CN105023163B - A kind of anti-counterfeiting system and method based on chaos graph label - Google Patents
A kind of anti-counterfeiting system and method based on chaos graph label Download PDFInfo
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- CN105023163B CN105023163B CN201510349037.XA CN201510349037A CN105023163B CN 105023163 B CN105023163 B CN 105023163B CN 201510349037 A CN201510349037 A CN 201510349037A CN 105023163 B CN105023163 B CN 105023163B
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Abstract
The invention discloses a kind of anti-counterfeiting system and method based on chaos graph label, the characteristic information that chaos graph label is extracted using image recognition technology is stored in by the ID of chaos graph label, characteristic information and with the information of the associated subject matter of label in the data of high in the clouds；The characteristic information that chaos graph label is calculated using identical image recognition technology finds out corresponding label characteristic information in database beyond the clouds using the ID of chaos graph label；According to two characteristic information similarities, judge whether to match, match, then return to the associated subject matter information of current label, mismatch, then it fails to match for return；System includes：Label information input system and label Verification system.The present invention is realized anti-fake using having not reproducible natural chaos structure graph as antifalsification label, and using image scanning, computer vision, graphic feature extraction, magnanimity figure retrieval technique；Be difficult to replicate with label, differentiate quick and precisely, it is wide using easy and range.
Description
Technical field
The invention belongs to field of anti-counterfeit technology more particularly to a kind of anti-counterfeiting systems and method based on chaos graph label.
Background technology
Anti-counterfeiting technology is an interleaving techniques for being related to subjects, is usually difficult to replicability using antifalsification label,
The product protected and the mechanism indicated on label or producer are subjected to tight association to a certain extent.With anti-counterfeiting technology and city
The economic fast development in field, the anti-counterfeiting technology not only making such as extensive bank, customs, the tax, finance, public security, government department
Passport, certificate, currency, on ticket and marketable securities, and be widely used in tobacco and wine, food, drug, health products, makeup
The commodity such as product, clothes, CD product and pesticide, chemical fertilizer, auto parts and components in the means of production it is anti-fake on.Anti-counterfeiting technology pair
Fraud false making activity is controlled and hit, safeguards that good market competition environment, protection intellectual property play an important roll.Businessman couple
The protection of intellectual property protection is increasingly paid attention to, therefore the demand to antifalse technology is very urgent.The core of anti-counterfeiting system
It is exactly antifalsification label.The antifalsification label being widely used at present is varied, as laser hologram label, watermark label, code label,
Digital coding label, bar coded sticker, two-dimension code label and RFID tag etc..For in principle, these antifalsification labels all may be used
To be replicated, can not ensure absolutely anti-fake.Other than the guarantee of the incidence relation between label and object is extremely important, prevent
Another key of antiforge system is exactly to test pseudo- accuracy.Although the bubble label (Bubble that Prooftag companies of France release
Tag bubble portion) is theoretically hardly reproducible, but since bubble portion does not have tamper-evident function, and tamper-evident part is complete
It is possible that being repaired or replicating, the synthesis non-reproduction of the label is caused to substantially reduce.
Existing backtracking inquiry type anti-counterfeiting technology be based on artificial antifalsification label, as digital coding, bar code, Quick Response Code and
RFID etc. can be replicated and forge in principle；Existing not reproducible natural structure graphical label it is complicated to not process and
Human eye is needed to judge.
Invention content
The purpose of the present invention is to provide a kind of anti-counterfeiting system and method based on chaos graph label, it is intended to solve existing
Backtracking inquiry type anti-counterfeiting technology, which is based on artificial antifalsification label, all can be replicated and forge, not reproducible natural structure graphical label
The problem of to not process complexity and human eye being needed to judge.
The invention is realized in this way a kind of method for anti-counterfeit based on chaos graph label, described to be based on chaos graph mark
The method for anti-counterfeit of label includes：
The characteristic information that chaos graph label is extracted first with image recognition technology, by the ID of chaos graph label, spy
Reference is ceased and is stored in the data of high in the clouds with the information of the associated subject matter of label；
Secondly the characteristic information that chaos graph label is calculated using identical image recognition technology, utilizes chaos graph mark
The ID of label finds out corresponding label characteristic information in database beyond the clouds；
Finally according to two characteristic information similarities, judge whether to match, if it does, then it is associated to return to current label
Subject matter information, if it does not match, returning, it fails to match.
Another object of the present invention is to provide a kind of anti-counterfeiting system based on chaos graph label, the label information record
Enter system includes with label Verification system：
Label information input system is extracted the characteristic information of chaos graph label using image recognition technology, then will mixed
The ID of ignorant graphical label, characteristic information and in the information deposit high in the clouds data of the associated subject matter of label；
Label Verification system calculates the characteristic information of chaos graph label using identical image recognition technology, then
Corresponding label characteristic information is found out in database beyond the clouds using the ID of chaos graph label, finally according to two characteristic information phases
Like degree, judge whether to match, if it does, then the associated subject matter information of current label is returned to, if it does not match, return
With failure.
Further, the label information input system is as follows：
Step 1 is staggered certain angle when each graph scanning using multi-angle graph scanning technology compared with last scan；
Step 2 calculates the angle point of the chaos graph label of different visual angles using Corner Detection Algorithm, and carries out feature
Matching, obtains the matching characteristic point between adjacent view image；
Step 3 calculates the basic square between neighbor image according to computer multiple view geometry principle using 7 algorithms
Battle array；
Step 4 calculates each characteristic point in any image in its neighbor figure using above-mentioned basis matrix
As upper corresponding to polar curve, using local template matching algorithm, calculate to other matched characteristic points present on polar curve；
Step 5 calculates the matching characteristic point parallax of matching image, obtains neighbor image parallactic figure；
Step 6 calculates chaos using principle of parallax by the disparity map of the neighbor image obtained in above-mentioned steps
Characteristic point space coordinate in graphical label, and further obtain the characteristic point relative position information in chaos graph label；
Step 7 extracts the corresponding chaos graph in each visual angle using structure-based image texture characteristic extraction algorithm
The texture information of label midpoint bit distribution；
Step 8, by the feature relative position information of the associated subject matter information of label and the chaos graph label of acquisition and
Texture information constitutes complex data information, assigns id information, and complex data information and id information are stored in background data base.
Further, the label information identifying system specific steps are as follows：
Step 1 is staggered certain angle when each graph scanning using multi-angle graph scanning technology compared with last scan；
Step 2 calculates the angle point of the chaos graph label of different visual angles using Corner Detection Algorithm, and carries out feature
Matching, obtains the matching characteristic point between adjacent view image；Step 3 is counted according to computer multiple view geometry principle using 7
Method calculates the basis matrix between neighbor image；
Step 4 calculates each characteristic point in any image in its neighbor figure using above-mentioned basis matrix
As upper corresponding to polar curve, using local template matching algorithm, calculate to other matched characteristic points present on polar curve；
Step 5 calculates the matching characteristic point parallax of matching image, obtains neighbor image parallactic figure；
Step 6 calculates chaos using principle of parallax by the disparity map of the neighbor image obtained in above-mentioned steps
Characteristic point space coordinate in graphical label, and further obtain the characteristic point relative position information in chaos graph label；
Step 7 extracts the corresponding chaos graph in each visual angle using structure-based image texture characteristic extraction algorithm
The texture information of label midpoint bit distribution；
Step 8 identifies the 2 D code information on outgoing label, reads tag ID；Step 9, using tag ID in database
The label information of typing before middle acquisition, and with the angle point relative position information of chaos graph label achieved above, label line
It manages feature and carries out similarity measurement；
Step 10 is set if the label information similarity that there is chaos image information and above-mentioned acquisition in the database is more than
Determine the label of threshold value, then confirms that association subject matter is certified products, and send back subject matter information associated with label；If instead
It is not present, then confirms that related product is non-certified products.
Anti-counterfeiting system and method provided by the invention based on chaos graph label, relatively existing anti-counterfeiting technology have
Following advantage：
(1) present invention using chaos graph can not copy feature design antifalsification label, have it is low-cost absolutely it is excellent
Gesture.
(2) present invention calculates the space surface relationship of chaos graph, and root using image recognition and multiple view geometry principle
According to the structure uniqueness and similarity measurement of chaos label, the intelligent recognition of chaos graph label is realized, differentiate quick and precisely, pole
Big degree promotes user experience.
(3) present invention extraction chaos graph textural characteristics, and carry out contrast verification during intelligent recognition, avoid due to
Error caused by the accuracy deficiency of chaos graph Label space structure recognition, further improves the reliable of verification result
Property.
Description of the drawings
Fig. 1 is the method for anti-counterfeit flow chart provided in an embodiment of the present invention based on chaos graph label；
Fig. 2 is the anti-counterfeiting system structural schematic diagram provided in an embodiment of the present invention based on chaos graph label.
Specific implementation mode
In order to make the purpose , technical scheme and advantage of the present invention be clearer, with reference to embodiments, to the present invention
It is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.
The present invention is used as antifalsification label using with not reproducible natural chaos structure graph, and utilization image scanning,
Computer vision, graphic feature extraction and structural texture information extraction, realize a kind of antifalse system, have label difficult
To replicate, differentiate quick and precisely, using easy and wide use scope feature.
1 pair of application principle of the invention is explained in detail below in conjunction with the accompanying drawings.
As shown in Figure 1, the method for anti-counterfeit based on chaos graph label of the embodiment of the present invention includes：
The characteristic information that chaos graph label is extracted first with image recognition technology, by the ID of chaos graph label, spy
Reference is ceased and is stored in the data of high in the clouds with the information of the associated subject matter of label；
Secondly the characteristic information that chaos graph label is calculated using identical image recognition technology, utilizes chaos graph mark
The ID of label finds out corresponding label characteristic information in database beyond the clouds；
Finally according to two characteristic information similarities, judge whether to match, if it does, then it is associated to return to current label
Subject matter information, if it does not match, returning, it fails to match.
As shown in Fig. 2, including label information input system and label the present invention is based on the anti-counterfeiting system of chaos graph label
Two parts of verification system；
Label information input system is extracted the characteristic information of chaos graph label using image recognition technology, then will mixed
The ID of ignorant graphical label, characteristic information and in the information deposit high in the clouds data of the associated subject matter of label；
Label Verification system calculates the characteristic information of chaos graph label using identical image recognition technology, then
Corresponding label characteristic information is found out in database beyond the clouds using the ID of chaos graph label, finally according to two characteristic information phases
Like degree, judge whether to match, if it does, then the associated subject matter information of current label is returned to, if it does not match, return
With failure.
Label information typing specific steps are as follows：
Step 1 is staggered certain angle when each graph scanning using multi-angle graph scanning technology compared with last scan；
Step 2 calculates the angle point of the chaos graph label of different visual angles using Corner Detection Algorithm, and carries out feature
Matching, obtains the matching characteristic point between adjacent view image；
Step 3 calculates the basic square between neighbor image according to computer multiple view geometry principle using 7 algorithms
Battle array；
Step 4 calculates each characteristic point in any image in its neighbor figure using above-mentioned basis matrix
As upper corresponding to polar curve, using local template matching algorithm, calculate to other matched characteristic points present on polar curve；
Step 5 calculates the matching characteristic point parallax of matching image, obtains neighbor image parallactic figure；
Step 6 calculates chaos using principle of parallax by the disparity map of the neighbor image obtained in above-mentioned steps
Characteristic point space coordinate in graphical label, and further obtain the characteristic point relative position information in chaos graph label；
Step 7 extracts the corresponding chaos graph in each visual angle using structure-based image texture characteristic extraction algorithm
The texture information of label midpoint bit distribution；
Step 8 believes the associated subject matter information of label and the feature relative position of the chaos graph label of above-mentioned acquisition
Breath and texture information constitute complex data information, assign id information, and complex data information and id information are stored in back-end data
Library.
The id information of chaos graph label is placed in the form of Quick Response Code at the two-dimension code area of chaos graph label, is convenient for
Identification.
Label information identify specific steps are as follows：
Step 1 is staggered certain angle when each graph scanning using multi-angle graph scanning technology compared with last scan；
Step 2 calculates the angle point of the chaos graph label of different visual angles using Corner Detection Algorithm, and carries out feature
Matching, obtains the matching characteristic point between adjacent view image；Step 3 is counted according to computer multiple view geometry principle using 7
Method calculates the basis matrix between neighbor image；
Step 4 calculates each characteristic point in any image in its neighbor figure using above-mentioned basis matrix
As upper corresponding to polar curve, using local template matching algorithm, calculate to other matched characteristic points present on polar curve；
Step 5 calculates the matching characteristic point parallax of matching image, obtains neighbor image parallactic figure；
Step 6 calculates chaos using principle of parallax by the disparity map of the neighbor image obtained in above-mentioned steps
Characteristic point space coordinate in graphical label, and further obtain the characteristic point relative position information in chaos graph label；
Step 7 extracts the corresponding chaos graph in each visual angle using structure-based image texture characteristic extraction algorithm
The texture information of label midpoint bit distribution；
Step 8 identifies the 2 D code information on outgoing label, reads tag ID；Step 9, using tag ID in database
The label information of typing before middle acquisition, and with the angle point relative position information of chaos graph label achieved above, label line
It manages feature and carries out similarity measurement；
Step 10 is set if the label information similarity that there is chaos image information and above-mentioned acquisition in the database is more than
Determine the label of threshold value, then confirms that association subject matter is certified products, and send back subject matter information associated with label；If instead
It is not present, then confirms that related product is non-certified products.
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
All any modification, equivalent and improvement etc., should all be included in the protection scope of the present invention made by within refreshing and principle.
Claims (2)
1. a kind of label information input system and label Verification system, which is characterized in that the label information input system and mark
Signing verification system includes：
Label information input system extracts the characteristic information of chaos graph label using image recognition technology, then by chaos figure
The ID of shape label, characteristic information and in the information deposit high in the clouds data of the associated subject matter of label；
Label Verification system is calculated the characteristic information of chaos graph label using identical image recognition technology, then utilized
The ID of chaos graph label finds out corresponding label characteristic information in database beyond the clouds, according to two characteristic information similarities, sentences
Whether disconnected to match, if it does, then returning to the associated subject matter information of current label, if it does not match, returning, it fails to match；
The label information input system is as follows：
Step 1 is staggered certain angle when each graph scanning using multi-angle graph scanning technology compared with last scan；
Step 2 calculates the angle point of the chaos graph label of different visual angles using Corner Detection Algorithm, and carries out feature
Match, obtains the matching characteristic point between adjacent view image；
Step 3 calculates the basis matrix between neighbor image according to computer multiple view geometry principle using 7 algorithms；
Step 4, using basis matrix, each characteristic point calculated in any image is corresponding right on neighbor image
Polar curve is calculated using local template matching algorithm to other matched characteristic points present on polar curve；
Step 5 calculates the matching characteristic point parallax of matching image, obtains neighbor image parallactic figure；
Step 6 calculates the spy in chaos graph label using principle of parallax by the disparity map of obtained neighbor image
Space of points coordinate is levied, and further obtains the characteristic point relative position information in chaos graph label；
Step 7 extracts the corresponding chaos graph label in each visual angle using structure-based image texture characteristic extraction algorithm
The texture information of midpoint bit distribution；
Step 8, by the feature relative position information and texture of the associated subject matter information of label and the chaos graph label of acquisition
Information constitutes complex data information, assigns id information, and complex data information and id information are stored in background data base.
2. label information input system as described in claim 1 and label Verification system, which is characterized in that the label Verification
System specific steps are as follows：
Step 1, using multi-angle graph scanning technology, when each graph scanning, is staggered compared with last scan；
Step 2 calculates the angle point of the chaos graph label of different visual angles using Corner Detection Algorithm, and carries out feature
Match, obtains the matching characteristic point between adjacent view image；
Step 3 calculates the basis matrix between neighbor image according to computer multiple view geometry principle using 7 algorithms；
Step 4, using basis matrix, each characteristic point calculated in any image is corresponding right on neighbor image
Polar curve is calculated using local template matching algorithm to other matched characteristic points present on polar curve；
Step 5 calculates the matching characteristic point parallax of matching image, obtains neighbor image parallactic figure；
Step 6 calculates the spy in chaos graph label using principle of parallax by the disparity map of obtained neighbor image
Space of points coordinate is levied, and further obtains the characteristic point relative position information in chaos graph label；
Step 7 extracts the corresponding chaos graph label in each visual angle using structure-based image texture characteristic extraction algorithm
The texture information of midpoint bit distribution；
Step 8 identifies the 2 D code information on outgoing label, reads tag ID；
Step 9, the label information of typing before being obtained in the database using tag ID, and with the chaos graph label of acquisition
Angle point relative position information, label textural characteristics carry out similarity measurement；
Step 10, if exist in the database the angle point relative position information of label information and the chaos graph label of acquisition,
Label textural characteristics similarity is more than the label of given threshold, then confirms that association subject matter is certified products, and send back and label phase
Associated subject matter information；If instead being not present, then confirm that related product is non-certified products；
The method for anti-counterfeit based on chaos graph label includes：
The characteristic information that chaos graph label is extracted first with image recognition technology believes the ID of chaos graph label, feature
It ceases and is stored in the data of high in the clouds with the information of the associated subject matter of label；
Secondly the characteristic information that chaos graph label is calculated using identical image recognition technology, utilizes chaos graph label
ID finds out corresponding label characteristic information in database beyond the clouds；
Finally according to two characteristic information similarities, judge whether to match, if it does, then returning to the associated target of current label
Object information, if it does not match, returning, it fails to match.
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| CN201510349037.XA CN105023163B (en) | 2015-06-23 | 2015-06-23 | A kind of anti-counterfeiting system and method based on chaos graph label |
| PCT/CN2015/086300 WO2016206173A1 (en) | 2015-06-23 | 2015-08-06 | Chaotic graphic tag-based anti-counterfeit system and method |
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| CN201510349037.XA CN105023163B (en) | 2015-06-23 | 2015-06-23 | A kind of anti-counterfeiting system and method based on chaos graph label |
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| CN106960351A (en) * | 2016-01-11 | 2017-07-18 | 深圳市安普盛科技有限公司 | A kind of commodity counterfeit prevention, verification method and system and bar code scanner |
| CN106203427A (en) * | 2016-07-06 | 2016-12-07 | 四川大学 | A kind of medicated cigarette genuine-fake identification system based on outer package feature |
| CN106485256A (en) * | 2016-10-10 | 2017-03-08 | 宋育锋 | Double label relative position information construction methods based on SIFT feature point |
| CN107633048B (en) * | 2017-09-15 | 2021-02-26 | 国网重庆市电力公司电力科学研究院 | Image annotation identification method and system |
| CN109754243A (en) * | 2017-11-01 | 2019-05-14 | 杭州沃朴物联科技有限公司 | The anti-system and method of stealthily substituting of gathering two dimensional code based on anti-counterfeiting mark |
| CN108373001A (en) * | 2018-02-01 | 2018-08-07 | 王学斌 | A kind of intelligent industrial robot automation warehousing system |
| CN109767826A (en) * | 2019-01-21 | 2019-05-17 | 河西学院 | A kind of acquisition methods and medical photography imaging system of medical treatment photographed data |
| CN110222602A (en) * | 2019-05-23 | 2019-09-10 | 艾科芯（深圳）智能科技有限公司 | Antiforge recognizing method, system, device end and computer readable storage medium |
| CN110533704B (en) * | 2019-07-22 | 2022-11-11 | 杭州沃朴物联科技有限公司 | Method, device, equipment and medium for identifying and verifying ink label |
| CN110428027B (en) * | 2019-07-22 | 2023-06-23 | 杭州沃朴物联科技有限公司 | Identification and counterfeit detection method, device, equipment and medium based on LCD (liquid crystal display) anti-counterfeit label |
| CN110443623A (en) * | 2019-07-22 | 2019-11-12 | 杭州沃朴物联科技有限公司 | Fake method, device, equipment and medium are tested in identification for antifalsification label |
| CN112598008B (en) * | 2020-12-25 | 2021-12-03 | 上海大学 | Thin film pattern database establishing and classification identification method for non-duplicable anti-counterfeit label |
| CN113935343B (en) * | 2021-10-12 | 2022-06-21 | 南通大学 | Commodity anti-counterfeiting code generation method based on character string-to-picture encryption |
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| WO2016206173A1 (en) | 2016-12-29 |
| CN105023163A (en) | 2015-11-04 |
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