti-counterfeiting image feature region is removed, is obtained
To the residual pixel in the anti-counterfeiting image feature region.
3. a kind of splicing paper money detection method as claimed in claim 1, it is characterised in that the spy of the comparison residual pixel
Whether value indicative matches with the characteristic value of the pixel at least one predeterminable area in the banknote image, specifically includes：
According to default feature extraction algorithm, the characteristic value of the residual pixel in the anti-counterfeiting image feature region is obtained；
According to default feature extraction algorithm, the feature of the pixel at least one predeterminable area in the banknote image is obtained
Value；
Remove the extreme value in the characteristic value of the pixel at least one predeterminable area in the banknote image；
By the characteristic value of the residual pixel with removing at least one predeterminable area in the banknote image after extreme value
The characteristic value of pixel is compared.
4. a kind of splicing paper money detection method as claimed in claim 1, it is characterised in that the positioning anti-fake characteristics of image is in paper
Before position on coin image, including：
Obtain the banknote image of bank note to be measured；
The border of the anti-counterfeiting image feature is worth to according to the texture and gray scale of the banknote image；
The anti-counterfeiting image feature is obtained according to the border.
5. a kind of splicing paper money detection method as described in any one of Claims 1-4, it is characterised in that the anti-counterfeiting image is special
Levy including at least one of following characteristics：Serial number, photochromatic printing ink character, watermark, offset printing microfilm of characters, holographic magnetic windowing
Safety line, offset printing are to being patterned, hand engraving head portrait, stealthy denomination numeral or intaglio ink.
6. one kind splicing paper money detecting system, it is characterised in that including：
Locating module, for position of the positioning anti-fake characteristics of image in banknote image；
Processes pixel module, for removing algorithm according to the position and presetted pixel, removes the anti-counterfeiting image feature place
Object pixel in region, obtains the residual pixel in the anti-counterfeiting image feature region；
Matching detection module, for comparing the characteristic value of the residual pixel and at least one preset areas in the banknote image
Whether the characteristic value of the pixel in domain matches, and at least one described predeterminable area does not include the anti-counterfeiting image feature location
Domain；
Result judgement module, if for mismatching, judging the true bank note corresponding to the banknote image as splicing paper money；It is no
Then, judge the true bank note corresponding to the banknote image not as splicing paper money.
7. a kind of splicing paper money detecting system as claimed in claim 6, it is characterised in that the processes pixel module includes：
Region setup unit, for according to the position, by the banknote image including the anti-counterfeiting image feature
Predeterminable area with default solid shape is used as the anti-counterfeiting image feature region；
Binary conversion treatment unit, for carrying out image binaryzation processing to the anti-counterfeiting image feature region；
Pixel removal unit, for the result according to described image binary conversion treatment, removes the anti-counterfeiting image feature location
Object pixel in domain, obtains the residual pixel in the anti-counterfeiting image feature region.
8. a kind of splicing paper money detecting system as claimed in claim 6, it is characterised in that the matching detection module includes：
Fisrt feature extraction unit, for according to default feature extraction algorithm, obtaining in the anti-counterfeiting image feature region
Residual pixel characteristic value；
Second feature extraction unit, for according to default feature extraction algorithm, at least one obtained in the banknote image to be pre-
If the characteristic value of the pixel in region；
In extreme value processing unit, the characteristic value for removing the pixel at least one predeterminable area in the banknote image
Extreme value；
Feature comparing unit, for that the characteristic value of the residual pixel and will remove in the banknote image after extreme value at least
The characteristic value of pixel in one predeterminable area is compared.
9. a kind of splicing paper money detecting system as claimed in claim 6, it is characterised in that also include：
Image collection module, the banknote image for obtaining bank note to be measured；
Border acquisition module, the side of the anti-counterfeiting image feature is worth to for the texture and gray scale according to the banknote image
Boundary；
Anti-counterfeiting image acquisition module, for obtaining the anti-counterfeiting image feature according to the border.
10. a kind of splicing paper money detecting system as described in any one of claim 6 to 9, it is characterised in that the anti-counterfeiting image is special
Levy including at least one of following characteristics：Serial number, photochromatic printing ink character, watermark, offset printing microfilm of characters, holographic magnetic windowing
Safety line, offset printing are to being patterned, hand engraving head portrait, stealthy denomination numeral or intaglio ink.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108062820A (en) * | 2017-11-29 | 2018-05-22 | 深圳怡化电脑股份有限公司 | A kind of paper currency detecting method, note detection device and electronic equipment |
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