CN108985799B - Product fidelity method based on random trace characteristics - Google Patents
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Abstract
The invention discloses a product fidelity method based on random trace characteristics, which is characterized by comprising the following steps of: 1) randomly generating a non-repeating random trace generation code, wherein the random trace generation code comprises random trace characteristic data corresponding to random trace characteristics; 2) generating a random trace feature on the product according to the random trace generation code, wherein the random trace feature corresponds to the random trace feature data; 3) giving a unique identification code to the product, and associating and storing the unique identification code and the random trace generation code; 4) when the product needs to be subjected to fidelity verification, the random trace generation code is called through the unique identification code, the random trace characteristics corresponding to the random trace generation code are reproduced, and the authenticity of the product is verified through one-to-one comparison between the reproduced random trace characteristics and the random trace characteristics on the product.
Description
Technical Field
The invention relates to the technical field of product fidelity, in particular to a product fidelity method based on random trace characteristics.
Background
The fidelity technology is a technology that traces generated on products or product materials in product processing due to random factors are utilized, unique trace feature combinations are extracted from each product to form unique feature groups of the product different from other products, the feature groups of the traces are subjected to feature confirmation one by one in inquiry, and if the correspondence is completely correct, the product can be confirmed to be a genuine product, and the technology is called as the fidelity technology.
The fidelity technology is different from most of the existing anti-counterfeiting technologies, most of the existing anti-counterfeiting technologies utilize a standardized anti-counterfeiting label to be added to the consistency part of a standardized product, only the uniqueness of the anti-counterfeiting label can be reflected, and the uniqueness of the product cannot be determined, so that most of the anti-counterfeiting technologies are anti-counterfeiting for the anti-counterfeiting label.
The trace extracted in the fidelity technology is randomly generated in production, so that the possibility of counterfeiting can be basically eliminated, the fidelity purpose of materials or products can be more effectively realized, and the anti-counterfeiting purpose is also realized.
However, there are currently a number of technical drawbacks to fidelity techniques that take advantage of the random marks that naturally occur in production. Firstly, the random marks naturally generated in the production of the product are generally limited in number, so that the mark feature combination number is difficult to meet the requirement of being more than or equal to the number of the large-batch products, and the purpose of performing uniqueness fidelity on any batch of products cannot be met. Secondly, random traces naturally generated in production are uncertain in position and unstable in trace form, and post-collection, feature extraction, trace image or video storage, trace reproduction, trace identification and the like are required to be carried out on the random traces of each product, so that the problems of large trace feature data collection workload, difficulty in selecting unique feature groups, huge trace image or video storage amount, large trace reproduction difficulty, difficulty in trace identification, low accuracy and the like are caused.
Aiming at the technical problems, the invention provides a product fidelity method for actively generating random marks with encodable characteristics on a product, wherein the random marks are formed on the product through a mark generation code generated randomly, and fidelity series operations such as generation, design, storage, reproduction, identification and the like of the random marks of the product are performed by combining a unique identification code corresponding to the product.
The invention proposes to form random marks on products by means of a mark generating code, which is coded data on mark features, including combined data of the mark features such as position, shape, size, direction, color, etc. of the mark, thus easily covering a huge number of products, each having a different combination of mark features. The method has the advantages of small memory space, easy correspondence with the unique identification code of the product, easy hierarchical identification and the like, is convenient for realizing the uniqueness of the trace characteristics, and has high safety factor.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a product fidelity method based on random trace characteristics, in which a random trace is actively formed on a product through a randomly generated trace generation code, and the product is subjected to fidelity by combining with a unique identification code corresponding to the product, so that the product has many types of random trace characteristics, is not repeated, facilitates realization of uniqueness of the trace characteristics, and has a high safety factor.
According to one aspect of the invention, a product fidelity method based on random trace characteristics is provided, which is characterized by comprising the following steps:
1) randomly generating a non-repeating random trace generation code, wherein the random trace generation code comprises random trace characteristic data corresponding to random trace characteristics;
2) generating a random trace feature on the product according to the random trace generation code, wherein the random trace feature corresponds to the random trace feature data;
3) giving a unique identification code to the product, and associating and storing the unique identification code and the random trace generation code;
4) when the product needs to be subjected to fidelity verification, the random trace generation code is called through the unique identification code, the random trace characteristics corresponding to the random trace generation code are reproduced, and the authenticity of the product is verified through one-to-one comparison between the reproduced random trace characteristics and the random trace characteristics on the product.
Preferably, the step 1 comprises: setting a random trace feature set satisfying the batch quantity of the product, wherein the random trace feature set is composed of combinations of the random trace features, wherein the number of the combinations of the random trace features is greater than or equal to the batch quantity of the product; and randomly generating a non-repeating combination of random trace features from the random trace feature set, and encoding the combination to obtain random trace feature data, thereby generating the random trace generation code.
Preferably, the random trace features comprise random trace locations and random trace identifications; more preferably, the random trace feature further comprises a random trace generation area in the random trace location.
Preferably, the step 2 includes generating a random trace identifier on a random trace generation area and a corresponding random trace position of the product according to the random trace generation code.
Preferably, said step 3 comprises storing said unique identification code and said random trace-generating code associated therewith in a product fidelity database.
In some embodiments, the product fidelity database also includes other product-related data including product information such as the name of the product, manufacturer, plant, line, and/or lot.
Preferably, the random trace marker is selected from at least one of a point, a line, a two-dimensional shape, a cartoon shape, and a character.
In some embodiments, said reproducing in said step 4 a random trace feature corresponding thereto comprises: and (3) reproducing corresponding random trace characteristics on a virtual two-dimensional or three-dimensional product graph of the computer.
Preferably, the step of reproducing the corresponding random trace feature on the computer virtual two-dimensional or three-dimensional product graphic comprises: and displaying corresponding random trace marks on corresponding random trace positions and random trace generation areas of the product graphs.
In some embodiments, the step 4 comprises: when fidelity verification is carried out, the unique identification code is requested to be inquired in a product fidelity database, if the unique identification code is inquired, an inquiry result is returned, and the inquiry result at least comprises product information and random trace characteristic data; creating a three-dimensional model of the product according to the product information; according to the random trace feature data, performing random trace feature mapping on the three-dimensional model; the reproduction of the random trace features is completed through a three-dimensional scene, and the positions of the random trace features are prompted; and verifying the authenticity of the product by comparing the random trace characteristics reproduced on the three-dimensional model with the random trace characteristics on the product one by one.
According to a second aspect of the invention, a product fidelity database is provided, which is used in the product fidelity method based on the random trace characteristics, and the product fidelity database comprises a unique identification code and random trace characteristic data which are in one-to-one correspondence with the product.
According to a third aspect of the invention, a method of generating random mark features on a product is proposed, comprising the steps of:
constructing a product fidelity database, wherein the product fidelity database comprises unique identification codes and random trace characteristic data which are in one-to-one correspondence with products;
acquiring the random trace characteristic data through the unique identification code; and
and generating random trace features on the product according to the random trace feature data, wherein the random trace features correspond to the random trace feature data.
The invention has the beneficial effects that:
the invention can obtain the non-repeated random trace generation code corresponding to the unique identification code of the product, can realize the product fidelity based on the random trace characteristics, has multiple levels and types of the random trace characteristics, can ensure no repetition, and has uniqueness and high safety factor.
The invention stores the random trace characteristic data in a mode of coding the random trace characteristics to form the random trace generation code, can realize the fidelity of products without adopting the modes of images including images, videos and the like, greatly saves the storage space, is convenient for data transmission and improves the transmission efficiency of data.
The invention establishes the two-dimensional or three-dimensional computer virtual model of the product, and graphically reproduces the random trace characteristics on the virtual model in ways of chartlet and the like, so that the fidelity verification process is simpler and more intuitive, and a user can conveniently check the authenticity of the actual product.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating one embodiment of a product fidelity method of the present invention;
FIG. 2 is a schematic diagram of one embodiment of a method of encoding a random trace-generating code of the present invention;
FIG. 3 is a schematic diagram of random trace feature data and random trace features of the present invention;
FIG. 4 is a schematic representation of another random trace feature data and corresponding random trace features of the present invention;
FIG. 5 is a schematic diagram for one embodiment of step S102 of FIG. 1, in accordance with the present invention;
FIG. 6 is a schematic diagram for one embodiment of step S103 of FIG. 1, in accordance with the present invention;
FIG. 7 is a schematic diagram of one embodiment of a product fidelity database of the present invention;
FIG. 8 is a schematic diagram illustrating one embodiment of step S104 of FIG. 1.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The invention provides a product fidelity method for actively generating random marks with encodable characteristics on a product.
Referring to fig. 1, fig. 1 is a schematic flow diagram of one embodiment of a product fidelity method of the present invention. It should be noted that the method of the present invention is not limited to the flow sequence shown in fig. 1 if the results are substantially the same.
As shown in fig. 1, the method comprises the steps of:
s101: and randomly generating a non-repeating random trace generation code, wherein the random trace generation code comprises random trace characteristic data corresponding to random trace characteristics.
The random trace generation code is random trace feature data obtained by encoding all random trace features on a product. The random trace features may generally include the location, area, shape, direction, and/or color levels of the random trace identifiers, and the specific feature levels may be selected according to the required combination variation number to meet the requirement that the combination number of the random trace features can be greater than or equal to the batch number of the products to be fidelity.
In some embodiments, the random mark features can include random mark locations and random mark identifications, wherein a random mark location refers to a location on the product at which a random mark identification is generated. In one embodiment, the random trace features may include random trace locations, random trace generation areas, and random trace identifications.
The random trace marks may be points, lines, two-dimensional shapes, cartoon images, characters, etc., and may also have additional features such as colors, directions, etc., and the present invention is not limited thereto.
FIG. 2 shows a method for encoding a random trace generation code, including setting levels of random trace features and the number of features of each level according to the number of batches of products requiring fidelity, so that the number of combined variations of the random trace features can be greater than or equal to the number of batches of products; the combination of all possible random trace features is encoded to form a set of random trace generation codes.
As shown in fig. 2, the random trace feature includes three levels, namely a random trace location, a random trace generation area, and a random trace identification. The random trace positions, the random trace generation areas and the random trace marks are not limited, as long as the combined change quantity of the random trace positions, the random trace generation areas and the random trace marks is larger than or equal to the batch quantity of the fidelity products. As an example, to form the random trace generation code, the random trace location, the random trace generation area, the random trace identification may be numbered. The numbering is carried out in groups, as shown in fig. 2, three groups of numbers are grouped, and finally, a unique number is arranged at each random trace position, a unique number is arranged in each random trace generation area, and a unique number is arranged in each random trace mark. Numbering may be done in numerical increments for ease of management.
Thus, each random trace identification may be represented by three numbers, which may be recorded using a three-dimensional array, e.g., [1,2,3], [1,4,9], as shown in FIG. 3. For example, in the random trace feature array [1,2,3], 1 represents a position code, [2] represents a random trace generation area code, and [3] represents a random trace identification code. Those skilled in the art can select a suitable encoding rule for a specific situation, and the present invention is not limited thereto.
Each three-dimensional array represents a random trace-identification record, and a random trace-generation code may comprise a plurality of random trace-identification records. By the method, the random trace characteristics on each product can be coded through the plurality of three-dimensional arrays, and a unique corresponding random trace generation code is obtained. For example, a random trace generation code may include random trace feature data as shown in fig. 3 and 4.
S102: and generating a random trace feature on the product according to the random trace generation code, wherein the random trace feature corresponds to the random trace feature data.
In one embodiment, after a non-repeating random trace generation code is obtained, random trace feature data, that is, a group of codes composed of a plurality of three-dimensional arrays, can be obtained through the random trace generation code, and the represented random trace feature can be analyzed according to a coding rule.
The random mark can be generated on the random mark position and the generation area by adopting methods such as spraying and/or indentation and/or pasting according to the data obtained by analyzing the random mark generation code. The invention is not limited with respect to the particular method of processing that produces random marks on the product.
FIG. 5 shows a schematic diagram of one embodiment of the present invention showing the process of generating random trace features on a product from a random trace generation code as shown in FIG. 3. Firstly, obtaining a non-repetitive random trace generation code, such as [1,4,9], analyzing the generation code to determine random trace characteristic data; and secondly, generating a No. 9 random trace mark in the No. 4 area of the No. 1 position on the product by spraying, sticking, stamping and the like.
S103: and giving a unique identification code to the product, and associating and storing the unique identification code and the random trace generation code.
In one embodiment, a unique identification code is generated for each product for use in associating random trace generation codes and/or random trace feature data for the product.
As shown in fig. 6, the random trace generation code shown in fig. 3 is associated with the unique identification code to obtain a piece of random trace feature data corresponding to the product. For example, the unique identification code may be selected from at least one of a two-dimensional code, a barcode, and a character code.
Further, the unique identification code and the random trace-generating code associated therewith may be stored to a product fidelity database. The product fidelity database may be located on a server. The product fidelity database also includes other product-related data including the name of the product, manufacturer, plant, production line, and/or lot, etc. FIG. 7 illustrates one embodiment of the basic structure of a product fidelity database.
S104: when the product needs to be subjected to fidelity verification, the random trace generation code is called through the unique identification code, the random trace characteristics corresponding to the random trace generation code are reproduced, and the authenticity of the product is verified through one-to-one comparison between the reproduced random trace characteristics and the random trace characteristics on the product.
In one embodiment, a unique identification number of a product can be obtained or a unique code of the product can be input by scanning a bar code or a two-dimensional code, and a random trace generation code or product trace characteristic data can be obtained in a product fidelity database by taking the unique identification number as a query condition. If the random trace generation code or the product trace feature data is not acquired, the inquired product is proved to be a non-genuine product, and the photo can be taken and submitted as a fidelity verification result. If the random trace generation code or the product trace feature data is acquired, calling a computer virtual two-dimensional or three-dimensional graph of the product, analyzing the random trace feature data, and reproducing the random trace features represented by the random trace feature data on the virtual graph, for example, displaying corresponding random trace marks on a random trace position and a random trace generation area corresponding to the virtual graph of the product.
And then, the authenticity of the product can be judged and fidelity verification records can be submitted by comparing the actual trace characteristics of the real product with the random trace characteristics displayed on the virtual graph one by one. If the actual product has trace characteristics consistent with all the repeated random trace characteristics, submitting fidelity verification records of the actual product as a genuine product, and if the trace characteristics on the actual product are different from the repeated random trace data, submitting the fidelity verification records of the actual product as a non-genuine product.
FIG. 8 illustrates a complete flow diagram of one embodiment of a fidelity verification process. As shown, when the user performs fidelity verification, the user may request to query the product fidelity database for the unique identification code, and if the unique identification code is not queried, a query result of a non-genuine product is returned, for example, displaying "no such product". If the unique identification code is inquired, returning an inquiry result, wherein the inquiry result at least comprises product information and random trace characteristic data; creating a three-dimensional model of the product according to the product information; according to the random trace feature data, random trace feature mapping is carried out on the three-dimensional model; the reproduction of the random trace features is completed through a three-dimensional scene, and the positions of the random trace features are prompted; and the user verifies the authenticity of the product by comparing the random trace characteristics reproduced on the three-dimensional model with the random trace characteristics on the product one by one.
According to the description, the invention can obtain the non-repeated random trace generation code corresponding to the unique identification code of the product, can realize the product fidelity based on the random trace characteristics, has multiple levels and types of the random trace characteristics, can ensure no repetition, and has uniqueness and high safety factor.
The invention stores the random trace characteristic data in a mode of coding the random trace characteristics to form the random trace generation code, can realize the fidelity of products without adopting the modes of images including images, videos and the like, greatly saves the storage space, is convenient for data transmission and improves the transmission efficiency of data.
The invention establishes the two-dimensional or three-dimensional computer virtual model of the product, and graphically reproduces the random trace characteristics on the virtual model in ways of chartlet and the like, so that the fidelity verification process is simpler and more intuitive, and a user can conveniently check the authenticity of the actual product.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the invention, also features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
While the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. The embodiments of the invention are intended to embrace all such alternatives, modifications and variances that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalents, improvements, and the like that may be made without departing from the spirit or scope of the present invention are intended to be included within the scope of the present invention.
Claims (7)
1. A product fidelity method based on random trace characteristics is characterized by comprising the following steps:
step 1: randomly generating a non-repeating random trace generation code, wherein the random trace generation code comprises random trace characteristic data obtained by coding random trace characteristics according to a preset coding rule;
the random trace feature data corresponds to the random trace features one to one, and the random trace features comprise at least one of the following levels: a random trace location, a random trace generation area in the random trace location, or a random trace identification;
setting levels of random trace features and the feature quantity of each level according to the batch quantity of products needing fidelity, so that the combined variation quantity of the random trace features is greater than or equal to the batch quantity of the products;
for all possible random trace feature combinations, randomly generating a nonrepeating random trace feature combination from the random trace feature set, and coding the nonrepeating random trace feature combination to obtain random trace feature data so as to generate the random trace generation code;
step 2: analyzing the random trace generation code according to a coding rule, and generating a random trace feature on the product, wherein the random trace feature corresponds to the random trace feature data;
and step 3: giving a unique identification code to the product to associate a random trace generation code and/or random trace feature data of the product, and associating and storing the unique identification code with the random trace generation code;
and 4, step 4: when the product needs to be subjected to fidelity verification, calling the random trace generation code through the unique identification code, reproducing corresponding random trace characteristics on a virtual two-dimensional or three-dimensional product graph of a computer, and verifying the authenticity of the product by comparing the reproduced random trace characteristics with the random trace characteristics on the product one by one; when a user performs fidelity verification, the user requests to inquire the unique identification code in a product fidelity database, if the unique identification code is inquired, an inquiry result is returned, and the inquiry result at least comprises product information and random trace characteristic data;
creating a three-dimensional model of the product according to the product information;
according to the random trace feature data, performing random trace feature mapping on the three-dimensional model;
the reproduction of the random trace features is completed through a three-dimensional scene, and the positions of the random trace features are prompted; and
and the user verifies the authenticity of the product by comparing the random trace characteristics reproduced on the three-dimensional model with the random trace characteristics on the product one by one.
2. The method of claim 1, wherein step 2 comprises generating random trace identifications on corresponding random trace locations or random trace-generating areas of the product based on the random trace-generating codes.
3. The method of claim 1, wherein said step 3 comprises storing said unique identification code and said random trace-generating code associated with said unique identification code in a product fidelity database.
4. The method of claim 3, wherein the product fidelity database further comprises other product-related data, the other product-related data comprising at least one of: name of product, manufacturer, workshop, line or batch.
5. The method of claim 1, wherein the random trace markings are selected from at least one of points, lines, two-dimensional shapes, cartoon shapes, characters.
6. The method of claim 1, wherein the method further comprises:
constructing a product fidelity database, wherein the product fidelity database comprises unique identification codes and random trace characteristic data which are in one-to-one correspondence with products;
acquiring the random trace characteristic data through the unique identification code;
and generating random trace features on the product according to the random trace feature data, wherein the random trace features correspond to the random trace feature data.
7. A product fidelity database for use in the product fidelity method of claim 1, wherein said product fidelity database includes a unique identification code and random trace feature data in a one-to-one correspondence with the product.
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| CN103761657A (en) * | 2014-01-08 | 2014-04-30 | 厦门芯标物联科技有限公司 | Random characteristic information anti-counterfeiting method |
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| CN102184675A (en) * | 2011-05-05 | 2011-09-14 | 江苏中准数据有限公司 | Random characteristic anti-counterfeiting label and preparation method thereof |
| CN103870862A (en) * | 2014-03-03 | 2014-06-18 | 汤永平 | Method for realizing anti-counterfeiting effect by separated graph random combination and realization thereof |
| CN106650868A (en) * | 2016-10-15 | 2017-05-10 | 李秀江 | Visual graphic symbol code authenticity checking method and device |
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