CN1564148A - Micro-image anti-fraud method for objects surface - Google Patents
Micro-image anti-fraud method for objects surface Download PDFInfo
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- CN1564148A CN1564148A CN 200410022300 CN200410022300A CN1564148A CN 1564148 A CN1564148 A CN 1564148A CN 200410022300 CN200410022300 CN 200410022300 CN 200410022300 A CN200410022300 A CN 200410022300A CN 1564148 A CN1564148 A CN 1564148A
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Abstract
The method includes step: determining region for guarding against false, taking amplified image of the region, sanding digital image to computer; processing the digital image, picking up basic components of characteristic data; encoding compressing the picked basic components together with other tested information about the goods, storing encoded and compressed data to computer. Procedure of authenticating a goods includes steps: picking up characteristic data from goods to be tested; obtaining characteristic data from networked computer; comparing the picked characteristic data with characteristic data from computer so as to determine true or false of the goods. Microscopic characteristic of each goods is unique, and it cannot be copied. Thus, the method is reliable. Features are no any damage to goods to be tested so as to be suitable for cultural relics, paintings etc.
Description
(1) technical field
The present invention relates to field of anti-counterfeit technology, be specifically related to a kind of body surface micro image method for anti-counterfeit.
(2) technical background
Present method for anti-counterfeit is multifarious, as printed images, fluorescence labelling, heat-sensitive variable colour figure etc.But generally by imitated, reliability is lower easily for the mark that with the naked eye can discern.
Use the required technology of sign of laser hologram image higher, make the micropore of stochastic distribution or pit has more uniqueness as anti-counterfeiting information characteristics.Though it is imitated that this class sign is difficult for, because of sign and object are integrated by stickup, just separated unavoidably, the fake producer may be recycled and reused for true sign on the fakement again, makes it be difficult for distinguishing.Therefore this class method for anti-counterfeit is still leaky.
On bill, directly print critical data ciphertext through encryption, increased reliability really, but encryption method has just had no anti-fake effect in case reveal.
Sign can not be printed or stick on to historical relics such as famous painting thereon, and the evaluation of its genuine piece also is a difficult problem that always exists.
(3) summary of the invention
The objective of the invention is to design a kind of body surface micro image that utilizes and carry out false proof method, can't copy, guarantee reliable.
The object of various materials, as paper commonly used, metal, plastics etc., even production environment is identical, fiber shape and distribution in its surface microscopic image, rough pattern size and each the tool feature always that distributes.The present invention utilizes the micro image of body surface point as its anti-counterfeiting mark.
Body surface micro image method for anti-counterfeit of the present invention comprises the steps:
1. be identified for false proof specific region for same class article;
2. by the specific region macrophotography of electric charge coupling (being CCD) opto-electronic conversion photomicrographic apparatus, and be converted to digital signal, digitized image is sent into computing machine these article;
3. computing machine is handled the gained picture signal, extracts image microscopic feature primitive data, and characteristics of image primitive digitalized data is encoded with other checking information of article deposits computing machine in;
4. by above-mentioned 2., 3. step is extracted the micro image feature digitalized data of the specific region of article surface to be checked;
5. obtain the digitalized data of micro image feature of the article of former storage by networking;
6. relatively the two judges the true and false with different to computing machine.
Body surface micro image method for anti-counterfeit of the present invention has utilized the micro image feature of article surface, all is at random uniquenesses for every article this features, can't copy, and guarantees the fully reliable of false proof evaluation.And this kind anti-false sign need not to paste or article are directly handled, and article are had no infringement, is specially adapted to the false proof of historical relic painting and calligraphy, classified papers and articles of price.Need not directly to contact with article during discriminating, also can identify in various occasions repeatedly, identify that equipment needed thereby is simple, it is low that enlargement factor is not more than 200 times cinephotomicrography photoelectric commutator cost, and computer processing all can be stored in the machine.It is quick accurate, simple to operate to identify, is easy to promote the use of.
(4) description of drawings
Fig. 1 is the process flow diagram that this body surface micro image method for anti-counterfeit is implemented;
Fig. 2 chooses micro image storage area synoptic diagram for this body surface micro image method for anti-counterfeit;
The micro image and the former storage area relationship synoptic diagram of picked-up when Fig. 3 is the evaluation of this body surface micro image method for anti-counterfeit;
Fig. 4 is this body surface micro image method for anti-counterfeit positioning radiography aid synoptic diagram.
(5) embodiment
As shown in Figure 1, body surface micro image method for anti-counterfeit of the present invention comprises the steps:
1. determining needs false proof article to be used for false proof specific region; General false proof region area is 0.1～10 square millimeter.
2. macrophotography
By the specific region macrophotography of CCD opto-electronic conversion photomicrographic apparatus to these article, enlargement factor is 30～200 times, and become the analog video electric signal through opto-electronic conversion, and be digital signal through the video collector collection and with analog signal conversion, digitized image is sent into computing machine;
3. Computer Processing
Computing machine is handled the gained picture signal, extracts image microscopic feature primitive data, and characteristics of image primitive data are encoded with other checking information of article deposits computing machine in;
The a computing machine carries out gray processing to the gained view data to be handled, and makes it be converted to the gray level image that only contains 255 rank monochrome informations at most;
B makes the image border sharpening, strengthens characteristics of image, and this is a conventional treatment method, for example uses Gauss's smoothing filter and Laplce's sharpening wave filter with adaptive smooth algorithm and Laplce's algorithm sharpening image border;
C extracts image microscopic feature primitive data, and this is a conventional treatment method, for example uses broad sense Hough (Hough) transform method to extract the characteristics of image primitive, as image microscopic feature primitive flag data, and the reference characteristic sign of identification usefulness during promptly as evaluation; As shown in Figure 2, the gained image is accepted or rejected, kept core M, its area is about 5%～100% of institute's pickup image total area;
D needs other macroscopic information of false proof article to carry out digitized processing becomes coding, as information or information such as arrangement sequence number and micro image production method such as goods categories, ages, this type of information code conversion is that bar code or series number are printed on the false proof article of need or on its appended file;
E merges article microcosmic and macroscopical encoding flag of c, d gained as the article identification characteristic, and compression deposits the anti-counterfeiting information database in, and this database is the network database system of sandwich construction.
4. article storage data to be checked are obtained in networking
According on the article to be checked or bar code or series number on its appended file, obtain the micro image anti-counterfeiting information by networking, as: position, false proof specific region and information such as enlargement factor, computer processing procedure, and the article identification characteristic of former storage, comprise the data of micro image feature and macrofeature;
5. article characteristics to be checked is extracted
By above-mentioned 2., 3. step is extracted the micro image characteristic indication data of the specific region of article surface to be checked; By avoiding being caused the difference of gained micro image because of getting the specific region time error, during evaluation taking the photograph zone is not is not accepted or rejected, perhaps She Qu region area is greater than 2～30 times of the micro-image region areas of former storage.As shown in Figure 3, the area that is absorbed guarantees that greater than former storage area M M is included in institute and takes the photograph in the image.
6. relatively the two judges the true and false with different to computing machine.
This is a conventional treatment method, and for example computing machine is determined genetic algebra and variation number percent with genetic algorithm, finds the solution the ideal adaptation degree of images of items micro image feature to be checked and stored data with the genetic search algorithm.When two groups of data characteristics matching rates greater than 90% the time, think coupling fully to be genuine piece that computing machine sends into function signal.And matching rate was thought not match less than 90% o'clock, was fakement, and computing machine sends alerting signal.
Embodiment 1
The real and fake discrimination of peace official's cow-bezoar ball
Final step after the pill Production and Packaging are finished is the false proof micro image of storage.With 10 square millimeters in the packing box trade mark upper right corner is false proof zone.Can help location fast by the employing instrument.Orientation tool as shown in Figure 4 has photography hole 2 on the main supporting plate 1, on 1 liang of adjacent side of main supporting plate perpendicular baffle plate 3 is arranged, and when packing box was placed on that two sides are close to baffle plate 3 on the main supporting plate 1, false proof specific region just was on the photography hole 2, makes things convenient for positioning radiography.With CCD opto-electronic conversion photomicrographic apparatus to the specific region macrophotography, enlargement factor is 30 times, and become video electrical signal through opto-electronic conversion, through the video collector collection and with analog signal conversion is digital signal, digitized image is sent into the check special purpose computer, handle and edge sharpening through gray processing, 5% area of getting institute pickup image center as shown in Figure 2 extracts characteristics of image primitive digital information, compresses with bar code informations such as the date of manufacture lot number merging in the pharmaceutical production to deposit the check computing machine in.
During evaluation, networking promptly obtains the false proof micro image information of this medicine storage to be checked according to bar code.10 square millimeters of the specific regions of medicine box by Computer Processing behind 30 times of macrophotographies, are obtained micro image primitive numerical information.Because of the micro image primitive of storage is taken from center 5% area in specific false proof zone, admittedly even when identifying during with former the storage location in false proof zone variant slightly, the micro image primitive of depositing still in the image that is absorbed.Computing machine is found the solution the ideal adaptation degree of medicine box image micro image feature to be checked and stored data with the genetic search algorithm, when two groups of data characteristics matching rates are genuine piece greater than 90% the time.
The false proof evaluation of famous painting
Famous painting after expert appraisal amplifies 200 times of photographies for 0.1 square millimeter in the specific region of getting of picture, and with the digitizing micro image information stores after the Computer Processing.Transfer to printing bar code such as computing machine network address of the anti-counterfeiting information of evaluation date, connoisseur and the storage of this picture for information about on the assay certificate of this picture simultaneously.
Learn the computing machine network address of the anti-counterfeiting information of storage during evaluation according to the bar code of this picture, networking obtains position, false proof specific region and information such as enlargement factor, computer processing procedure, with false proof zone is that 200 times of photographies of 2 square millimeters of areas amplifications are got at the center, and digitizing afterwards gets the micro image characteristic.Because of the picked-up area greater than when storage area, although deviation is arranged slightly, the micro image primitive of storage is still in the image that is absorbed.Computing machine and the former data of networking gained relatively, when two groups of data characteristics matching rates are genuine piece greater than 90% the time.
The false proof evaluation of certificate
After certificate making is finished, get 5 square millimeters of specific regions and amplify 120 times of photographies, after the Computer Processing, 30% area of getting institute pickup image center extracts the storage of characteristics of image primitive digital information.And with the certificate unit of issuing, time and sequence number and micro image make information digitalization with printing bar code on certificate.
Obtain the micro image data that micro image is made information and storage according to bar code information during evaluation.120 times of photographies are amplified in 5 square millimeters of specific regions, handle the back and extract the micro image primitive, relatively differentiate with the storage data.
Claims (6)
1 one kinds of body surface micro image method for anti-counterfeit is characterized by and comprise the steps:
1. determine that article are used for false proof specific region;
2. macrophotography, enlargement factor is 30～200 times, and becomes the analog video electric signal through opto-electronic conversion, is digital signal through the video collector collection and with analog signal conversion, and digitized image is sent into computing machine;
3. Computer Processing comprises that gray processing is handled, the image border sharpening, extracts the characteristics of image primitive, and as image microscopic feature primitive flag data, compression deposits Computer Database in;
4. article storage data to be checked are obtained in networking;
5. by above-mentioned 2., 3. step is extracted the micro image characteristic indication data of the specific region of article surface to be checked;
6. relatively the two judges the true and false with different to computing machine.
2 body surface micro image method for anti-counterfeit according to claim 1 is characterized by:
False proof region area is 0.1～1 0 square millimeter.
3 body surface micro image method for anti-counterfeit according to claim 1 and 2 is characterized by:
The gained image is accepted or rejected, and the reserve part area is about 5%～100% of institute's pickup image total area.
4 body surface micro image method for anti-counterfeit according to claim 1 and 2 is characterized by:
Other macroscopic information of article to be checked carries out digitized processing, as information or information such as arrangement sequence number bar code and micro image production method such as goods categories, ages; Article micro image characteristic indication data and macroscopical encoding flag merge as the article identification characteristic, and compression deposits Computer Database in.
5 body surface micro image method for anti-counterfeit according to claim 1 and 2 is characterized by:
The ideal adaptation degree of computing machine images of items micro image more to be checked feature and stored data, when two groups of data characteristics matching rates greater than 90% the time, think coupling fully to be genuine piece; Matching rate was thought not match less than 90% o'clock, is fakement.
6 body surface micro image method for anti-counterfeit according to claim 1 and 2 is characterized by:
During evaluation taking the photograph zone is not is not accepted or rejected, perhaps She Qu region area is greater than 2～30 times of the micro-image region areas of former storage.
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| CN 200410022300 CN1564148A (en) | 2004-04-09 | 2004-04-09 | Micro-image anti-fraud method for objects surface |
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| CN100405405C (en) * | 2005-12-29 | 2008-07-23 | 兆日科技（深圳）有限公司 | Fiber image antifake method |
| CN100423042C (en) * | 2006-01-12 | 2008-10-01 | 周用金 | Painting and calligraphy works random colour line coincidance antifake identification method |
| CN1807127B (en) * | 2006-01-12 | 2010-05-12 | 周用金 | False proof authentication method for calligraphy and painting with concealed high intensity fiber thread on fixed point |
| CN101872417A (en) * | 2010-05-27 | 2010-10-27 | 王键辉 | Method and management system for identifying products by particle information |
| CN102073865A (en) * | 2010-12-24 | 2011-05-25 | 兆日科技（深圳）有限公司 | Anti-counterfeiting method and system using autologous fiber textures of paper |
| CN102214305A (en) * | 2011-04-08 | 2011-10-12 | 大连理工大学 | Method for taking evidence for source of printing paper sheet by using grain characteristic |
| CN101582162B (en) * | 2008-05-14 | 2012-01-25 | 上海锦渡信息科技有限公司 | Art identifying method based on texture analysis |
| CN102375975A (en) * | 2010-08-18 | 2012-03-14 | 瑞萨电子株式会社 | Authentication device and authentication method |
| CN103227712A (en) * | 2013-03-28 | 2013-07-31 | 深圳市捷龙标牌有限公司 | Colorless or colored micro code changing technology system |
| CN103310526A (en) * | 2012-03-12 | 2013-09-18 | 王洪群 | Device for identification and anti-counterfeiting distinguishment of common paper and application method of device |
| CN105264578A (en) * | 2013-05-10 | 2016-01-20 | 伊诺维亚薄膜有限公司 | Authentication apparatus and method |
| CN106251340A (en) * | 2016-07-24 | 2016-12-21 | 朱建宗 | A kind of feature pattern data calculate the method for comparison micro image |
| WO2017148420A1 (en) * | 2016-03-02 | 2017-09-08 | 北京柯斯元科技有限公司 | Random texture-based anti-counterfeiting method, anti-counterfeiting identification system, anti-counterfeiting system, and anti-counterfeiting product |
| CN108596312A (en) * | 2018-07-09 | 2018-09-28 | 北京德隐艺术品投资管理有限公司 | A kind of mark label and its realize that lockhole knows method for distinguishing using the mark label |
| CN109241812A (en) * | 2017-07-10 | 2019-01-18 | 上海爱观视觉科技有限公司 | A kind of original identification device and recognition methods |
| CN109740708A (en) * | 2019-01-04 | 2019-05-10 | 厦门迅为联创信息技术有限公司 | Method, system and the anti-counterfeit certificate of the anti-fake examination of painting and calligraphy pieces based on data-link |
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| CN100405405C (en) * | 2005-12-29 | 2008-07-23 | 兆日科技（深圳）有限公司 | Fiber image antifake method |
| CN100423042C (en) * | 2006-01-12 | 2008-10-01 | 周用金 | Painting and calligraphy works random colour line coincidance antifake identification method |
| CN1807127B (en) * | 2006-01-12 | 2010-05-12 | 周用金 | False proof authentication method for calligraphy and painting with concealed high intensity fiber thread on fixed point |
| CN101582162B (en) * | 2008-05-14 | 2012-01-25 | 上海锦渡信息科技有限公司 | Art identifying method based on texture analysis |
| CN101872417A (en) * | 2010-05-27 | 2010-10-27 | 王键辉 | Method and management system for identifying products by particle information |
| CN102375975A (en) * | 2010-08-18 | 2012-03-14 | 瑞萨电子株式会社 | Authentication device and authentication method |
| CN102073865A (en) * | 2010-12-24 | 2011-05-25 | 兆日科技（深圳）有限公司 | Anti-counterfeiting method and system using autologous fiber textures of paper |
| CN102214305A (en) * | 2011-04-08 | 2011-10-12 | 大连理工大学 | Method for taking evidence for source of printing paper sheet by using grain characteristic |
| CN103310526B (en) * | 2012-03-12 | 2015-11-25 | 王洪群 | The device of a kind of plain paper identification and false proof discriminating and using method thereof |
| CN103310526A (en) * | 2012-03-12 | 2013-09-18 | 王洪群 | Device for identification and anti-counterfeiting distinguishment of common paper and application method of device |
| CN103227712B (en) * | 2013-03-28 | 2018-02-23 | 深圳市捷龙标签科技有限公司 | The micro- time-varying code technological system of colorless or colored |
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| CN111210428A (en) * | 2020-02-28 | 2020-05-29 | 涂道华 | System and method for identifying oxidized microscopic traces of cultural relics and artworks |
| CN111563753A (en) * | 2020-04-29 | 2020-08-21 | 程烨 | Query method and device for product tracing information, server and storage medium |
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