Three-dimensional code element label with self-anti-counterfeiting function, and generation method and verification method thereof

Abstract

A three-dimensional code element label with a self-anti-fake function comprises a medium carrier, the medium carrier is formed through a standard printing technology, the surface of the medium carrier is randomly provided with at least three positioning patterns in a regular geometrical shape, the center coordinates of the multiple positioning patterns can form a verification area of a square structure, and the center coordinates of the multiple positioning patterns can form the verification area. The verification region is uniformly divided into a plurality of sub-regions; the three-dimensional code pattern is formed by mixing colored particles with glue through a letterpress printing process and then randomly fixing the mixture on the surface of the medium carrier; the verification code area comprises three rows of verification code codes: the first row of verification codes comprises information codes with more than 13 bits; the second row of verification codes comprises more than 21 bits of verification codes, and the multiple verification codes comprise a total number code of particles in a verification area, a number code of particles in each sub-area and an anti-counterfeiting verification code; and the third line of verification code comprises a coordinate code with more than 25 bits.

Description

Technical Field

[0001] The present invention relates to the field of three-dimensional code labels, and particularly to a three-dimensional code element label with self-antiforgery function, a generation method thereof, and a verification method thereof. Background Art

[0002] There are seven types of anti-counterfeiting technologies, namely material anti-counterfeiting, printing anti-counterfeiting, laser anti-counterfeiting, digital anti-counterfeiting, electronic identification anti-counterfeiting, texture anti-counterfeiting, and security line digital information anti-counterfeiting. The current mainstream solution is to paste a two-dimensional code on the commodity, and consumers scan the two-dimensional code to authenticate the authenticity of the commodity and obtain the traceability information of the commodity. Since the two-dimensional code algorithm is an open-source algorithm, counterfeiters can directly generate two-dimensional codes. For two-dimensional codes using encryption algorithms, counterfeiters can obtain the two-dimensional code electronic image by photographing the two-dimensional code printed matter with instruments (such as two-dimensional code duplicators, high-definition cameras, etc.), then use image correction software to make certain adjustments to the two-dimensional code electronic image, and finally print the two-dimensional code electronic image with the same type of material to obtain counterfeit two-dimensional codes.

[0003] In the prior art, such as the three-dimensional code generation method disclosed in Application No. 2021108820314, includes the following steps: the code generation end obtains commodity information and background pictures; the code generation end generates a two-dimensional code matrix according to the commodity information; the code generation end fuses the background picture and the two-dimensional code matrix to obtain a three-dimensional code; several first specific areas and several second specific areas are selected on the three-dimensional code; the color values of each first specific area and the color values of each second specific area are recorded. And the three-dimensional code is associated with the commodity, and the three-dimensional code is used for anti-counterfeiting traceability of the commodity.

[0004] First of all, although the above three-dimensional code label can achieve the effect of integrating three-element information, its essence still uses two-dimensional code technology, only adding a product background picture to the two-dimensional code technology. It only increases the anti-counterfeiting difficulty, but its anti-counterfeiting effect is really limited. Secondly, the generation of the label requires a product background picture, so the association between the label and the product is extremely large, which not only increases the cost of label generation, but also greatly limits the use range of the label itself. Summary of the Invention

[0005] In order to solve the above problems, the present invention provides a three-dimensional code element label with self-antiforgery function, a generation method thereof, and a verification method thereof: A three-dimensional code element label with self-antiforgery function includes the following parts: A medium carrier, which is formed by a standard printing process, and at least three positioning graphics in regular geometric shapes are randomly provided on the surface of the medium carrier. The central coordinates of the multiple positioning graphics can form a square-structured verification area, and the verification area is evenly divided into multiple sub-areas; Three-dimensional code pattern, which is formed by randomly fixing colored particles mixed with glue on the surface of the medium carrier through intaglio printing process. The three-dimensional code pattern has a three-dimensional concave and convex touch feeling. The colored particles are randomly distributed within the verification area, and the particle size of the colored particles is 0.1 - 5.5 mm; Verification code area, including three rows of verification code encodings: The first row of verification code contains more than 13-bit information encodings. Multiple said information encodings include one or more of enterprise code, production time, or production serial number; The second row of verification code contains more than 21-bit check encodings. Multiple said check encodings include the total number of particles encoding in the verification area, the number of particles encoding in each sub-area, and the anti-counterfeiting verification encoding. The anti-counterfeiting verification encoding is generated through an encryption algorithm based on the existing encodings; The third row of verification code contains more than 25-bit coordinate encodings. Multiple said coordinate encodings include the first domain value and the center coordinates of more than 4 specific particles. The first domain value is used to determine the sub-area where multiple specific particles are located. The specific particles are more than 4, and the coordinate information is extracted and encoded through the Hough transform algorithm; The verification code encodings are displayed in plain text or in ciphertext through an encryption algorithm.

[0006] Preferably, the positioning pattern is any one of a circle, a triangle, a square, or a rectangle. When the positioning pattern is a circle, its diameter is more than one time the average diameter of the colored particles; when the positioning pattern is a polygon, its minimum side length is more than one time the average diameter of the colored particles.

[0007] Preferably, the first check encoding of the second row of verification code is a division encoding used to determine the equal division type of the verification area, and the division encoding is greater than zero. The division encoding is a non-zero bit. When it represents 0, the placeholder meaning is reserved, reserved, indicating a total of 15 types from 1 - F. The division encoding determines the equal division type of the verification area through its own table, and the content of its own table can be set according to user needs. For example, when the division encoding is 1, it means that the square verification area is divided into 9 equal sub-areas; The total number of particles encoding in the verification area, more than 2 bits, is used to represent the total number value of the colored particles in the verification area; The number of particles encoding in the area, more than 18 bits, represents the number of particles in each of the multiple sub-areas divided in the verification area. The number of particles is encoded in decimal or hexadecimal; The anti-counterfeiting verification code, more than 4 bits, is generated by extracting part of the hash value through a hash operation on the foregoing encodings.

[0008] Preferably, the verification code in the third row includes a first-bit domain value and the central coordinates of more than 4 specific particles. The first-bit domain value coordinates are in hexadecimal, with a total of 16 types. The range of the first-bit domain value is 0 - F. The first-bit domain value is used to determine the sub-region where multiple specific particles are located through a provided Lookup Table 1, which is set by the user himself. The Lookup Table 1 contains the first-bit domain value and the sub-region labels corresponding to the first-bit domain value where multiple specific particles are located. The central coordinates of each specific particle are represented by a 6-digit hexadecimal number, where the first 3 digits are the abscissa and the last 3 digits are the ordinate. The selection rule for the specific particles is as follows: number them in sequence from left to right along the X-axis and from top to bottom along the Y-axis. When the serial number is odd, add 1 to the odd number and then divide by 2. When the serial number is even, divide it directly by 2. The resulting number is the serial number of the center dot of the specific particle to be taken, and the coordinates of the center dot of this specific particle are taken out and compiled into the coding table.

[0009] Preferably, the Hough transform algorithm includes the following steps: (1) Perform grayscale conversion, Gaussian blur, and Canny edge detection on the verification area image; (2) Detect the center coordinates and radius of the colored particles through the Hough gradient method, and screen the particles that meet the preset radius range; (3) Convert the detection result to the original image coordinate system, and record the number and position of the particles.

[0010] Preferably, the encryption algorithm uses symmetric encryption, asymmetric encryption, hybrid encryption system, national encryption algorithm, or hash algorithm to generate ciphertext encoding.

[0011] Preferably, the label is applied to the identification of the origin of goods, anti-counterfeiting certification, metaverse scene mapping, or the scene of binding unique encoding with one-dimensional code and two-dimensional code.

[0012] A method for generating the three-dimensional code element label includes the following steps: S1: Prepare a medium carrier, form a medium carrier substrate through a printing process, and print a positioning pattern on the surface of the medium carrier substrate to delimit the verification area; S2: Randomly distribute colored particles on the surface of the medium carrier through a relief printing process to form a three-dimensional pattern with a concave-convex touch; S3: Use the Hough transform algorithm to extract the quantity, position, and central coordinate information of the colored particles in the three-dimensional pattern; S4: Generate a verification code according to the extracted information. The verification code includes information encoding, check encoding, and coordinate encoding, and print the verification code on the medium carrier.

[0013] A method for verifying the three-dimensional code element label includes the following steps: S1: Obtain the label image through machine vision recognition technology, recognize the positioning pattern and delimit the verification area; S2: Identify the information code, check code and coordinate code in the verification area, and parse the number, position and central coordinate information of the particles of the three-dimensional pattern contained in the verification code; S3: Use the Hough transform algorithm to extract the number, position and central coordinate information of the particles of the three-dimensional pattern in the verification area; S4: Compare and verify the extracted information with the data parsed from the verification code. If they are consistent, it is judged as genuine; otherwise, it is judged as fake.

[0014] Preferably, the comparison and verification include: In the networked mode, compare the extracted label image with the original generated image in the database; In the offline mode without a network environment, reverse-infer the number and position information of the particles through the verification code, and compare it with the extracted value of the current image.

[0015] The three-dimensional code element label generation and verification method with anti-counterfeiting function provided by the present invention has the following remarkable beneficial effects compared with the existing one-dimensional code, two-dimensional code and ordinary anti-counterfeiting labels: Through the comprehensive anti-counterfeiting scheme of physical randomness (three-dimensional concave and convex particles) + high-precision machine vision + high-strength encryption (SM4 national encryption algorithm and Hough transform algorithm) + multi-mode verification (networked / offline / tactile), the present invention realizes the anti-counterfeiting effect of being extremely difficult to counterfeit, quickly recognizable and widely applicable, and can be widely applied to fields such as luxury anti-counterfeiting, food traceability, drug authenticity guarantee, and metaverse commodity authentication, and has extremely high market application value. Brief Description of the Drawings

[0016] Figure 1 It is a schematic diagram of the three-dimensional code element label structure.

[0017] Figure 2 It is a schematic diagram of the verification area of the meta-label.

[0018] Figure 3 It is a legend diagram of the encoding description of the meta-label.

[0019] Figure 4 It is a schematic diagram of the application of the Hough transform algorithm. Detailed Embodiment

[0020] The following further describes the present invention in combination with Figure 1-2 Examples.

[0021] A three-dimensional code element label with self-anti-counterfeiting function includes the following parts: Media carrier, which is formed by a standard printing process. There are at least three positioning patterns with regular geometric shapes randomly on the surface of the media carrier. The central coordinates of multiple said positioning patterns can be constructed into a verification area in a square structure. The positioning pattern is any one of a circle, a triangle, a square or a rectangle. When the positioning pattern is a circle, its diameter is more than one time the average diameter of the colored particles; when the positioning pattern is a polygon, its minimum side length is more than one time the average diameter of the colored particles. In this embodiment, taking a circle as an example, the positioning pattern is a positioning circle. The positioning circle is printed on the media carrier by an inkjet or printing standard process to form a standard. When printing, the diameter of the circle needs to be more than one time the average particle diameter to facilitate machine reading and discrimination / zoning; a rectangular area with a predetermined length and width is constructed according to the center points of each positioning circle as the next verification area, and then the verification area is evenly divided into multiple sub-areas.

[0022] Three-dimensional code pattern, which is formed by randomly fixing colored particles mixed with glue on the surface of the media carrier through a relief printing process. The three-dimensional code pattern has a three-dimensional concave-convex touch feeling. The colored particles are randomly distributed within the verification area, and the particle size of the colored particles is 0.1 - 5.5 mm.

[0023] Taking Figure 3 as an example, the verification code area includes three rows of verification code encodings: The first row of verification code contains 21-bit information encoding. The information encoding is plaintext encoding, and the number of digits of the information encoding can be extended. The 21-bit information encoding sequentially includes an enterprise code, a production time, and a production serial number. The enterprise code can be composed of the 13-bit encoding of the original one-dimensional bar code of the commodity, or can be determined by the enterprise itself during use. The production time is 6-bit encoding, and the production serial number is 2-bit digital encoding. For example Figure 3 The first row of verification code of a certain enterprise can be: 48970313524**-250308-03, representing the product code of the 3rd production batch of this enterprise on March 8, 2025.

[0024] The second row of verification code contains 25-bit check encoding. The 25-bit check encoding sequentially includes the following parts: The first bit of the check encoding is a division encoding used to determine the equal division type of the verification area. The division encoding is greater than zero. The division encoding is a non-0 bit. When it represents 0, the placeholder meaning is reserved. It represents a total of 15 types from 1 - F. The division encoding determines the equal division type of the verification area through its own table, and the content of its own table can be set according to user needs. For example Figure 3 As shown, when the division encoding is 1, it means that the square verification area is divided into 9 equal sub-areas.

[0025] The 2nd - 3rd position check code is the total number code of particles in the verification area. The total number code of particles in the verification area has 2 digits and is used to represent the total number value of colored particles in the verification area, with a lower limit of 000 and an upper limit of 255, encoded in hexadecimal. As shown in the appendix Figure 3 It shows that the 1st - 3rd position check code vertically is 17E, indicating that the verification area image is equally divided into 9 sub - regions, and the number of particles recognized by the program is 7E in hexadecimal, which is 126 in decimal.

[0026] The area particle number code. Since this embodiment has 9 sub - regions, the area particle number code has 18 digits, representing the number of particles in each of the 9 sub - regions divided in the verification area. As Figure 3 shown, the area particle number code is 1412090C0C110D0E0B, which means that the number of particles recognized by the algorithm in each of the 9 sub - regions is successively 14, 12, 09, 0C, 0C, 11, 0D, 0E, 0B in hexadecimal encoding.

[0027] The anti - counterfeiting verification code, 4 - digit. It performs a standard hash operation on the previous encoded numbers and takes the 1st digit and the last 3 digits (the first, second, and third digits from the right) of the hash value to form a 4 - digit anti - counterfeiting verification code area. The previous encoded numbers described in this application can be either information codes or check codes, or even coordinate codes, and can actually be set by the user themselves.

[0028] The 3rd - row verification code contains more than 25 - digit coordinate codes. The multiple coordinate codes include a 1st - digit domain value and the center coordinates of more than 4 specific particles. The 1st - digit domain value is used to determine the sub - region where the multiple specific particles are located. The specific particles are more than 4, and the coordinate information is extracted and encoded through the Hough transform algorithm.

[0029] The third-line verification code includes the first bit field value and the central coordinates of more than 4 specific particles. The coordinates of the first bit field value are in hexadecimal with a total of 16 types. The range of the first bit field value is 0 - F. The first bit field value is used to determine the sub-regions where multiple specific particles are located through a provided Lookup Table 1, which is set by the user himself. The Lookup Table 1 contains the first bit field value and the labels of the sub-regions where multiple specific particles corresponding to the first bit field value are located. The central coordinates of each specific particle are represented by a 6-digit hexadecimal number, where the first 3 digits are the abscissa and the last 3 digits are the ordinate. The selection rule for the specific particles is as follows: Number them in sequence from left to right along the X-axis and from top to bottom along the Y-axis. When the serial number is odd, add 1 to the odd number and then divide by 2; when the serial number is even, directly divide by 2. The resulting number is the serial number of the center dot of the specific particle to be taken, and the coordinates of the center dot of this specific particle are taken out and compiled into the coding table. For example, when the value of the first bit field value is 1, it is necessary to take the coordinates of the center dots of the specific particles in the four sub-region grids numbered 1, 2, 7, and 9. The lower left corner is the origin coordinate, which is 000. Every 6 digits form a group of coordinate values, with a total of 4 groups. The first three digits of each group are the abscissa, and the last three digits are the ordinate. The numerical ranges of the abscissa and ordinate are both 000 - FFF.

[0030] The above verification code encoding forms a string of codes composed of numbers and English letters (including upper and lower cases) through a complete set of encryption algorithms and operation rules. This embodiment has a 21-bit information code, a 21-bit check code, and a 25-bit coordinate code, which finally form a ciphertext / plaintext code of no less than 50 bits and are printed synchronously on the medium carrier, including but not limited to being printed on the top, bottom, left, and right of the pattern or on the pattern itself. This technical solution can either transpose all the data from 0 - F through a self-set Lookup Table 2 to become ciphertext, or use the national secret SM4 encryption algorithm to convert the above plaintext into ciphertext. Among them, this embodiment does not convert the ciphertext through Lookup Table 2. Lookup Table 2 is only an example of primary encryption.

[0031] As Figure 4 shown, the Hough transform algorithm of this embodiment includes the following steps: (1) Perform grayscale conversion, Gaussian blur, and Canny edge detection on the verification area image; (2) Detect the center coordinates and radius of the colored particles through the Hough gradient method, and screen the particles that meet the preset radius range; (3) Convert the detection result into the original image coordinate system and record the number and position of the particles.

[0032] The following is a part of the program for extracting the center coordinates of small particles: import cv2 import numpy as np def draw_rectangle_and_extract_circles(image_path, points): # Read the image image = cv2.imread(image_path) # Ensure that the input points are a list containing four points if len(points) != 4: raise ValueError("Please provide the coordinates of four points.") #points = [(49, 63), (323, 67), (43, 353), (317, 357)] # Get the top-left and bottom-right coordinates of the rectangle top_left = (min(points[0][0], points[1][0]), min(points[0][1],points[1][1])) bottom_right = (max(points[2][0], points[3][0]), max(points[2][1],points[3][1])) # Draw the rectangle cv2.rectangle(image, top_left, bottom_right, (0, 255, 0), 2) # Extract the rectangular region roi = image[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]] # Convert to grayscale image gray_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY) # Blur the grayscale image to reduce noise gray_roi = cv2.GaussianBlur(gray_roi, (5, 5), 0) # Use Canny edge detection edges = cv2.Canny(gray_roi, 50, 150) # Morphological operation: dilation kernel = np.ones((3, 3), np.uint8) dilated_edges = cv2.dilate(edges, kernel, iterations=1) # Create a mask mask = np.zeros(gray_roi.shape, dtype=np.uint8) cv2.rectangle(mask, (0, 0), (gray_roi.shape[1], gray_roi.shape[0]),(255), thickness=-1) # Apply the mask masked_edges = cv2.bitwise_and(dilated_edges, dilated_edges, mask=mask) # Display the edge image cv2.imshow('Masked Edges', masked_edges) # Detect circles using the Hough Circle Transform circles = cv2.HoughCircles(masked_edges, cv2.HOUGH_GRADIENT, dp=1,minDist=10, param1=30, param2=10, minRadius=1, maxRadius=15) # Store the coordinates of the centers of the qualified circles circle_centers = [] if circles is not None: circles = np.uint16(np.around(circles)) for i in circles[0, :]: radius = i[2] if radius>1: # Only extract circles with a radius greater than 1 # Calculate the coordinates of the center in the original image center = (i[0] + top_left[0], i[1] + top_left[1]) # Convert to the coordinates of the original image circle_centers.append(center) # Mark the center of the circle on the image cv2.circle(image, center, 10, (255, 0, 0), -1) # Draw the center of the circle with a radius of 10 and color it blue # Display the result image cv2.imshow('Result', image) cv2.waitKey(0) cv2.destroyAllWindows() # Example call image_path = 'C:\\Users\\w\\Desktop\\tu1.jpg' points = [(69, 83), (303, 87), (63, 333), (297, 337)] 1. Basic idea of the Hough transform The Hough transform is a feature extraction technique used to detect specific shapes (such as lines, circles, etc.) in an image. For circle detection, the Hough transform maps a circle in the image space to a point in the parameter space, which is determined by the center coordinates (a, b) and the radius r. Specifically, a circle in the image space corresponds to a point in the parameter space, and multiple points in the image space that lie on the same circle will intersect at the same point in the parameter space.

[0033] 2. Construction of the parameter space In the Hough transform, the parameter space is usually a three-dimensional space representing the abscissa a, ordinate b of the center of the circle, and the radius r. For each edge point in the image, the Hough transform will traverse all possible centers of the circle and radii and accumulate the corresponding points in the parameter space. If multiple edge points lie on the same circle, their accumulator values in the parameter space will increase significantly, forming a peak.

[0034] 3. Accumulator and voting mechanism The Hough transform uses an accumulator array to count the number of votes for each possible circle. For each edge point in the image, the Hough transform will calculate all possible centers of the circle and radii and increment the corresponding position in the accumulator by 1. Finally, the parameters (a, b, r) corresponding to the point with the largest value in the accumulator are the parameters of the circle existing in the image.

[0035] 4. Optimization of the Hough gradient method To improve the computational efficiency, the Hough gradient method is used in OpenCV to optimize the standard Hough circle transform. The Hough gradient method first calculates the gradient of the image through Canny edge detection and the Sobel operator, then draws lines along the gradient direction to count the possible centers of the circles. Next, the radius is determined by calculating the distance from the edge points to the center of the circle. This method reduces the computational amount and improves the detection speed.

[0036] A method for generating the three-dimensional code element label includes the following steps: S1: Prepare a medium carrier, form a substrate of the medium carrier through a printing process, and print a positioning pattern on the surface of the substrate of the medium carrier to delimit a verification area; S2: Randomly distribute colored particles on the surface of the medium carrier through a relief printing process to form a three-dimensional pattern with a concave-convex touch; S3: Use the Hough transform algorithm to extract the quantity, position, and central coordinate information of the colored particles in the three-dimensional pattern; S4: Generate a verification code according to the extracted information. The verification code includes information encoding, check encoding, and coordinate encoding, and print the verification code on the medium carrier.

[0037] A method for verifying the three-dimensional code element label includes the following steps: S1: Obtain a label image through machine vision recognition technology, recognize the positioning pattern and delimit a verification area; S2: Recognize the information encoding, check encoding, and coordinate encoding in the verification area, and parse out the quantity, position, and central coordinate information of the particles of the three-dimensional pattern included in the verification code encoding; S3: Use the Hough transform algorithm to extract the quantity, position, and central coordinate information of the particles of the three-dimensional pattern in the verification area; S4: Compare and verify the extracted information with the data parsed from the verification code. If they are consistent, it is determined to be true; otherwise, it is determined to be false.

[0038] The comparison and verification include: In the online mode, compare the extracted label image with the original generated image in the database; In the offline mode, inversely deduce the particle quantity and position information through the verification code, and compare it with the value extracted from the current image.

[0039] A verification method for three-dimensional code element labels includes the following steps: (1) Obtain a label image through machine vision recognition technology, recognize the positioning pattern, and delimit a verification area; (2) Recognize the information encoding, check encoding, and coordinate encoding in the verification code area, and parse out the number of particles, positions, and central coordinate information of the three-dimensional pattern contained in the encoding; (3) Use the Hough transform algorithm to extract the number of particles, positions, and central coordinate information of the three-dimensional pattern in the verification area; (4) Compare and verify the extracted information with the data parsed from the verification code. If they are consistent, it is determined to be true; otherwise, it is determined to be false.

[0040] The comparison and verification of this three-dimensional code support online or offline verification. During online verification, after reading / taking a photo of the label, the photo to be compared and read can also be transmitted to the background, and the pattern is read in reverse / forward. At the same time, the information such as the position of the label in the photo is parsed and compared with the verification code, and then the photo taken when the label was generated is queried for comparison to determine the authenticity of the label, and the verification result is returned; during offline verification in a network-free environment, only the photo is parsed, the verification code is checked, and the number of particles and the position information of specific particles contained in the label pattern are deduced from the verification code and compared with the pattern to determine the authenticity of the label. The three-dimensional characteristics of the pattern can be verified through the touch feeling or a binocular camera to prevent the possibility of scanning or printing counterfeit patterns.

[0041] The three-dimensional code element label first uses randomly printed colored small particles to form a concave-convex circular pattern with a scattered distribution. According to the center points of the pre-printed positioning circles, a coordinate map of the verification area is formed. Then, an optimized Hough transform algorithm for detecting the circle contour is used, and with machine vision recognition technology, the number of colored small particles in the verification area and the center coordinates of each small dot are recognized and recorded. After encoding and encrypting the above information according to the formulated coding rules, it is printed on the second and third lines of the verification code area. During verification, first, use machine vision recognition technology to recognize the encoding on the second and third lines of the verification code area, and parse out the number information of relevant colored small particles in the verification area, the position information of specific particles, etc. contained in the encoding; then, use the same optimized Hough transform algorithm for detecting the circle contour to extract the number of small particles and the center coordinates of each small dot of the concave-convex circular pattern, and compare the extracted values with the values parsed from the encoding on the second and third lines. If the comparison result is true, it is determined that the label (pattern + verification code) is consistent with the production and has not been counterfeited; if the comparison result is false, it is determined that the label has been forged and is inconsistent with the production. The three-dimensional code element label utilizes the randomness and extremely difficult to repeat consistency of the distribution pattern of colored particles during printing to achieve the self-antiforgery function with the number and position coordinates of the particles.

[0042] The application scenarios of this three-dimensional code element label include the following: Scenario identifiers such as place of origin, packaging, time, etc. For example, the proof of goods when overseas shopping agents purchase goods, and the labels of the country of origin of foreign fruits, beef, red wine, etc.; Identify the scenarios where what you see is what you get. For example, the proof of the consistency between the inspected products and the shipped products of second-hand luxury goods, the place of origin of special agricultural products, the proof of processing (harvesting) time, etc.; Identify that the manufacturer promotes its own characteristic brand products; Identify the application scenarios of the metaverse, the metaverse scenarios; Identify existing products with one-dimensional barcodes to ensure that the actual products correspond one-to-one with the codes, forming a single anti-counterfeiting and traceability code; Identify the applicable scenarios of existing two-dimensional codes, corresponding one-to-one with the two-dimensional codes for anti-counterfeiting and traceability.

[0043] Compared with the prior art, the present invention has the following advantages: 1. Extremely high anti-counterfeiting security Physical anti-counterfeiting: Use randomly distributed colored particles to form a three-dimensional pattern with concave-convex touch. The particle distribution of each label is unique and non-replicable, and it cannot be imitated by scanning, copying or printing.

[0044] Encryption anti-counterfeiting: Accurately extract the particle position information through an optimized Hough transform algorithm, and combine with the SM4 national secret encryption algorithm to generate a high-strength verification code to ensure that the code cannot be tampered with or forged.

[0045] Multiple verification mechanisms: Support online verification + offline verification + touch verification to form a multi-level anti-counterfeiting system.

[0046] 2. High-precision machine recognition ability Optimize the detection accuracy of the particle center by the improved Hough gradient method, combine Canny edge detection + Sobel gradient calculation to improve the recognition accuracy of tiny particles. Use grid division to verify the area, and record the number and coordinates of particles in each partition to make the error tolerance rate of machine vision recognition higher and reduce misjudgment.

[0047] 3. Flexible application adaptability Compatible with multiple media: Can be printed on various carriers such as paper, plastic, metal, textiles, etc. to meet the needs of different industries.

[0048] Support multiple verification methods: Online verification: applicable to high-value goods (such as luxury goods, imported food), can combine blockchain technology to ensure the immutability of data. Offline verification: applicable to environments without network (such as remote areas), only need to take a photo to complete the verification. Tactile verification: users can detect concave and convex tactile sensations through touch or binocular cameras to quickly distinguish between genuine and fake. Obviously, the above embodiments of the present invention are only examples for explaining the present invention, and are not limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or variations can be made based on the above description. It is not necessary and impossible to list all implementation manners here. And these obvious changes or variations derived from the essential spirit of the present invention still fall within the protection scope of the present invention.

Claims

1. A three-dimensional code element label with a self-anti-counterfeiting function, characterized in that, It includes the following parts: A medium carrier, which is formed by a standard printing process. On the surface of the medium carrier, there are at least three positioning patterns with regular geometric shapes randomly. The central coordinates of multiple said positioning patterns can be constructed into a verification area in a square structure, and the verification area is evenly divided into multiple sub-areas; A three-dimensional code pattern, which is formed by randomly fixing colored particles on the surface of the medium carrier after mixing with glue through a relief printing process. The three-dimensional code pattern has a three-dimensional concave-convex touch feeling. The colored particles are randomly distributed in the verification area, and the particle size of the colored particles is 0.1 - 5.5 mm; A verification code area, including three rows of verification code encodings: The first row of verification codes, containing more than 13-bit information encodings. Multiple said information encodings include one or more items of information such as enterprise codes, production times, or production serial numbers; The second row of verification codes, containing more than 21-bit check encodings. Multiple said check encodings include the total number encoding of particles in the verification area, the particle number encoding of each sub-area, and an anti-counterfeiting verification encoding. The anti-counterfeiting verification encoding is generated by an encryption algorithm based on the existing encodings; The third row of verification codes, containing more than 25-bit coordinate encodings. Multiple said coordinate encodings include the first-bit domain value and the central coordinates of more than 4 specific particles. The first-bit domain value is used to determine the sub-area where multiple specific particles are located. The number of specific particles is more than 4, and the coordinate information is extracted and encoded through the Hough transform algorithm; The verification code encodings are displayed in plain text or in ciphertext through an encryption algorithm.

2. The three-dimensional code element label with a self-anti-counterfeiting function according to claim 1, wherein: The positioning pattern is any one of a circle, a triangle, a square, or a rectangle. When the positioning pattern is a circle, its diameter is more than one time the average diameter of the colored particles; when the positioning pattern is a polygon, its minimum side length is more than one time the average diameter of the colored particles.

3. A three-dimensional code element label with a self - anti - counterfeiting function according to claim 1, wherein: The first check encoding in the second row of verification codes is a division encoding used to determine the equal - division type of the verification area, and the division encoding is greater than zero; The total number encoding of particles in the verification area, with more than 2 bits, used to represent the total number value of colored particles in the verification area; The particle number encoding of the area, with more than 18 bits, representing the number of particles in each sub - area of the multiple sub - areas divided by the verification area. The particle number is encoded in decimal or hexadecimal; The anti - counterfeiting verification code, with more than 4 bits, is generated by extracting part of the hash value through a hash operation on the foregoing encodings.

4. A three-dimensional code element label with a self - anti - counterfeiting function according to claim 3, wherein: The verification code of the third row includes the first bit field value and the central coordinates of more than 4 specific particles. The coordinates of the first bit field value are in hexadecimal, with a total of 16 types. The range of the first bit field value is 0 - F. The first bit field value is used to determine the sub-region where multiple specific particles are located through the provided Lookup Table 1, which is set by the user himself. The Lookup Table 1 contains the first bit field value and the labels of the sub-regions where multiple specific particles corresponding to the first bit field value are located; The central coordinates of each specific particle are represented by a 6-digit hexadecimal number, where the first 3 digits are the abscissa and the last 3 digits are the ordinate. The selection rule for the specific particles is as follows: Number them from left to right along the X-axis coordinate and from top to bottom along the Y-axis coordinate. When the serial number is odd, add 1 to the odd number and then divide by 2; When the serial number is even, divide it directly by 2. The resulting number is the serial number of the central dot of the specific particle to be taken, and the coordinates of the central dot of this specific particle are taken out and compiled into the coding table.

5. A three-dimensional code element label with a self - anti - counterfeiting function according to claim 1, characterized in that: The Hough transform algorithm includes the following steps: (1) Perform grayscale conversion, Gaussian blur, and Canny edge detection on the verification area image; (2) Detect the center coordinates and radius of the colored particles through the Hough gradient method, and screen the particles that meet the preset radius range; (3) Convert the detection result into the original image coordinate system, and record the number and position of the particles.

6. A three-dimensional code element label with a self - anti - counterfeiting function according to claim 1, characterized in that: The encryption algorithm uses symmetric encryption, asymmetric encryption, hybrid encryption system, national encryption algorithm, or hash algorithm to generate ciphertext encoding.

7. A three-dimensional code element label with a self - anti - counterfeiting function according to claim 1, characterized in that: The label is applied to the identification of the origin of goods, anti - counterfeiting certification, meta - universe scene mapping, or the scene of uniquely encoding and binding with one - dimensional codes and two - dimensional codes.

8. A method for generating a three - dimensional code element label according to any one of claims 1 - 7, comprising the following steps: S1: Prepare a medium carrier, form a medium carrier substrate through a printing process, and print a positioning pattern on the surface of the medium carrier substrate to delimit the verification area; S2: Randomly distribute colored particles on the surface of the medium carrier through a relief printing process to form a three - dimensional pattern with a concave - convex touch; S3: Use the Hough transform algorithm to extract the number, position, and central coordinate information of the colored particles in the three - dimensional pattern; S4: Generate a verification code according to the extracted information. The verification code includes information encoding, check encoding, and coordinate encoding, and print the verification code on the medium carrier.

9. A method for verifying a three - dimensional code element label according to any one of claims 1 - 7, comprising the following steps: S1: Obtain a label image through machine vision recognition technology, identify the positioning pattern and delimit the verification area; S2: Identify the information encoding, check encoding, and coordinate encoding in the verification area, and parse out the number, position, and central coordinate information of the particles in the three - dimensional pattern included in the verification code encoding; S3: Use the Hough transform algorithm to extract the number, position, and central coordinate information of the particles in the three - dimensional pattern in the verification area; S4: Compare and verify the extracted information with the data parsed from the verification code. If they are consistent, it is determined to be true; otherwise, it is determined to be false.

10. The verification method of the three-dimensional code element label according to claim 9, wherein The comparison and verification include: In the networked mode, compare the extracted label image with the original generated image in the database; in the offline mode without network, reverse-infer the particle quantity and position information through the verification code, and compare it with the value extracted from the current image.

Images