An anti-counterfeiting label, its preparation method and verification method

Abstract

This invention provides an anti-counterfeiting label, its preparation method, and verification method, relating to the field of anti-counterfeiting label technology. It includes an adhesive sticker with a QR code and a fingerprint code printed on it. The fingerprint code includes a specific colored pattern and also includes raised textures hidden beneath the colored pattern and protruding upwards. This invention solves the problem that existing anti-counterfeiting labels rely on visual identification, making them unsuitable for certain groups or environments. It enriches the identification methods of anti-counterfeiting labels, thereby improving their applicability and helping users accurately distinguish genuine from counterfeit labels.

Description

Technical Field

[0001] This invention relates to the field of anti-counterfeiting label technology, and more specifically, to an anti-counterfeiting label, its preparation method, and its verification method. Background Technology

[0002] An anti-counterfeiting label includes an adhesive sticker with a QR code and a fingerprint code printed on it. The fingerprint code includes a specific color pattern. When the anti-counterfeiting label is verified, the user terminal (e.g., a mobile phone) scans the QR code to obtain a parameter sequence. After the parameter sequence is input into the verification system, the verification system will look up the fingerprint code parameter corresponding to the parameter sequence based on the binding relationship. The fingerprint code parameter is then input into a specific drawing program to obtain a fingerprint code image and feed it back to the user. Finally, the user can visually compare the fed-back fingerprint code image with the color pattern on the sticker to distinguish the authenticity of the anti-counterfeiting label.

[0003] However, this identification method is highly dependent on the user's vision. When the user's vision is affected, such as when the user has an eye disease (such as red-green color blindness, cataracts, etc.), the user often cannot accurately identify the authenticity of the anti-counterfeiting label through this identification method. Similarly, if the lighting conditions are poor (such as dim lighting or other colored light instead of white light), the user will also be unable to accurately identify the authenticity of the anti-counterfeiting label.

[0004] There is currently no effective technical solution to the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide an anti-counterfeiting label, its preparation method, and its verification method. This invention solves the problem that existing anti-counterfeiting labels rely on visual identification, which makes them unsuitable for certain groups of people or certain environments. It enriches the identification methods of anti-counterfeiting labels, thereby improving their applicability and helping users to accurately identify the authenticity of anti-counterfeiting labels.

[0006] In a first aspect, the present invention provides a verification method for use on an anti-counterfeiting label, the anti-counterfeiting label comprising an adhesive sticker, the sticker having a QR code and a fingerprint code printed on it, the fingerprint code comprising a specific color pattern and a raised texture hidden beneath the color pattern and protruding upwards;

[0007] The verification method includes the following steps:

[0008] B1. The user terminal scans the QR code to obtain the first parameter sequence;

[0009] B2. Input the first parameter sequence into the verification system and obtain the color verification pattern and texture verification pattern after passing the verification;

[0010] B3. The authenticity of the anti-counterfeiting label is determined by the color verification pattern and / or the texture verification pattern.

[0011] This method incorporates tactile verification, significantly improving its reliability. Accurate verification can still be performed through touch, even in low light conditions or when the user's vision is limited. Furthermore, the dual verification mechanism increases the difficulty of anti-counterfeiting and enhances system security.

[0012] Furthermore, the specific steps in step B3 include:

[0013] B31. Verify the authenticity of the anti-counterfeiting label by any one or more of the following steps:

[0014] B31A. The authenticity of the anti-counterfeiting label is determined by visually comparing the color verification pattern with the color pattern on the sticker;

[0015] B31B. The authenticity of the anti-counterfeiting label can be determined by tactile comparison of the texture verification pattern and the raised texture on the sticker.

[0016] Furthermore, the raised texture includes a magnetic body embedded under the colored pattern; the sticker has a foldable card that can be placed on the fingerprint code on the side near the fingerprint code, the card being filled with powder that can be attracted by the magnetic body, the card being used to make the magnetic body visible through the powder when placed on the fingerprint code.

[0017] Step B31, which involves verifying the authenticity of the anti-counterfeiting label, further includes:

[0018] B31C. The authenticity of the anti-counterfeiting label is determined by covering the fingerprint code with the card and visually comparing the texture verification pattern with the powder morphology displayed on the card.

[0019] Secondly, the present invention provides an anti-counterfeiting label, including an adhesive sticker, on which a QR code and a fingerprint code are printed. The fingerprint code includes a specific colored pattern and also includes raised textures that are hidden beneath the colored pattern and protrude upwards.

[0020] The anti-counterfeiting label of the present invention not only retains the method of distinguishing authenticity through visual comparison, but also adds the method of distinguishing authenticity through tactile comparison, so that the anti-counterfeiting label has more means of identification, thereby meeting more user requirements and environmental requirements, greatly improving its applicability and facilitating accurate identification of authenticity.

[0021] Furthermore, the raised texture includes a magnetic material embedded beneath the colored pattern; the sticker has a foldable card that covers the fingerprint code on one side, the card being filled with powder that can be attracted and moved by the magnetic material, the card being used to make the magnetic material visible through the powder when it is covered on the fingerprint code.

[0022] By introducing tactile and magnetic verification, the reliability and applicability of anti-counterfeiting labels are greatly increased.

[0023] Furthermore, the shape of the raised texture can be any one or more of the following: granular, strip-shaped, and block-shaped.

[0024] Thirdly, the present invention provides a method for preparing the aforementioned anti-counterfeiting label, comprising the following steps:

[0025] S1. Generate the QR code according to a specific first parameter sequence and print it on the sticker;

[0026] S2. Obtain a second parameter sequence that has a unique correspondence with the first parameter sequence; the second parameter sequence contains a feature code and a parameter code;

[0027] S3. Determine the shape and position of the raised texture according to the feature code and set the raised texture within a preset area of ​​the sticker;

[0028] S4. Press the protective layer onto the sticker and make the protective layer fully cover the raised texture;

[0029] S5. Generate the color pattern according to the parameter code and print it on the preset area.

[0030] This method effectively solves the problem of existing anti-counterfeiting label verification methods relying too heavily on user vision. By introducing raised textures, it provides users with a tactile verification option, reducing reliance on visual perception.

[0031] Furthermore, the raised texture is granular in shape;

[0032] The specific steps in step S3 include:

[0033] S31. Obtain the corresponding scatter plot based on the feature code; the scatter plot includes multiple first random points scattered within the preset area;

[0034] S32. Set the raised texture at each of the first random points.

[0035] Furthermore, the feature code is obtained through the following steps:

[0036] A1. A three-dimensional sphere model is obtained based on a random generation algorithm for discrete points on a sphere; the surface of the three-dimensional sphere model is scattered with multiple second random points;

[0037] A2. Randomly generate the orientation information of the virtual camera relative to the three-dimensional sphere model; the orientation information includes the relative coordinates and relative distance of the virtual camera relative to the center of the three-dimensional sphere model;

[0038] A3. Generate a corresponding feature code based on the three-dimensional sphere model and the orientation information;

[0039] The specific steps in step S31 include:

[0040] S311. Determine the corresponding three-dimensional sphere model based on the feature code and obtain the corresponding relative coordinates and relative distance;

[0041] S312. Control the movement of the virtual camera according to the corresponding relative coordinates and relative distance, and obtain the corresponding first-view image through the window after the virtual camera is in place, and use it as the corresponding scatter plot; the shape and size of the window are consistent with the shape and size of the preset area.

[0042] Furthermore, the specific steps in step A3 include:

[0043] A31. The virtual camera is moved according to the corresponding relative coordinates and relative distances, and after the virtual camera is in place, the corresponding second-view image is obtained through the view window; the second-view image contains multiple randomly distributed third points;

[0044] A32. Determine the processing range of each of the third random points in the second perspective view; the processing range refers to the range enclosed by a circular boundary drawn with the third random point as the center and a preset radius;

[0045] A33. When the processing ranges of any two of the third random points overlap, adjust the relative distance so that the processing ranges of all the third random points do not overlap;

[0046] A34. When the processing range of any of the third random points exceeds the view window, adjust the relative coordinates so that the processing range of all the third random points falls within the view window;

[0047] A35. Generate the corresponding feature code based on the three-dimensional sphere model, the adjusted relative distance, and the adjusted relative coordinates.

[0048] As can be seen from the above, the anti-counterfeiting label provided by the present invention adds a raised texture similar to an embossed design on the basis of a colored pattern. This raised texture has the same specificity as the colored pattern. Users can obtain the shape of the raised texture of the genuine product through the verification system and then compare it from a tactile perspective. This achieves the effect of distinguishing between genuine and counterfeit products through both visual and tactile comparison, avoiding the situation of relying solely on visual identification. It enriches the identification methods of anti-counterfeiting labels, broadens the scope of application of anti-counterfeiting labels, meets more user requirements, and breaks through more environmental limitations.

[0049] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the structure of an anti-counterfeiting label provided in an embodiment of the present invention.

[0051] Figure 2 This is a schematic diagram of the structure of an anti-counterfeiting label provided in an embodiment of the present invention, showing a card folded over a fingerprint code.

[0052] Figure 3 This is a cross-sectional view of an anti-counterfeiting label provided in an embodiment of the present invention.

[0053] Figure 4 This is a flowchart of a preparation method provided in an embodiment of the present invention.

[0054] Figure 5 A flowchart of a verification method provided in an embodiment of the present invention.

[0055] Label Explanation:

[0056] 100. QR code; 200. Fingerprint code; 210. Colored pattern; 220. Raised texture; 221. Magnetic object; 300. Card. Detailed Implementation

[0057] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0058] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0059] Existing anti-counterfeiting label technologies typically use adhesive stickers printed with QR codes and fingerprint codes. The fingerprint code includes a specific color pattern used for verification. During verification, the user's terminal scans the QR code to obtain a parameter sequence, which is then input into the verification system. The system retrieves the corresponding fingerprint code parameters based on the binding relationship, generates a fingerprint code image, and sends it back to the user. The user visually compares the returned fingerprint code image with the color pattern on the sticker to distinguish the authenticity of the anti-counterfeiting label.

[0060] However, this anti-counterfeiting method relies heavily on the user's visual ability, which can lead to inaccurate identification results in certain situations. For example, when users have visual impairments (such as red-green color blindness, cataracts, etc.), they may find it difficult to accurately identify subtle differences in colored patterns. Furthermore, poor lighting conditions, such as dim light or interference from colored light sources, can also affect the user's accurate judgment of colored patterns. These factors can significantly reduce the effectiveness of anti-counterfeiting measures and increase the risk of counterfeit and substandard products circulating in the market.

[0061] For example, certain colors may appear distorted under warm lighting. Furthermore, some products may target older consumers who may have varying degrees of vision problems, further complicating accurate identification.

[0062] In this situation, anti-counterfeiting methods that rely solely on visual comparison may lead to the following consequences:

[0063] First, the misjudgment rate may increase significantly, leading to genuine products being mistaken for counterfeits or counterfeits being mistaken for genuine products, which will affect brand reputation and consumer rights.

[0064] Secondly, in order to improve the accuracy of identification, the verification process may require longer time and more specialized equipment, which reduces the practicality and popularity of the anti-counterfeiting system.

[0065] Third, this limitation could be exploited by criminals who could create counterfeit products that are harder to distinguish by mimicking visual effects.

[0066] Therefore, an anti-counterfeiting technology that does not rely entirely on visual recognition and can maintain high accuracy under various environmental conditions is particularly important. This not only relates to the protection of brand rights but also directly affects consumer interests and the maintenance of market order. Therefore, an innovative technical solution is urgently needed to overcome the limitations of existing anti-counterfeiting labels under visually restricted conditions and achieve a reliable and universally applicable anti-counterfeiting effect.

[0067] For reference, see the appendix. Figure 1 The present invention provides an anti-counterfeiting label, including an adhesive sticker, on which a QR code 100 and a fingerprint code 200 are printed. The fingerprint code 200 includes a specific colored pattern 210 and also includes a raised texture 220 hidden under the colored pattern 210 and protruding upward.

[0068] Adhesive stickers refer to thin sheets of material with an adhesive backing that can be easily attached to various surfaces. They can be made of materials such as polyethylene, polypropylene, or polyester, and coated with pressure-sensitive adhesive.

[0069] A QR code is a matrix-style two-dimensional barcode capable of storing a large amount of information. It can be implemented using standard formats such as QR codes and Data Matrix.

[0070] A fingerprint code is a unique graphic identifier containing a specific color pattern. It can be implemented using multi-colored stripes, dot matrix, or irregular patterns.

[0071] Raised textures refer to tiny raised structures formed on the surface of the sticker. These can be achieved using processes such as embossing, hot pressing, or 3D printing.

[0072] This embodiment introduces a raised texture hidden beneath a colored pattern within the fingerprint code. This design cleverly combines visual and tactile anti-counterfeiting methods, overcoming the limitations of traditional anti-counterfeiting labels that rely solely on visual identification. The raised texture allows for tactile verification of the anti-counterfeiting label's authenticity even under visually restricted conditions, thereby improving the reliability and applicability of the anti-counterfeiting effect.

[0073] The anti-counterfeiting label of this application uses an adhesive sticker as the basic carrier, on which a QR code and a fingerprint code are printed. The QR code adopts a standard matrix two-dimensional barcode format for storing and quickly reading anti-counterfeiting information. The fingerprint code contains two key elements: a specific color pattern and an raised texture.

[0074] The colored patterns are printed directly onto the sticker surface using a precise printing process, and can take the form of multi-colored stripes, dot matrix, or irregular shapes. These colored patterns provide the primary visual anti-counterfeiting effect. The raised texture is formed on the sticker surface before or after the colored pattern is printed using a special process and is covered by the colored pattern. The height of the raised texture is controlled at the micrometer level to ensure that it does not significantly affect the visual effect of the colored pattern, while still being perceptible to the touch.

[0075] During the anti-counterfeiting verification process, users can first perform preliminary verification by visually comparing the colored patterns. If lighting conditions are poor or vision is limited, users can lightly touch the fingerprint code area with their finger to perceive the presence and distribution of the raised texture. This dual verification mechanism greatly improves the reliability of the anti-counterfeiting effect.

[0076] The design of the raised texture takes several factors into consideration. First, the height and distribution of the texture are carefully calculated to provide sufficient tactile feedback without compromising visual appeal. Second, the shape and arrangement of the texture can be designed into specific patterns as needed, increasing its uniqueness and difficulty in counterfeiting. Finally, the material selection for the raised texture needs to consider abrasion resistance and compatibility with colored patterns to ensure long-term stability; for example, it can be created by printing layer by layer with UV-curing inks and curing with ultraviolet light.

[0077] Through this design, the anti-counterfeiting label of this application retains the advantages of traditional visual anti-counterfeiting while adding tactile anti-counterfeiting function, effectively solving the technical problem of difficulty in accurately distinguishing authenticity under visually limited conditions.

[0078] In some embodiments, reference is made to the appendix. Figure 1 and attached Figure 2 The raised texture 220 includes a magnetic body 221 embedded under the colored pattern 210; a card 300 that can be folded and covered over the fingerprint code 200 is provided on the side of the sticker near the fingerprint code 200. The card 300 is filled with powder that can be attracted and moved by the magnetic body 221. The card 300 is used to make the magnetic body 221 visible through the powder when it is covered over the fingerprint code 200.

[0079] This embodiment creates a multi-factor authentication mechanism by introducing a magnetic material and a foldable card. The magnetic material is embedded under a colored pattern, forming a raised texture that can be sensed by touch. The powder filling the foldable card can be attracted by the magnetic material, revealing its shape when it covers a fingerprint code.

[0080] Specifically, the magnetic material can be made of various materials, such as metals like iron, cobalt, and nickel, or their alloys. These materials have good magnetism and can effectively attract powder from the card. The shape and distribution of the magnetic material can be designed as needed, for example, it can be dots, lines, or specific patterns. This design allows the raised texture to be perceived by touch even when the colored patterns are not clearly discernible.

[0081] The size of the foldable card should match the fingerprint area to ensure complete coverage. The powder filling the card can be fine iron powder or other magnetic particles. This powder should be fine enough to accurately display the shape of the magnetic material without leaking out of the card.

[0082] When the card is placed over the fingerprint code, the magnet attracts the powder, forming a pattern corresponding to the shape of the magnet. This method provides a new verification method that does not rely on existing color patterns, and is particularly suitable for situations with poor lighting or limited color discrimination by the user.

[0083] In practical applications, users can determine the authenticity of an anti-counterfeiting label by touching the raised texture of the fingerprint code area. Alternatively, users can place a foldable card over the fingerprint code to observe the powder distribution. If the anti-counterfeiting label is genuine, the powder will be attracted by a magnetic material, forming a pattern corresponding to the shape of the magnetic material; this pattern should match the intended design.

[0084] As a preferred embodiment, the magnetic material can be designed into specific patterns or text, such as a brand logo or product name. When the card is covered, the revealed powder pattern will form these specific patterns or text, further increasing the reliability of anti-counterfeiting measures.

[0085] In addition, the card can be designed for multiple uses. For example, the sticker can be pasted on the product while the card remains movable (i.e., the card can still be folded normally to cover the fingerprint code). At this time, the user can flick the card with their finger to vibrate the powder inside and cause the powder to redisperse.

[0086] This improved anti-counterfeiting label structure offers significant advantages over existing technologies. Traditional methods primarily rely on visual identification, which proves ineffective in low light conditions or when the user's vision is limited. The proposed solution, however, significantly increases the reliability and applicability of the anti-counterfeiting label by introducing tactile and magnetic verification. For example, in complete darkness, users can verify the label's authenticity by touch. Similarly, users with red-green color blindness can verify the label's authenticity by observing the powder's morphology. This multi-layered verification mechanism not only increases the difficulty of anti-counterfeiting but also expands the label's application scenarios, enabling it to function effectively in various environments.

[0087] In some embodiments, reference is made to the appendix. Figure 3 The raised texture 220 can be any one or more of the following shapes: granular, strip-shaped, and block-shaped.

[0088] Specifically, granular textures may be more suitable for applications requiring a fine tactile feel. For example, fine granular raised textures can be used in anti-counterfeiting labels for some high-end products, providing not only a unique tactile experience but also a subtle visual texture effect. Striped textures are likely more easily perceived by touch and are suitable for scenarios requiring rapid verification. For example, raised striped textures can be used on product packaging that requires frequent verification, allowing verifiers to quickly determine authenticity through simple touch. Block textures may provide a more pronounced visual and tactile effect and are suitable for applications requiring a higher level of security. For example, raised block textures can be used on anti-counterfeiting labels for important documents or high-value items; this texture is not only easily identifiable but also provides a stronger anti-counterfeiting effect.

[0089] Furthermore, these raised textures of different shapes can be combined to form more complex texture patterns. For example, granular, striped, and blocky textures can be used in different areas of the anti-counterfeiting label, or these different shaped textures can be arranged in a specific pattern to form a unique texture combination. This combination not only increases the design flexibility of the anti-counterfeiting label, but also greatly increases the difficulty of counterfeiting.

[0090] Therefore, by providing a variety of shape options, the technical solution of this application increases the flexibility and adaptability of anti-counterfeiting labels. At the same time, the diverse shapes also increase the difficulty of counterfeiting, as potential counterfeiters need to accurately replicate specific shape combinations. Furthermore, the presence of raised textures not only provides visual anti-counterfeiting but also increases the possibility of tactile anti-counterfeiting. This multi-dimensional anti-counterfeiting feature makes the verification process more reliable, enabling effective verification even under poor visual conditions.

[0091] This design not only solves the problem of diverse raised texture shapes in anti-counterfeiting labels but also improves their security and counterfeiting resistance. Compared with existing technologies, the solution presented in this application has the following advantages: First, the diverse raised texture shapes increase the design flexibility of anti-counterfeiting labels, allowing for the selection of the most suitable texture combination based on different products and application scenarios. Second, the raised texture is hidden beneath the colored pattern, increasing the concealment of the anti-counterfeiting features and making it difficult for counterfeiters to replicate through surface observation. Third, the combination of multiple shapes significantly increases the difficulty of counterfeiting, as it requires the simultaneous replication of multiple intricate texture shapes and arrangements. Finally, this design provides both visual and tactile verification methods, enabling effective verification even in low-light conditions, greatly improving the practicality and reliability of anti-counterfeiting labels.

[0092] Reference Appendix Figure 3 and attached Figure 4 The present invention provides a method for preparing the anti-counterfeiting label in the above embodiments, comprising the following steps:

[0093] S1. Generate a QR code based on a specific first parameter sequence and print it on a sticker;

[0094] S2. Obtain the second parameter sequence that has a unique correspondence with the first parameter sequence; the second parameter sequence contains a feature code and a parameter code;

[0095] S3. Determine the shape and position of the raised texture based on the feature code and set the raised texture within the preset area of ​​the sticker;

[0096] S4. Press the protective layer onto the sticker and ensure that the protective layer fully covers the raised texture;

[0097] S5. Generate a color pattern based on the parameter code and print it on the preset area.

[0098] The anti-counterfeiting label preparation method proposed in this application solves the problem of excessive reliance on user vision in existing anti-counterfeiting label verification methods by introducing raised textures and corresponding preparation steps. Specifically, this method provides the possibility of tactile verification by setting raised textures on the sticker, reducing reliance on vision. Combining the raised texture with colored patterns achieves dual verification of vision and touch, improving the anti-counterfeiting effect. The generation of QR codes, raised textures, and colored patterns using parameter sequences and feature codes ensures the uniqueness and relevance of anti-counterfeiting information. Covering the raised texture with a protective layer enhances the durability of the anti-counterfeiting label.

[0099] First, in step S1, a QR code is generated based on a specific first parameter sequence and printed on the sticker. This step can be achieved in various ways, such as using specialized QR code generation software or converting the first parameter sequence into a QR code pattern using a custom algorithm. Printing can employ technologies such as thermal transfer, inkjet, or laser printing, the specific choice depending on the sticker material and durability requirements.

[0100] In step S2, a second parameter sequence that uniquely corresponds to the first parameter sequence is obtained. This correspondence can be established using a hash function, encryption algorithm, or other mapping methods. The second parameter sequence contains a feature code and a parameter code; this separation design increases the complexity and security of the anti-counterfeiting information.

[0101] In step S3, the shape and position of the raised texture are determined based on the feature code. The raised texture can be of various shapes, such as dots, lines, or specific patterns. The position can be determined based on a random distribution generated by the feature code or a preset rule. The raised texture can be created using processes such as embossing printing, hot pressing, or UV curing.

[0102] Step S4 involves laminating the protective layer onto the sticker. The protective layer can be made of a transparent plastic film or a special coating, and the lamination process must ensure that the raised texture is not damaged. Hot or cold pressing techniques can be used, and specific parameters such as temperature, pressure, and time need to be adjusted according to the material properties.

[0103] Finally, step S5 generates a color pattern based on the parameter code and prints it on the preset area. The color pattern can be generated using a specialized image processing algorithm to convert the parameter code into a specific combination of colors and patterns. A high-precision color printer can be selected to ensure the clarity and color reproduction of the pattern.

[0104] These steps are closely interconnected and interactive. For example, the correspondence between the first and second parameter sequences ensures the correlation between the QR code, the raised texture, and the colored pattern. The combination of setting the raised texture and printing the colored pattern creates the possibility of dual visual and tactile verification. The lamination of the protective layer not only protects the raised texture but also enhances the durability of the entire anti-counterfeiting label.

[0105] The anti-counterfeiting label preparation method of this application effectively solves the problem of excessive reliance on user vision in existing anti-counterfeiting label verification methods by combining multiple technical features. By introducing raised texture, this method provides users with a tactile verification option, reducing reliance on vision. Even when user vision is affected or lighting conditions are poor, users can still verify the authenticity of the anti-counterfeiting label by touching the raised texture.

[0106] Specifically, the generation of the first parameter sequence and the QR code provides the foundational information for subsequent verification. The second parameter sequence contains a feature code and a parameter code, uniquely corresponding to the first parameter sequence, ensuring the uniqueness and relevance of the anti-counterfeiting information. The raised texture determines its shape and position based on the feature code, providing a basis for tactile verification and significantly reducing reliance on visual perception. A protective layer covers the raised texture, protecting it from damage and ensuring long-term reliability. The colored pattern is generated based on the parameter code, providing a basis for visual verification; combined with the raised texture, it enhances the overall anti-counterfeiting effect.

[0107] These features work together to achieve dual verification through both visual and tactile means, effectively solving the problem of over-reliance on visual verification. Even in low light conditions or when the user's vision is limited, tactile verification can still be performed effectively, greatly improving the reliability and applicability of anti-counterfeiting labels.

[0108] As a preferred embodiment, the method for preparing the anti-counterfeiting label of this application can be as follows:

[0109] First, a 128-bit random number generator is used to generate the first parameter sequence, which serves as a unique identifier. Using a standard QR code generation algorithm, this 128-bit sequence is encoded into a 33×33 pixel QR code, which is then printed onto a 50mm×50mm PET sticker using a 600dpi thermal transfer printer.

[0110] Next, the first parameter sequence is converted into a 256-bit second parameter sequence using the SHA-256 hash algorithm. These 256 bits are divided into two parts: the first 128 bits are used as the signature, and the last 128 bits are used as the parameter code.

[0111] Based on the feature code, a Voronoi diagram-based algorithm is used to generate a distribution map of the raised texture. Within a central 30mm x 30mm area of ​​the sticker, 20-30 randomly distributed dot-like raised textures are generated, each with a diameter of 0.5-1mm and a height of 0.1-0.2mm. These raised textures are then applied to the sticker surface using UV curing technology.

[0112] Then, a 0.05mm thick transparent PET film is selected as the protective layer and pressed for 30 seconds at 120℃ and 5MPa using a hot press to ensure that the protective layer completely covers the raised texture and adheres tightly to the sticker.

[0113] Finally, a color pattern is created using the parameter code through a proprietary image generation algorithm. This algorithm converts the 128-bit parameter code into a complex, difficult-to-reproduce color pattern containing multiple geometric shapes and gradient colors. Using a 1200 dpi resolution inkjet printer, this color pattern is precisely printed on a 30mm × 30mm area containing the raised texture.

[0114] In this way, the anti-counterfeiting labels produced contain both visible QR codes and colored patterns, as well as tactile raised textures, achieving a dual anti-counterfeiting effect of both visual and tactile senses.

[0115] Compared with existing technologies, the anti-counterfeiting label preparation method of this application has significant advantages. Existing technologies mainly rely on visual verification, which makes it difficult to accurately distinguish between genuine and counterfeit products when lighting is insufficient or the user's vision is limited. This application, by introducing raised textures, provides the possibility of tactile verification, greatly reducing reliance on visual conditions. Simultaneously, the method of this application organically combines QR codes, raised textures, and colored patterns through a unique correspondence of parameter sequences, forming a more complex and difficult-to-counterfeit anti-counterfeiting system. Furthermore, the application of a protective layer enhances the durability of the anti-counterfeiting label, solving the problem of easy wear and tear of anti-counterfeiting features in existing technologies. These innovations significantly improve the reliability, applicability, and security of the anti-counterfeiting label of this application.

[0116] In some embodiments, the raised texture is granular in shape;

[0117] The specific steps in step S3 include:

[0118] S31. Obtain the corresponding scatter plot based on the feature code; the scatter plot contains multiple first random points scattered within a preset area;

[0119] S32. Set raised textures at each of the first random points.

[0120] This application introduces the concepts of feature codes and scatter plots to transform abstract parameter sequences into specific raised texture locations. By randomly distributing granular raised textures within a preset area, the security of the anti-counterfeiting label is increased, while also facilitating user verification through touch. This method solves the problem of determining the shape and position of the raised texture, improving the reliability and practicality of the anti-counterfeiting label.

[0121] The raised texture is designed with a granular shape, which offers several advantages. First, the granular shape facilitates its dispersion within a pre-defined area, enabling greater randomness and unpredictability. Second, the granular shape allows users to perceive it through touch, enabling verification even in visually limited situations. The size of the granular raised texture can be adjusted according to actual needs, typically set to a diameter between 0.1mm and 1mm to ensure tactile perception without compromising the overall aesthetics of the label.

[0122] In step S31, the conversion from parameters to specific locations is achieved by generating a scatter plot using the feature code. Various algorithms can be used to generate the scatter plot, such as pseudo-random number generation algorithms and hash functions. These algorithms ensure that the same feature code always generates the same scatter plot, while different feature codes generate scatter plots with sufficient differences.

[0123] A scatter plot contains multiple first random points scattered across a preset area. The preset area can be a specific region on a label, such as a rectangular or circular area. The number of random points can be adjusted as needed, typically between 5 and 20, to strike a balance between security and manufacturing complexity.

[0124] In step S32, raised textures are set at each of the first random points. This step transforms the scatter plot into actual raised textures, thus determining the positions of the raised textures. Raised textures can be achieved in various ways, such as hot pressing, UV curing, and 3D printing. The height of each raised texture can be set between 0.05mm and 0.5mm to ensure it is tactile but not overly prominent.

[0125] The technical solution of this application achieves precise determination of the shape and position of the raised texture through the above steps. This method has the following advantages:

[0126] First, by using feature codes and parameter codes, this application establishes a mapping relationship from abstract data to specific physical characteristics. This mapping relationship is unique and irreversible, greatly increasing the security of anti-counterfeiting labels.

[0127] Secondly, the use of scatter plots and random point locations ensures the random distribution of the raised texture within the preset area. This randomness makes the anti-counterfeiting label difficult to copy or counterfeit, because even if the generation algorithm is known, the same raised texture distribution cannot be reproduced without the original feature code.

[0128] Furthermore, designing the raised texture as granular not only facilitates manufacturing but also allows users to verify the authenticity through touch. This design takes into account different usage scenarios and user needs, improving the practicality and universality of the anti-counterfeiting label.

[0129] Finally, the technical solution of this application achieves highly personalized and difficult-to-replicate anti-counterfeiting features through the combination of software algorithms and hardware manufacturing. This combination raises the technical threshold of anti-counterfeiting labels and increases the difficulty of counterfeiting.

[0130] As a specific embodiment, the following scenario can be considered:

[0131] Suppose we need to produce anti-counterfeiting labels for a batch of high-end watches. First, generate a second-parameter sequence containing the production date, batch number, and serial number, for example, "20230601-A001-00001". Then, convert this second-parameter sequence into a feature code using a specific algorithm, such as "7f8a9b2c3d4e5f6g".

[0132] Next, a pseudo-random number generator based on feature codes is used to generate 5 random points within a preset area of ​​10mm × 10mm. The coordinates of these points are recorded to form a scatter plot.

[0133] During the manufacturing process, sophisticated 3D printing technology is used to print a granular raised texture with a diameter of 0.2 mm and a height of 0.1 mm at each random point. These raised textures are distributed within a predetermined area, forming a unique tactile pattern.

[0134] Finally, a colored pattern is overlaid on the raised texture to complete the anti-counterfeiting label. This type of anti-counterfeiting label can not only be initially verified visually, but also allows for deeper verification by feeling the distribution of the raised texture.

[0135] Compared to existing technologies, traditional anti-counterfeiting labels primarily rely on visual verification, which is easily affected by lighting conditions and user vision. This application overcomes these limitations by introducing tactile verification. Furthermore, the randomly distributed raised texture of this application is more difficult to counterfeit than fixed patterns, thus improving the anti-counterfeiting effect. In addition, the technical solution of this application can ensure the uniqueness of each anti-counterfeiting label, which is difficult to achieve with traditional mass-produced anti-counterfeiting labels.

[0136] In some embodiments, the signature is obtained through the following steps:

[0137] A1. A three-dimensional sphere model is obtained based on a random generation algorithm for discrete points on a sphere; multiple second random points are scattered on the surface of the three-dimensional sphere model;

[0138] A2. Randomly generate the orientation information of the virtual camera relative to the 3D sphere model; the orientation information includes the relative coordinates and relative distance of the virtual camera relative to the center of the 3D sphere model;

[0139] A3. Generate the corresponding feature code based on the three-dimensional sphere model and orientation information;

[0140] The specific steps in step S31 include:

[0141] S311. Determine the corresponding three-dimensional sphere model based on the feature code and obtain the corresponding relative coordinates and relative distance;

[0142] S312. Control the movement of the virtual camera according to the corresponding relative coordinates and relative distance, and obtain the corresponding first-person view through the window after the virtual camera is in place, and use it as the corresponding scatter plot; the shape and size of the window are consistent with the shape and size of the preset area.

[0143] The feature code generation method proposed in this application cleverly solves the problem of unreasonable point distribution during feature code generation by introducing the concepts of a three-dimensional sphere model and a virtual camera. First, a three-dimensional sphere model is created using a spherical discrete point random generation algorithm to ensure that points are uniformly distributed on the sphere. Then, the orientation information of the virtual camera is randomly generated, increasing the randomness and complexity of the feature code. Finally, by controlling the movement of the virtual camera and acquiring images from specific viewpoints, a scatter plot adapted to a preset area is generated.

[0144] This method ensures the randomness and uniformity of the point distribution, avoiding the clustering or sparsity problems that may occur with traditional two-dimensional planar random generation. By changing the position of the virtual camera, countless different scatter plots can be generated from the same three-dimensional sphere model, greatly increasing the uniqueness and security of the feature code. Using a viewport with the same shape and size as the preset area ensures that the generated scatter plot can perfectly fit the specified area on the anti-counterfeiting label, thus facilitating the placement of magnetic objects when preparing the anti-counterfeiting label.

[0145] The feature code generation method of this application includes the following key steps:

[0146] 1. Random Point Generation Algorithm for a Spherical Discrete Surface: This algorithm is used to generate a 3D sphere model, ensuring the randomness and uniformity of point distribution. It can be implemented using various methods, such as:

[0147] a) Spherical coordinate method: Randomly generate angles and radii in a spherical coordinate system, and then convert them to a Cartesian coordinate system.

[0148] b) Rejection sampling: Randomly generate points within the cube space, retaining only those points that fall within the sphere.

[0149] c) Spiral method: Points are evenly distributed along a spiral line on the spherical surface.

[0150] 2. Virtual Camera Orientation Information Generation: Randomly generate the orientation information of the virtual camera relative to the 3D sphere model, including relative coordinates and relative distance. The following methods can be used:

[0151] a) Spherical coordinate random method: randomly generate angles in the spherical coordinate system, and generate distances either fixedly or randomly.

[0152] b) Vector randomization method: Randomly generate unit vectors, and then randomly generate distances.

[0153] 3. Feature Code Generation: Generate a feature code based on the 3D sphere model and orientation information. The following encoding methods can be used:

[0154] a) Direct encoding: Directly encode the parameters of the spherical model and the camera orientation information.

[0155] b) Hash encoding: Hash the sphere model and camera orientation information.

[0156] c) Compression coding: Use compression algorithms to reduce the amount of data in the feature code.

[0157] 4. Scatter Plot Acquisition: A scatter plot is generated by controlling the movement of a virtual camera and capturing images from a specific viewpoint. Specific steps include:

[0158] a) Decode the 3D sphere model and camera orientation information based on the feature code.

[0159] b) Move the virtual camera to the designated location.

[0160] c) Obtain a two-dimensional scatter plot by projecting through a window.

[0161] These steps are closely interconnected and work together to generate high-quality feature codes and scatter plots. The spherical discrete point algorithm ensures a uniform distribution of points, the introduction of a virtual camera increases the complexity of the feature codes, and the use of a viewport guarantees the matching of the scatter plot with the preset area.

[0162] In practical applications, the method of this application can flexibly adjust parameters to meet different needs. For example, the density and distribution characteristics of the generated scatter plot can be controlled by adjusting parameters such as the size of the sphere, the number of points, and the camera distance range. In addition, multiple virtual cameras can be introduced to simultaneously acquire multiple scatter plots from different angles, further increasing the complexity and security of the feature code. Specific Implementation

[0163] Suppose we need to generate a feature code and scatter plot for a 5cm×5cm anti-counterfeiting label.

[0164] 1. Use a spherical discrete point random generation algorithm to create a three-dimensional sphere model with a radius of 100 units, and evenly distribute 100 points on the sphere surface.

[0165] 2. Randomly generate virtual camera location information:

[0166] Relative coordinates: (x,y,z)=(78.3,-45.6,92.1).

[0167] Relative distance: 150 units.

[0168] 3. Encode the sphere model parameters and camera orientation information into feature codes, for example: "S100P100C78.3,-45.6,92.1D150".

[0169] 4. Reconstruct the 3D scene based on the feature code:

[0170] Parse the feature code, reconstruct the sphere model, and set the virtual camera position.

[0171] Point the virtual camera at the center of the ball and set the viewport size to 5cm x 5cm.

[0172] A two-dimensional scatter plot was obtained by projecting the viewport, resulting in approximately five points scattered within a 5cm × 5cm area.

[0173] 5. Use these points as the locations for placing the magnetic elements to complete the design of the anti-counterfeiting label.

[0174] This application successfully solves the problem of unreasonable point distribution during feature code generation using this method. Compared with traditional two-dimensional plane random generation methods, the method of this application has the following advantages:

[0175] 1. The distribution of points is more even, avoiding the problems of local clustering or sparseness.

[0176] 2. The uniqueness and security of the signature are significantly improved, making it difficult to crack through simple copying or guessing.

[0177] 3. The generated scatter plot can perfectly fit the preset area, which facilitates the subsequent production of anti-counterfeiting labels.

[0178] 4. By adjusting the parameters, the density and distribution characteristics of the scatter plot can be flexibly controlled to adapt to different application needs.

[0179] This feature code generation method based on three-dimensional space not only solves the technical problem of unreasonable point distribution, but can also be used in combination with other anti-counterfeiting technologies to further improve the security and reliability of anti-counterfeiting labels.

[0180] In some embodiments, the specific steps in step A3 include:

[0181] A31. Control the movement of the virtual camera according to the corresponding relative coordinates and relative distance, and obtain the corresponding second-view image through the view window after the virtual camera is in place; the second-view image contains multiple randomly distributed third points;

[0182] A32. Determine the processing range of each third random point in the second-view image; the processing range refers to the area enclosed by a circular boundary drawn with the third random point as the center and a preset radius;

[0183] A33. When the processing ranges of any two third random points overlap, adjust the relative distance so that the processing ranges of all third random points do not overlap;

[0184] A34. When the processing range of any third random point exceeds the view window, adjust the relative coordinates so that the processing range of all third random points falls within the view window;

[0185] A35. Generate the corresponding feature code based on the three-dimensional sphere model, the adjusted relative distance, and the adjusted relative coordinates.

[0186] The technical solution of this application optimizes the feature code generation process through a series of steps. First, a second-view image containing random points is acquired using a virtual camera. Then, a processing range is set for each random point, and the distribution of these points is optimized by adjusting the relative distance and relative coordinates. Specifically, when the processing ranges of points overlap, the overlap is eliminated by adjusting the relative distance; when the processing range exceeds the viewport, the relative coordinates are adjusted to ensure that all points are within the viewport. Finally, a feature code is generated based on these optimized parameters.

[0187] In practical applications, the technical solution of this application can be implemented in the following ways:

[0188] First, the virtual camera's movement is controlled based on relative coordinates and relative distance. For example, a three-dimensional coordinate system can be set up, with the center of the sphere at the origin (0, 0, 0), and the initial position of the virtual camera might be (10, 10, 10), with a relative distance of 17.32 units. By adjusting these parameters, the position and viewpoint of the virtual camera can be changed.

[0189] Secondly, a second-person perspective view is obtained through a viewport. The viewport can be designed as a circular area, for example, 640x480 pixels (the shape and size of the viewport are consistent with the shape and size of the preset area). Once the virtual camera is in place, it captures the image of the 3D sphere model through this viewport, forming the second-person perspective view.

[0190] Next, determine the processing range for each third random point in the second-view image. The processing range can be defined as a circular area centered on each random point. For example, a fixed radius value, such as 5 pixels, can be set as a preset radius.

[0191] Next, two key adjustment steps will be performed:

[0192] 1. When the processing ranges of any two third random points overlap, adjust the relative distance. For example, if the circular processing ranges of two points intersect, the relative distance of the virtual camera can be gradually increased, such as from the initial 17.32 units to 18.5 units, until all processing ranges no longer overlap.

[0193] 2. When the processing range of any third random point exceeds the viewport, adjust the relative coordinates. For example, if the processing range of a certain point partially falls outside the 640x480 pixel viewport, you can adjust the relative coordinates of the virtual camera, such as adjusting the x-coordinate from 10 to 9.5, until the entire processing range falls completely within the viewport.

[0194] Finally, the final feature code is generated using a specific encoding algorithm based on the adjusted parameters.

[0195] The advantage of this method lies in its ability to dynamically adjust the distribution of random points, ensuring better uniformity and reliability of the generated feature codes. Through repeated adjustments, the method in this application can effectively avoid the point clustering or sparsity problems that may occur in traditional random generation methods, thereby improving the quality and anti-counterfeiting effect of the feature codes.

[0196] For example, in one specific embodiment, suppose there are 100 randomly distributed points on the initial 3D sphere model. The virtual camera captures images of 5 points at the current location. These points may be unevenly distributed, with some areas densely populated and others sparsely populated. Using the method of this application, the processing radius of each point is first set to 5 pixels. Then, the system checks if there are any overlapping processing ranges among these 5 points. If two pairs of points are found to have overlapping processing ranges, the system increases the relative distance, for example, from the initial 20 units to 22 units. This process is repeated until the processing ranges of all points no longer overlap.

[0197] Next, the system checks if any point's processing area extends beyond the 640x480 pixel viewport. If one point is found to have a portion of its processing area outside the viewport, the system fine-tunes the virtual camera's relative coordinates, for example, adjusting the x-coordinate from 10 to 9.8 and the y-coordinate from 10 to 10.2. This process is repeated until the processing areas of all points are completely within the viewport.

[0198] Through the above optimizations, each point has sufficient spacing and is all within the specified viewing window, which helps to improve the recognition accuracy and anti-counterfeiting effect of the feature code.

[0199] This application introduces a three-dimensional sphere model and a virtual camera. By changing the position of the virtual camera, different scatter plots are obtained. Finally, feature codes with different characteristics are generated based on different three-dimensional sphere models and different orientation information. Furthermore, this application's method introduces the concept of processing range, providing a clear criterion for optimizing the point distribution, making the optimization process more precise and controllable. Compared to simple random generation or fixed template methods, this application's method ensures both randomness and the quality and reliability of the feature codes, thereby greatly improving the security and practicality of anti-counterfeiting labels.

[0200] Reference Appendix Figure 5 The present invention provides a verification method for anti-counterfeiting labels based on the above embodiments (i.e., the verification method can be applied to the anti-counterfeiting labels in the above embodiments), comprising the following steps:

[0201] B1. The user terminal scans the QR code to obtain the first parameter sequence;

[0202] B2. Input the first parameter sequence into the verification system and obtain the color verification pattern and texture verification pattern after passing the verification;

[0203] B3. Verify the authenticity of anti-counterfeiting labels by using color verification patterns and / or texture verification patterns.

[0204] The verification method proposed in this application effectively solves the technical problem that relying solely on visual comparison makes it difficult to accurately distinguish the authenticity of anti-counterfeiting labels by introducing a multi-dimensional verification mechanism. Specifically, the method first uses a user terminal to scan a QR code to obtain a parameter sequence, and then generates a color verification pattern and a texture verification pattern through the verification system. These two verification patterns correspond to visual and tactile verification, respectively, so that the verification process is no longer limited to a single visual comparison.

[0205] By providing both visual and tactile verification methods, this approach significantly improves the accuracy and reliability of anti-counterfeiting verification. Even in poor lighting conditions or when the user's vision is limited, verification can still be performed through tactile comparison. This multi-dimensional verification method not only enhances the anti-counterfeiting effect but also improves the applicability and universality of the verification process.

[0206] The core innovation of this method lies in the introduction of texture verification patterns, enabling tactile verification. This innovative design means that anti-counterfeiting verification no longer relies entirely on vision, greatly improving the reliability and applicability of the verification process.

[0207] The verification method proposed in this application includes three main steps:

[0208] First, the user's terminal scans the QR code to obtain the first parameter sequence. This step can be achieved in various ways, such as using a smartphone's camera to scan the QR code on the sticker, or using a dedicated QR code scanning device. During the scanning process, the device may need to adjust the focus and lighting to ensure accurate reading of the QR code information. The first parameter sequence may contain various information, such as the unique identifier of the anti-counterfeiting label, the production date, batch number, etc.

[0209] Next, the first parameter sequence is input into the verification system, and upon successful verification, a color verification pattern and a texture verification pattern are obtained. The verification system can be a remote server or a local device, which receives the first parameter sequence and performs verification. The verification process may involve steps such as querying a database and decrypting information. After successful verification, the system generates two verification patterns: a color verification pattern and a texture verification pattern. The color verification pattern may be a complex color pattern or graphic, while the texture verification pattern may be a tactile description or model of a surface texture.

[0210] Finally, the authenticity of the anti-counterfeiting label is verified using color verification patterns and / or texture verification patterns. Users can choose to use visually contrasting color verification patterns, or tactilely sensing texture verification patterns, or both methods simultaneously. This flexibility allows the verification process to adapt to different environmental conditions and user needs.

[0211] These three steps are closely linked, forming a complete verification process. The parameter sequence obtained in the first step provides the necessary input information for subsequent verification. The processing by the verification system in the second step ensures the security and reliability of the verification, while the two generated verification patterns provide multi-dimensional references for the final identification. The flexible verification method in the final step makes full use of the results of the first two steps, achieving accurate anti-counterfeiting identification.

[0212] A specific embodiment of this verification method is as follows:

[0213] Users scan the QR code on the anti-counterfeiting label using their smartphones. The QR code contains a 128-bit unique identifier as the first parameter sequence. The mobile application sends this sequence to the verification server via an encrypted channel. The server verifies the validity of the sequence and generates a 300x300 pixel color verification pattern containing specific color gradients and geometric shapes. Simultaneously, the server also generates a corresponding texture verification pattern describing the location and number of a series of tiny bumps.

[0214] The verification pattern is returned to the user's phone via an encrypted channel. The user can view the color verification pattern on the screen and visually compare it with the actual pattern on the anti-counterfeiting label. For texture verification, the user can lightly touch the surface of the anti-counterfeiting label with their fingertip to feel the position and size of the raised areas and compare it with the texture verification pattern provided by the mobile app.

[0215] Compared to existing technologies, traditional methods rely solely on visual comparison, making them susceptible to lighting conditions and user vision limitations. This method, however, introduces tactile verification, significantly improving its reliability. Even in low light conditions or when user vision is impaired, accurate verification can still be performed through touch. Furthermore, the dual verification mechanism increases the difficulty of anti-counterfeiting and enhances system security.

[0216] In some embodiments, the specific steps in step B3 include:

[0217] B31. Verify the authenticity of the anti-counterfeiting label by following one or more of the following steps:

[0218] B31A. Verify the authenticity of anti-counterfeiting labels by visually comparing the color verification pattern with the color pattern on the sticker;

[0219] B31B. Verify the authenticity of anti-counterfeiting labels by comparing the texture of patterns and the raised texture on stickers.

[0220] It offers flexible verification options, allowing users to choose between visual comparison, tactile comparison, or a combination of both for verification, increasing the applicability and practicality of the verification method.

[0221] The technical solution proposed in this application includes two methods for identifying the authenticity of anti-counterfeiting labels: visual comparison and tactile comparison. These two methods can be used alone or in combination to improve the accuracy and reliability of identification.

[0222] Specifically, the visual comparison method distinguishes genuine anti-counterfeiting labels from fake ones by comparing the color verification pattern with the color pattern on the sticker. This method utilizes the human eye's ability to recognize colors and patterns, allowing for quick and intuitive identification. However, this method may be affected by poor lighting conditions or limited user vision.

[0223] To overcome the limitations of visual comparison, this application introduces a tactile comparison method. This method distinguishes the authenticity of anti-counterfeiting labels by comparing the texture verification pattern and the raised texture on the sticker. The raised texture can take different shapes, such as granular, striped, or blocky, to increase the difficulty and accuracy of identification. The tactile comparison method does not depend on visual conditions, so it can still be used effectively in low light or when the user's vision is limited.

[0224] Combining these two methods can significantly improve the accuracy of identifying genuine anti-counterfeiting labels. For example, in well-lit conditions, users can first perform visual comparison, and then further confirm through tactile comparison. In low-light environments, users can primarily rely on tactile comparison for identification.

[0225] Furthermore, the technical solution of this application takes into account the needs and usage scenarios of different users. For users with normal vision, visual comparison methods can be used primarily; for users with limited vision, tactile comparison methods can be relied upon more. This flexibility makes the anti-counterfeiting label verification method of this application applicable to a wider range of user groups and usage environments.

[0226] The technical solution of this application effectively solves the problem of inaccurate identification that may result from relying solely on visual comparison by combining visual and tactile senses for verification. Visual comparison provides an intuitive identification method, while tactile comparison offers an identification method that does not depend on visual conditions. The combined use of the two can greatly improve the accuracy and reliability of identifying genuine and counterfeit anti-counterfeiting labels.

[0227] In practical applications, the technical solution of this application can be implemented according to the following steps:

[0228] First, the user receives an anti-counterfeiting label that needs to be verified. This label contains an adhesive sticker with a QR code and a fingerprint code printed on it. The fingerprint code includes a specific colored pattern and an upward-protruding texture hidden beneath the colored pattern.

[0229] Next, the user scans the QR code on the anti-counterfeiting label using a terminal device (such as a smartphone) to obtain the first parameter sequence. The user then inputs this first parameter sequence into the verification system. After successful verification, the verification system generates and provides the user with a color verification pattern and a texture verification pattern.

[0230] Users can then choose one or more of the following methods to verify the authenticity of the anti-counterfeiting label:

[0231] 1. Visual Comparison: Users will visually compare the color verification pattern provided by the verification system with the color pattern on the sticker. Users need to carefully observe the details such as the color, shape, and position of the two patterns to determine whether they are completely identical.

[0232] 2. Tactile Comparison: Users can compare the texture verification pattern provided by the verification system with the raised texture on the sticker using tactile means. Users can gently touch the raised texture on the sticker with their fingers to feel its shape and distribution, and then compare it with the texture verification pattern.

[0233] 3. Combined use: Users can first perform visual comparison, then tactile comparison, or both comparisons simultaneously. This method can maximize the accuracy of identification.

[0234] This method allows for the identification of genuine anti-counterfeiting labels through tactile comparison, even in low light conditions or when the user's vision is limited, thus overcoming the limitations of existing technologies that rely too heavily on visual comparison.

[0235] Compared with the prior art, the technical solution of this application has the following advantages:

[0236] 1. Multi-sensory verification: By combining visual and tactile verification, the accuracy and reliability of identifying genuine and counterfeit anti-counterfeiting labels are improved. This multi-sensory verification method overcomes the limitations of single-sensory verification.

[0237] 2. High adaptability: The technical solution of this application is applicable to various lighting conditions and user vision. Even in situations with insufficient light or limited user vision, effective verification can still be performed through tactile comparison.

[0238] 3. High flexibility: Users can choose to use visual comparison, tactile comparison or a combination of both for verification according to the actual situation, which increases the applicability and practicality of the verification method.

[0239] 4. Enhanced Security: By introducing tactile verification, the security of anti-counterfeiting labels is increased, making counterfeiting more difficult. Counterfeiters not only need to replicate the visual effects but also imitate the tactile characteristics.

[0240] 5. User-friendly: The technical solution of this application takes into account the needs of different users. Whether the user has normal vision or limited vision, this verification method can be used conveniently.

[0241] In summary, the technical solution proposed in this application effectively solves the problem of inaccurate identification that may result from relying solely on visual comparison by combining visual and tactile verification, thereby improving the accuracy, reliability, and applicability of anti-counterfeiting label verification.

[0242] In some embodiments, the raised texture 220 includes a magnetic body 221 embedded under the colored pattern 210; a card 300 that can be folded and covered over the fingerprint code 200 is provided on the side of the sticker near the fingerprint code 200, the card 300 is filled with powder that can be attracted by the magnetic body 221, and the card 300 is used to make the magnetic body 221 visible through the powder when it is covered over the fingerprint code 200.

[0243] Step B31, used to verify the authenticity of the anti-counterfeiting label, also includes:

[0244] B31C. Cover the card with the fingerprint code and verify the authenticity of the anti-counterfeiting label by visually comparing the texture and the powder form shown on the card.

[0245] The technical solution proposed in this application creatively transforms anti-counterfeiting verification from a simple visual comparison to a combination of physical interaction and visual perception by introducing a magnetic material and powder that can be attracted by the magnetic material. This method not only increases the difficulty of anti-counterfeiting but also improves the accuracy of verification. Even in poor lighting conditions or when the user's color perception is limited, the authenticity of the anti-counterfeiting label can be determined relatively accurately by observing the pattern formed by the powder on the card.

[0246] Specifically, in the anti-counterfeiting label of this application, the raised texture includes a magnetic material embedded beneath the colored pattern. This design provides a physical basis for subsequent verification. The magnetic material can be made of various materials, such as metals like iron, cobalt, and nickel, or their alloys, or magnetic oxides like ferrite. The shape of the magnetic material can be granular, strip-shaped, or block-shaped, and its size and distribution can be designed according to specific requirements.

[0247] The sticker has a foldable card attached to the side closest to the fingerprint scanner. This foldable design allows the card to stay firmly on the sticker when not in use, preserving the overall appearance of the label, while conveniently covering the fingerprint scanner when verification is required. The card can be made of a soft and transparent material, such as paper or thin plastic.

[0248] The card is filled with a powder that can be attracted to a magnetic object. This powder is a key material in the verification process, capable of interacting with magnetic materials. The powder can be fine iron powder or other magnetic particles. The particle size of the powder should be small enough to ensure that it can form a clear pattern under the influence of a magnetic field.

[0249] When a card is placed over a fingerprint scanner, the powder inside the card is attracted by a magnetic material, forming a pattern on the card surface that corresponds to the texture of the magnetic material. This process makes the previously hidden magnetic texture visible. The movement and aggregation of the powder are affected by the strength of the magnetic field, so the clarity and accuracy of the pattern directly reflects the distribution of the magnetic material.

[0250] During the verification process, the user first scans a QR code using their terminal to obtain the first parameter sequence and inputs it into the verification system. Upon successful verification, the system generates a color verification pattern and a texture verification pattern. Next, the user places the card over the fingerprint code. The powder inside the card is then attracted by a magnetic material, forming a specific pattern on the card's surface. The user visually compares the texture verification pattern with the powder pattern displayed on the card to determine the authenticity of the anti-counterfeiting label.

[0251] This verification method combines physical interaction and visual contrast, greatly improving the reliability of anti-counterfeiting measures. Even in low-light conditions, or for users with weak color recognition abilities, or those who cannot make an accurate judgment after touching the raised texture, observing the black and white contrast pattern formed by the powder can help determine the authenticity of the anti-counterfeiting label relatively accurately.

[0252] Furthermore, because the distribution of the magnetic material is hidden and the interaction with the powder is based on physical principles, this method also greatly increases the difficulty of counterfeiting.

[0253] As a preferred implementation, an image recognition function can be incorporated into the verification system. Users can photograph the powder pattern formed on the card and upload it to the verification system for automatic comparison. The verification system can use image processing algorithms to analyze the uploaded image and compare it with a preset standard pattern, thereby providing a more objective verification result.

[0254] In one specific embodiment, the anti-counterfeiting label has a sticker size of 5cm × 5cm, with the fingerprint code area measuring 2cm × 2cm. The raised texture uses granular magnetic material with a particle size between 50-100 micrometers, randomly distributed within the fingerprint code area. The card size is 2.5cm × 2.5cm, with a thickness of 0.5mm, and is uniformly filled with iron powder with a particle size of 10-20 micrometers. During verification, the user places the card over the fingerprint code and gently taps it a few times to ensure the powder is fully affected by the magnetic field. Subsequently, the user can visually inspect the pattern formed on the card surface or use a magnifying glass and compare it with a standard pattern provided by the verification system.

[0255] Compared to existing technologies, traditional methods rely primarily on the user's visual recognition ability, which is easily affected by ambient light and individual differences in vision. This application, by introducing magnetic interaction, transforms hidden information into a tactile and more easily identifiable form, significantly improving the accuracy and reliability of verification. Furthermore, this method increases the difficulty of counterfeiting anti-counterfeiting labels, as counterfeiters not only need to replicate the visual effect but also precisely mimic the distribution of the magnetic material, which is technically more challenging.

[0256] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0257] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for producing a security label, characterized by, The anti-fake label comprises a pasteable sticker, the sticker is printed with a two-dimensional code (100) and a fingerprint code (200), the fingerprint code (200) comprises a specific color pattern (210), characterized in that the fingerprint code (200) further comprises a raised texture (220) hidden under the color pattern (210) and protruding upward; The preparation method of the anti-fake label comprises the following steps: S1. generating the two-dimensional code according to a specific first parameter sequence and printing on the sticker; S2. obtaining a second parameter sequence having a unique correspondence with the first parameter sequence; the second parameter sequence comprises a feature code and a parameter code; S3. determining the shape and position of the raised texture according to the feature code and setting the raised texture in a preset area of the sticker; S4. pressing a protective layer on the sticker and making the protective layer fully cover the raised texture; S5. generating the color pattern according to the parameter code and printing on the preset area; The shape of the raised texture is granular; The specific steps in step S3 comprise: S31. obtaining a corresponding scatter plot according to the feature code; the scatter plot comprises a plurality of first random points arranged dispersedly in the preset area; S32. setting the raised texture on each first random point; The feature code is obtained by the following steps: A1. obtaining a three-dimensional spherical model based on a spherical discrete point random generation algorithm; the three-dimensional spherical model surface is dispersedly arranged with a plurality of second random points; A2. randomly generating the orientation information of a virtual camera relative to the three-dimensional spherical model; the orientation information comprises the relative coordinates and relative distance of the virtual camera relative to the center of the three-dimensional spherical model; A3. generating a corresponding feature code according to the three-dimensional spherical model and the orientation information; The specific steps in step S31 comprise: S311. determining the corresponding three-dimensional spherical model according to the feature code and obtaining the corresponding relative coordinates and relative distance; S312. controlling the virtual camera to move according to the corresponding relative coordinates and relative distance, and obtaining a corresponding first perspective picture through a view window after the virtual camera is in position and taking the first perspective picture as a corresponding scatter plot; the shape and size of the view window are consistent with the shape and size of the preset area; The specific steps in step A3 comprise: A31. controlling the virtual camera to move according to the corresponding relative coordinates and relative distance, and obtaining a corresponding second perspective picture through the view window after the virtual camera is in position; the second perspective picture comprises a plurality of third random points arranged dispersedly; A32. determining the processing range of each third random point in the second perspective picture; the processing range refers to the range surrounded by the circular boundary drawn according to the preset radius with the third random point as the center; A33. when the processing ranges of any two third random points overlap, adjusting the relative distance to make the processing ranges of all third random points not overlap. A34. When the processing range of any one of the third random point positions exceeds the viewing window, adjust the relative coordinates so that the processing range of all the third random point positions falls within the viewing window; A35. Generate a corresponding feature code according to the three-dimensional spherical model, the adjusted relative distance, and the adjusted relative coordinates.

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