Commodity anti-counterfeiting verification method based on random winding pattern

Abstract

The invention relates to the technical field of commodity anti-counterfeiting, in particular to a commodity anti-counterfeiting verification method based on a random winding pattern, which comprises the following steps of: forming a unique pattern by manually and randomly winding a belt, and realizing one-to-one correspondence between a commodity and the pattern in combination with an image recognition technology. The method comprises the specific steps of belt manufacturing, random winding and fixing, image acquisition and storage and consumer scanning and comparison. According to the method, the anti-counterfeiting pattern which cannot be copied is generated by utilizing random combination of points, lines and surfaces, verification is performed by adopting a feature point matching algorithm, and the data security is enhanced through distributed storage and a block chain technology. The anti-counterfeiting cost can be reduced, the verification convenience and accuracy are improved, and an efficient and reliable technical scheme is provided for commodity anti-counterfeiting.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of commodity anti-counterfeiting, and specifically relates to a commodity anti-counterfeiting verification method based on a random winding pattern. BACKGROUND

[0002] With the increasing demand for commodity anti-counterfeiting, anti-counterfeiting technologies based on complex patterns or codes have gradually become a research hotspot. However, existing anti-counterfeiting technologies still have certain deficiencies in realizing randomness, uniqueness, and consumer verification convenience, and it is difficult to fully meet the demand for high security anti-counterfeiting.

[0003] After searching, a commodity anti-counterfeiting code generation and verification method with a publication number of CN106548353B and a publication date of April 7, 2020 was found. This patent generates an anti-counterfeiting code through multi-level encryption, including double encryption of enterprise keys and production keys, and finally encrypts it in combination with a website key, thereby ensuring the uniqueness and confidentiality of the anti-counterfeiting code. However, this technical solution relies on complex encryption algorithms and digital anti-counterfeiting codes, and the verification process is relatively cumbersome for ordinary consumers and requires high technical support. In addition, since the anti-counterfeiting code is statically generated, once it is copied or forged, the blocking effect on the circulation of counterfeit goods may be limited.

[0004] After searching, a commodity anti-counterfeiting code construction and verification method with a publication number of CN102999771B and a publication date of July 1, 2015 was found. This patent dynamically generates an anti-counterfeiting code using commodity circulation status and path information through a combination of plaintext and hidden codes, realizing multi-role and multi-channel commodity authenticity identification. However, this technical solution has strong dependence on the anti-counterfeiting system, and consumers need to query and verify through a specific platform, which has a high operation threshold. In addition, although dynamic coding increases the difficulty of anti-counterfeiting, the generation and storage process is complex, which may lead to reduced system operation efficiency and increased implementation costs for enterprises.

[0005] The above problems show that existing commodity anti-counterfeiting technologies still have deficiencies in realizing randomness, uniqueness, and consumer verification convenience, especially in preventing counterfeiting and improving consumer experience. Therefore, the present application provides a commodity anti-counterfeiting verification method based on a random winding pattern, which aims to form a unique and non-reproducible pattern by manually winding a ribbon at random, combine image recognition technology of an anti-counterfeiting platform, simplify the consumer verification process, and ensure the uniqueness and non-reproducibility of the anti-counterfeiting pattern, thereby meeting the demand for efficient, low-cost, and easy-to-operate in the modern commodity anti-counterfeiting field. SUMMARY

[0006] The application provides a commodity anti-counterfeiting verification method based on a random winding pattern, aiming to form an uncopyable unique pattern by manually winding a belt randomly, combining image recognition technology of an anti-counterfeiting platform, and simplifying a consumer verification process.

[0007] The technical scheme adopted by the application is as follows:

[0008] A commodity anti-counterfeiting verification method based on a random winding pattern comprises the following steps:

[0009] A belt with point, line and surface patterns is fixed on a tearing-off position of commodity outer packaging by manual random winding, and the removal of the belt is ensured to be a necessary condition for opening the outer packaging.

[0010] An image acquisition device is used to shoot the wound belt, extract a unique pattern formed by recombination of points, lines and surfaces on the belt, and upload the pattern to an anti-counterfeiting platform for storage, and meanwhile, a corresponding relationship between the pattern and the commodity is established.

[0011] After a consumer obtains the commodity, a special scanning tool provided by an anti-counterfeiting system is used to scan the pattern on the belt, and the anti-counterfeiting system compares the scanning result with the pattern stored in the platform.

[0012] When the scanning result is consistent with the stored pattern, the commodity is determined to be a genuine product, otherwise, the commodity is determined to be a fake product.

[0013] As a further description of the above technical scheme, the manufacturing process of the belt comprises the following steps:

[0014] A flexible material is selected as a belt base material, and a point, line and surface pattern is drawn on the surface of the base material, wherein the size of the point, the thickness of the line and the shape of the surface are generated in a random distribution manner.

[0015] The design of the pattern needs to meet the requirements of randomness and uncopyability, and the distribution density of the point, the bending angle of the line and the area change of the surface are controlled to realize the requirements.

[0016] The width and length of the belt are adjusted according to the size of the commodity outer packaging, so that the belt can closely fit the outer packaging and cover the tearing-off position.

[0017] As a further description of the above technical scheme, the fixing method of the belt comprises the following steps:

[0018] One end of the belt is fixed at a starting position of the outer packaging, and is preliminarily fixed by pasting or buckling.

[0019] The belt is wrapped around the outer package in multiple turns through artificial random winding;

[0020] During the winding process, the point, line, and surface patterns on the belt recombine due to random bending and twisting, forming a unique overall pattern;

[0021] After winding is complete, the end of the belt is fixed at the termination position of the outer package, using the same fixing method as the starting position.

[0022] As a further description of the above technical solution, the specific operation of the image acquisition device includes the following steps:

[0023] A high-resolution camera is used to take pictures of the wrapped belt, with the shooting angle perpendicular to the belt surface to reduce the influence of perspective distortion;

[0024] During the shooting process, ensure uniform distribution of light to avoid shadows or reflections that interfere with pattern recognition;

[0025] Through image processing algorithms, the shooting results are preprocessed, including denoising, edge detection, and contrast enhancement, to improve the clarity and recognizability of the pattern;

[0026] The unique pattern formed by the recombination of points, lines, and surfaces on the belt is extracted and converted into a digital image stored in the anti-counterfeiting platform.

[0027] As a further description of the above technical solution, the storage and comparison process of the anti-counterfeiting platform includes the following steps:

[0028] The extracted pattern is stored in association with the unique identification code of the product, ensuring that each product corresponds to a unique pattern;

[0029] The stored pattern is encrypted to prevent unauthorized access or tampering;

[0030] After the consumer scans the pattern on the belt, the anti-counterfeiting system performs a pixel-by-pixel comparison of the scanning results with the stored pattern;

[0031] During the comparison process, a certain error range is allowed to accommodate minor differences that may occur under different shooting conditions.

[0032] As a further description of the above technical solution, the dedicated scanning tool of the anti-counterfeiting system includes the following functional modules:

[0033] Camera module for capturing the pattern on the belt;

[0034] Image processing module for preprocessing and feature extraction of the shooting results;

[0035] A communication module is configured to transmit the extracted pattern to the anti-counterfeiting platform for comparison;

[0036] A result display module is configured to feed back the comparison result to the consumer.

[0037] As a further description of the above technical solution, the comparison algorithm of the anti-counterfeiting system adopts a feature point matching-based technology, which specifically includes the following steps:

[0038] Feature points are extracted from the stored pattern and the scanning result respectively, and the selection of the feature points is based on the distribution density of the points, the bending angle of the lines, and the area change of the faces;

[0039] The similarity between the feature points is calculated, and the Euclidean distance or the cosine similarity is used as the measurement standard;

[0040] When the similarity exceeds a preset threshold, it is determined that the two patterns are consistent, otherwise it is determined that they are inconsistent.

[0041] As a further description of the above technical solution, the security design of the anti-counterfeiting system includes the following measures:

[0042] A distributed storage architecture is adopted to store the pattern data on multiple server nodes, thereby reducing the risk of single-point failure;

[0043] The blockchain technology is introduced to record the binding relationship between the pattern and the commodity, thereby ensuring the data tamper resistance;

[0044] Access permission control is set to allow only authorized users to query or modify the stored pattern data.

[0045] Compared with the prior art, the present application has the following advantages:

[0046] The existing anti-counterfeiting technology relies on complex encryption algorithms or dynamic encoding, which has a high operation threshold and a large implementation cost. The present application generates a unique pattern by manually winding the tape randomly, without the need for additional encryption or computing resources, thereby reducing the implementation cost of enterprises;

[0047] The static anti-counterfeiting code in the existing anti-counterfeiting technology is easy to copy or counterfeit. The pattern formed by random winding in the present application has high randomness and non-replicability, which fundamentally solves the problem of counterfeiting;

[0048] The existing anti-counterfeiting technology requires the consumer to query and verify through a specific platform, which is cumbersome. The present application simplifies the verification process through a special scanning tool, thereby improving the user experience of the consumer;

[0049] The present application combines image recognition technology to realize the automatic collection and comparison of anti-counterfeiting patterns, thereby improving the efficiency and accuracy of anti-counterfeiting verification;

[0050] The application enhances the security and reliability of data by the distributed storage of the anti-fake platform and the blockchain technology, and provides an efficient, low-cost and easy-to-operate solution for the modern commodity anti-fake field. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is a schematic diagram of the random winding of the belt in the application fixed at the unsealing place of the commodity outer package.

[0052] Figure 2 It is a partial enlarged view of the point, line and surface patterns on the surface of the belt.

[0053] Figure 3 It is a schematic diagram of the scene of the image acquisition device shooting the wound belt.

[0054] Figure 4 It is a flowchart of the anti-fake platform storing the binding relationship between the pattern and the unique identification code of the commodity.

[0055] Figure 5 It is an operation schematic diagram of the consumer using a special scanning tool to scan the belt pattern.

[0056] Figure 6 It is a principle diagram of the feature point matching process in the comparison algorithm of the anti-fake system.

[0057] Figure 7 It is a data management schematic diagram of the anti-fake platform adopting a distributed storage architecture.

[0058] Figure 8 It is an application schematic diagram of the blockchain technology in the security design of the anti-fake system.

[0059] The reference signs are as follows: 1, belt; 2, commodity outer package; 3, point pattern; 4, line pattern; 5, surface pattern; 6, image acquisition device; 7, anti-fake platform; 8, scanning tool. DETAILED DESCRIPTION

[0060] The application provides a commodity anti-fake verification method based on a random winding pattern, and the specific implementation manner is described in detail below in combination with the drawings. Figure 1 A schematic diagram of the random winding of the belt 1 fixed at the unsealing place of the commodity outer package 2 is shown, and the winding manner of the belt 1 and the combined state thereof with the outer package 2 are clearly visible. The surface of the belt 1 is designed with a point pattern 3, a line pattern 4 and a surface pattern 5, and the random distribution characteristics and design details of these patterns are shown in Figure 2 The scene of the image acquisition device 6 shooting the wound belt 1 is shown in Figure 3 The requirements for the shooting angle and light distribution are also clearly shown in the figure.

[0061] First, the tape 1 is fixed on the outer packaging 2 of the product by random winding by hand, ensuring that the removal of the tape 1 is the necessary condition for opening the outer packaging 2. One end of the tape 1 is fixed at the starting position of the outer packaging 2, and the initial fixation is achieved by sticking or buckling. Then, the tape 1 is wound around the outer packaging 2 for multiple turns by random winding by hand. During the winding process, the dot pattern 3, line pattern 4 and surface pattern 5 on the tape 1 are recombined due to random bending and twisting, forming a unique overall pattern. After winding is completed, the end of the tape 1 is fixed at the termination position of the outer packaging 2, using the same fixation method as the starting position. This step ensures the close combination of the tape 1 and the outer packaging 2 of the product, and at the same time, the patterns on the tape 1 form a unique and uncopyable uniqueness due to random winding.

[0062] Next, the wrapped tape 1 is photographed using the image acquisition device 6, and the shooting angle should be perpendicular to the surface of the tape 1 to reduce the influence of perspective distortion. During the shooting process, ensure that the light is evenly distributed to avoid shadows or reflections that interfere with pattern recognition. The shooting results are preprocessed by image processing algorithms, including denoising, edge detection and contrast enhancement, to improve the clarity and recognizability of the patterns. The unique pattern formed by the recombination of the dot pattern 3, line pattern 4 and surface pattern 5 on the tape 1 is extracted and converted into a digital image and stored in the anti-counterfeiting platform 7. Figure 4 The flowchart for binding the pattern stored in the anti-counterfeiting platform 7 with the unique identification code of the product describes the process of data storage and encryption. The extracted pattern is stored in association with the unique identification code of the product, ensuring that each product corresponds to a unique pattern. The stored pattern is encrypted to prevent unauthorized access or tampering.

[0063] After the consumer obtains the product, the special scanning tool 8 provided by the anti-counterfeiting system is used to scan the pattern on the tape 1, and the anti-counterfeiting system compares the scanning results with the patterns stored in the anti-counterfeiting platform 7. Figure 5 The operation diagram shows the consumer using the special scanning tool 8 to scan the pattern on the tape 1, and the relative position of the scanning tool 8 and the tape 1 is clearly shown. The scanning tool 8 includes a camera module for capturing the pattern on the tape 1, an image processing module for preprocessing and feature extraction of the shooting results, a communication module for transmitting the extracted pattern to the anti-counterfeiting platform 7 for comparison, and a result display module for feeding back the comparison results to the consumer. The comparison algorithm of the anti-counterfeiting system uses a feature point matching-based technology to extract feature points from the stored pattern and the scanning results, and the selection of feature points is based on the distribution density of the dot pattern 3, the bending angle of the line pattern 4 and the area change of the surface pattern 5. The similarity between the feature points is calculated, and the Euclidean distance or cosine similarity is used as the measurement standard. When the similarity exceeds the preset threshold, it is determined that the two patterns are consistent, otherwise it is determined that they are inconsistent. Figure 6This diagram illustrates the principle of feature point matching in the comparison algorithm of an anti-counterfeiting system, explaining the steps of feature point extraction and similarity calculation.

[0064] The security design of the anti-counterfeiting platform 7 includes a distributed storage architecture and the application of blockchain technology. Figure 7 The diagram illustrates the data management of the anti-counterfeiting platform 7, which utilizes a distributed storage architecture. This architecture distributes pattern data across multiple server nodes, reducing the risk of single points of failure. Figure 8 This diagram illustrates the application of blockchain technology in the security design of an anti-counterfeiting system, depicting the process of recording the binding relationship between patterns and products. Blockchain technology is introduced to record the binding relationship between patterns and products, ensuring the immutability of the data. Access control is implemented, allowing only authorized users to query or modify the stored pattern data.

[0065] In the above embodiments, the manufacturing process of the strap 1 includes selecting a flexible material as the strap substrate, and drawing dot patterns 3, line patterns 4, and surface patterns 5 on the surface of the substrate. The size of the dot patterns 3, the thickness of the line patterns 4, and the shape of the surface patterns 5 are all generated in a random distribution manner. The pattern design meets the requirements of randomness and non-reproducibility, specifically achieved by controlling the distribution density of the dot patterns 3, the bending angle of the line patterns 4, and the area variation of the surface patterns 5. The width and length of the strap 1 are adjusted according to the dimensions of the outer packaging 2 of the product to ensure that the strap 1 can fit tightly to the outer packaging 2 and cover the opening area.

[0066] Throughout the implementation process, the connection between the ribbon 1 and the outer packaging 2 of the product is crucial to the anti-counterfeiting effect. The random winding method of the ribbon 1 makes its pattern highly random and uncopyable, fundamentally solving the counterfeiting problem. The anti-counterfeiting platform 7 enhances data security and reliability through a distributed storage architecture and blockchain technology, providing an efficient, low-cost, and easy-to-operate solution for modern product anti-counterfeiting. The consumer verification process is simplified by a dedicated scanning tool 8, improving the user experience. The introduction of image recognition technology enables automated collection and comparison of anti-counterfeiting patterns, improving the efficiency and accuracy of anti-counterfeiting verification.

[0067] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principle of this invention will be further explained below in conjunction with a specific application scenario.

[0068] On the production line, the operator first fixes one end of the tape 1 to the starting position of the outer package 2 by adhesion. Then, the tape 1 is manually wound around the outer package 2 for multiple turns to ensure the randomness of the pattern. In this process, the point pattern 3, line pattern 4, and surface pattern 5 on the surface of the tape 1 are recombined into a unique overall pattern due to bending and twisting. After winding, the end of the tape 1 is also fixed to the termination position of the outer package 2 by adhesion. The key to this step is that the close combination of the tape 1 and the outer package 2 makes the pattern highly random and uncopyable, fundamentally solving the problem of counterfeiting. Figure 1 As shown, the winding method of the tape 1 and its combined state with the outer package 2 are clearly visible, and Figure 2 The random distribution characteristics of the point pattern 3, line pattern 4, and surface pattern 5 are shown.

[0069] Next, the image acquisition device 6 captures the wrapped tape 1, and the shooting angle needs to be perpendicular to the surface of the tape 1 to reduce the influence of perspective distortion. To ensure the quality of the shot, the ambient light needs to be evenly distributed to avoid shadows or reflections. After shooting, the image processing algorithm preprocesses the shooting results, including denoising, edge detection, and contrast enhancement, to improve the clarity and recognizability of the pattern. The unique pattern formed by the recombination of the point pattern 3, line pattern 4, and surface pattern 5 on the tape 1 is extracted and converted into a digital image and stored in the anti-counterfeiting platform 7. As shown, Figure 3 The requirements for the shooting scene and light distribution are clearly shown. Figure 4 Further describes the process of binding the pattern stored in the anti-counterfeiting platform 7 with the unique identification code of the product, where the pattern is stored after encryption to ensure data security.

[0070] When the product circulates to the consumer, the consumer uses a special scanning tool 8 to scan the pattern on the tape 1. The camera module of the scanning tool 8 captures the pattern on the tape 1, the image processing module preprocesses and extracts features from the shooting results, the communication module transmits the extracted pattern to the anti-counterfeiting platform 7 for comparison, and the result display module feeds back the comparison result to the consumer. As shown, Figure 5 The relative position of the scanning tool 8 and the tape 1 is clearly shown. The comparison algorithm of the anti-counterfeiting system uses a feature point matching-based technique to extract feature points from the stored pattern and the scanning results. The selection of feature points is based on the distribution density of the point pattern 3, the bending angle of the line pattern 4, and the area change of the surface pattern 5. When calculating the similarity between feature points, the Euclidean distance or cosine similarity is used as the measurement standard. When the similarity exceeds the preset threshold, it is determined that the two patterns are consistent, otherwise it is determined that they are inconsistent. Figure 6 The steps of feature point extraction and similarity calculation are described in detail.

[0071] The security design of the anti-counterfeiting platform 7 is achieved through a distributed storage architecture and blockchain technology. For example... Figure 7 As shown, the distributed storage architecture disperses pattern data across multiple server nodes, reducing the risk of single point of failure. Figure 8 The application process of blockchain technology is described, recording the binding relationship between patterns and products to ensure the immutability of data. Furthermore, access control is implemented, allowing only authorized users to query or modify stored pattern data, further enhancing system security.

[0072] In the above implementation process, the manufacturing process of the strap 1 is one of the key technical aspects. A flexible material is selected as the strap substrate, and dot patterns 3, line patterns 4, and surface patterns 5 are drawn on the substrate surface. The size of the dot patterns 3, the thickness of the line patterns 4, and the shape of the surface patterns 5 are all generated in a random distribution. By controlling the distribution density of the dot patterns 3, the bending angle of the line patterns 4, and the area variation of the surface patterns 5, the design of the patterns is ensured to meet the requirements of randomness and non-reproducibility. The width and length of the strap 1 are adjusted according to the dimensions of the outer packaging 2 of the product to ensure that it can fit tightly to the outer packaging 2 and cover the opening area.

[0073] Throughout the implementation process, the random winding method of the ribbon 1 ensures that its pattern is highly random and uncopyable, fundamentally solving the counterfeiting problem. The anti-counterfeiting platform 7 enhances data security and reliability through a distributed storage architecture and blockchain technology, providing an efficient, low-cost, and easy-to-operate solution for modern commodity anti-counterfeiting. The consumer verification process is simplified by a dedicated scanning tool 8, improving the user experience. The introduction of image recognition technology enables automated acquisition and comparison of anti-counterfeiting patterns, improving the efficiency and accuracy of anti-counterfeiting verification.

[0074] All content not described in detail in this specification is prior art known to those skilled in the art, and the model parameters of each device are not specifically limited; conventional equipment can be used. Electrical control components not mentioned in this technical solution are not shown in the figures because they are prior art, and will not be described further here.

[0075] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A product anti-counterfeiting verification method based on random winding patterns, characterized in that, The process includes the following steps: The tape is manually and randomly wrapped around the opening of the outer packaging of the product to ensure that the removal of the tape is a necessary condition for opening the outer packaging; The wrapped tape is photographed using an image acquisition device to extract the unique pattern formed by the recombination of points, lines and surfaces on the tape, and the pattern is uploaded to the anti-counterfeiting platform for storage, while establishing a correspondence between the pattern and the product. After obtaining the product, consumers scan the pattern on the tape using a dedicated scanning tool provided by the anti-counterfeiting system. The anti-counterfeiting system then compares the scan results with the patterns stored on the platform. If the scan result matches the stored pattern, the product is considered genuine; otherwise, it is considered counterfeit.

2. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The production process of the strap includes the following steps: Selecting a flexible material as the strap substrate, drawing dot, line, and surface patterns on the substrate surface, wherein the size of the dots, the thickness of the lines, and the shape of the surfaces are all generated in a random distribution manner; the design of the patterns meets the requirements of randomness and non-reproducibility, which is achieved by controlling the distribution density of the dots, the bending angle of the lines, and the area variation of the surfaces; the width and length of the strap are adjusted according to the size of the outer packaging of the product to ensure that the strap can fit tightly to the outer packaging and cover the opening.

3. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The method of securing the strap includes the following steps: First, secure one end of the strap to the starting position of the outer packaging using adhesive or clips; then, wrap the strap around the outer packaging multiple times by hand using random winding; during the winding process, the dots, lines, and surfaces on the strap will recombine due to random bending and twisting, forming a unique overall pattern; after winding, secure the end of the strap to the ending position of the outer packaging using the same securing method as the starting position.

4. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The specific operation of the image acquisition device includes the following steps: using a high-resolution camera to photograph the wrapped tape, with the shooting angle perpendicular to the tape surface to reduce the impact of perspective distortion; during the shooting process, ensuring uniform light distribution and avoiding interference from shadows or reflections on pattern recognition; preprocessing the shooting results using image processing algorithms, including noise reduction, edge detection, and contrast enhancement, to improve the clarity and recognizability of the pattern; extracting the unique pattern formed by the recombination of points, lines, and surfaces on the tape, and converting it into a digital image stored in the anti-counterfeiting platform.

5. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The storage and comparison process of the anti-counterfeiting platform includes the following steps: the extracted pattern is bound and stored with the product's unique identification code to ensure that each product corresponds to a unique pattern; the stored pattern is encrypted to prevent unauthorized access or tampering; after the consumer scans the pattern on the tape, the anti-counterfeiting system compares the scan result with the stored pattern pixel by pixel; during the comparison process, a certain error range is allowed to accommodate minor differences that may occur under different shooting conditions.

6. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The dedicated scanning tool of the anti-counterfeiting system includes the following functional modules: a camera module for capturing patterns on the tape; an image processing module for preprocessing and feature extraction of the shooting results; a communication module for transmitting the extracted patterns to the anti-counterfeiting platform for comparison; and a result display module for providing feedback on the comparison results to consumers.

7. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The comparison algorithm of the anti-counterfeiting system adopts feature point matching technology, which includes the following steps: extracting feature points from the stored patterns and scanning results respectively. The selection of feature points is based on the distribution density of points, the curvature angle of lines, and the area change of surfaces; calculating the similarity between feature points, using Euclidean distance or cosine similarity as the measurement standard; when the similarity exceeds a preset threshold, the two patterns are determined to be consistent, otherwise they are determined to be inconsistent.

8. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The security design of the anti-counterfeiting platform includes the following measures: A distributed storage architecture is adopted, which disperses the pattern data across multiple server nodes to reduce the risk of single point of failure; blockchain technology is introduced to record the binding relationship between the pattern and the product, ensuring the immutability of the data; Configure access control to allow only authorized users to query or modify stored pattern data.

9. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The design of the dots, lines, and surfaces on the surface of the strip shall meet the following conditions: the size of the dots shall be randomly distributed between 0.1 mm and 1 mm; the thickness of the lines shall be randomly distributed between 0.05 mm and 0.5 mm; the shape of the surfaces shall be a regular geometric shape or an irregular geometric shape, and the area shall be randomly distributed between 1 square millimeter and 10 square millimeters.

10. The product anti-counterfeiting verification method based on random winding patterns according to claim 1, characterized in that, The error range of the anti-counterfeiting system is set to a pixel deviation of no more than 5% of the total number of pixels, in order to accommodate minor differences that may occur under different shooting conditions.

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