A preparation method and identification method and system for commodity identity information label

Abstract

The present invention relates to a method for preparing and identifying a product identity information tag, and a method and system for identifying the tag. The identification method comprises the following steps: forming a metallographic tag; establishing a product identity database based on the metallographic tags of different products; receiving a user's metallographic tag identification request, extracting the metallographic tag of the product to be tested, performing a matching search, and returning an authenticity identification result. This identification method uses the microscopic metallographic structure of the metal material as an identifier, which is stable, unique, and non-replicable. It is also adaptable to a wide range of products and applications, and is low-cost. The system uses an image search algorithm to identify and match the metallographic tag, and when used in conjunction with barcodes and QR codes, it achieves high search efficiency and is easy to identify.

Description

Technical Field

[0001] The present invention belongs to the technical field of commodity identification, and in particular relates to a method for preparing a commodity identity information label and an identification method and system. Background Art

[0002] In modern society, product identification and anti-counterfeiting are key factors in commercial circulation, especially for valuable commodities such as famous cigarettes and liquors, luxury brand clothing and bags, luxury watches, etc. These commodities are currently identified by anti-counterfeiting codes, radio frequency tags, etc. Artificially created acquired identification objects are easy to forge and are not unique.

[0003] Phase composition, grain size, grain distribution, and grain boundaries are key natural characteristics of materials. For example, the martensite, austenite, cementite, and pearlite present in the steel and stainless steel we use daily are all components of the material's basic grains. Nucleation conditions and subsequent growth are key factors in the formation of basic grains, resulting in grains of varying sizes and specific shapes. Leveraging the inherent metallographic characteristics of metal materials for identification is fundamentally different from current artificially manufactured anti-counterfeiting and identity labels, offering advantages such as uniqueness, irreproducibility, and ease of identification.

[0004] Traditional metallographic formation generally uses sample inlay to form inlays. For product identification, this method cannot meet the needs of large quantities of products and the continuity of product production. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for preparing and identifying a commodity identity information label in order to solve the above problems.

[0006] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0007] A method for preparing a product identity information label comprises the following steps:

[0008] Step S1: Preselect an inseparable metal region M in the product body, grind, polish, and etch the surface of the metal region M in sequence to obtain a metal region N;

[0009] Step S2: Clean the corroded area on the surface of the metal area N with clean water, then preheat the metal area N and blow hot air with inert gas to remove residual water;

[0010] Step S3: using a vacuum suction cup to extract air from the corroded area on the surface of the metal area N;

[0011] Step S4: using transparent glass or transparent resin to seal and cover the corroded area of the metal area N to obtain the metal area P. The transparent and sealed corroded area on the surface of the metal area P is the metallographic mark.

[0012] The present invention also proposes a method for identifying the above-mentioned commodity identity information mark, comprising the following steps:

[0013] Step C1: establishing a commodity identity database based on metallographic identifications of different commodities, wherein the commodity identity database includes original images based on metallographic identifications;

[0014] Step C2: Receive a request for product metallographic identification sent by the user, extract the metallographic identification of the product to be detected, form an image to be matched, and perform a matching search on images under different image modes based on an image matching algorithm, and return the result of identifying the authenticity. The image matching search for images under different image modes based on the image matching algorithm includes: using an alignment search algorithm to search and match images with near-translation, no rotation, and no scaling, and using a non-alignment search algorithm to process images with translation, rotation, and scaling.

[0015] As a further optimization solution of the present invention, the establishment of the identity database in step C1 specifically includes the following steps:

[0016] Step C1.1: Use a light source to illuminate the metallographic marking area of the product;

[0017] Step C1.2: Use a microscopic imaging camera to capture the metallographic markings of the product and generate an image X;

[0018] Step C1.3: Convert the generated image X into a digital image Y. Aggregate all digital images Y of the same product to create an identity database to form the original image.

[0019] As a further optimization solution of the present invention, the identification process of step C2 specifically includes the following steps:

[0020] Step C2.1: The user initiates a metallographic identification request. The user first captures the product's QR code or barcode information to determine the product type and narrow the search scope. The user then captures the product's metallographic identification and obtains a complete metallographic identification image of the product. If the metallographic identification is incomplete, a partial metallographic identification image is captured. The captured metallographic identification image is digitized to form the image to be matched.

[0021] Step C2.2: Send the image to be matched to the identity database and initiate a recognition request;

[0022] Step C2.3: Determine whether the image pattern of the image to be matched is a nearly translated image without rotation or scaling. If so, use an alignment search algorithm to search and match the image to be matched with the original image in the identity database. If the image pattern is a nearly translated image without rotation or scaling, use a non-alignment search algorithm to search and match the image to be matched with the original image in the identity database.

[0023] Step C2.4: Return the result of authenticity identification after matching.

[0024] As a further optimization solution of the present invention, if the image is nearly translated without rotation or scaling, an alignment search algorithm is used to search and match the image to be matched with the original image in the identity library. The specific process is as follows: assuming that the resolution of the original image A is m×n and the resolution of the image to be matched B is v×w, the following steps are performed:

[0025] Step L1: Set a sliding window with a resolution of v×w. The number of times the image B to be matched can slide on the original image A is: (m-v+1)×(n-w+1);

[0026] Step L2: The image to be matched B starts to slide on the original image A, sliding pixel by pixel from the origin of the original image A. The similarity between the original image A and the image to be matched B is calculated once each slide. The similarity is the Euclidean distance value. The smaller the Euclidean distance value, the higher the similarity. There are a total of (m-v+1)×(n-w+1) values.

[0027] Step L3: Find the minimum value from the (m-v+1)×(n-w+1) Euclidean distance values, and the corresponding window is the best matching area.

[0028] As a further optimization solution of the present invention, if the image is translated, rotated, and scaled, a non-aligned search algorithm is used to search and match the image to be matched with the original image in the identity library. The process includes: assuming that the resolution of the original image A is m×n and the resolution of the image to be matched B is v×w, the following steps are implemented:

[0029] Step R1: Calculate the Surf features of the original image A and the image to be matched B;

[0030] Step R2: Use the Surf features of the original image A and the image to be matched B to obtain the transformation matrix H;

[0031] Step R3: Generate an image with all zeros, the image size is the same as the original image A, let this image be C;

[0032] Step R4: transform the image B to be matched to the image C according to the transformation matrix H, set the grayscale values of the image B to be matched to 255, and set the transformed image to be image D;

[0033] Step R5: The area in image D that is all 255 values is the matching area.

[0034] The present invention also provides a commodity identity information recognition system for implementing the recognition process, the recognition system comprising the following subsystems:

[0035] Metallographic formation subsystem: used to process the inseparable metal area of the product itself to form metallographic identification;

[0036] Imaging subsystem: used to collect and record the metallographic marks generated for products, and also used to collect metallographic marks for subsequent product identification and appraisal;

[0037] Identity database identification subsystem: used to search and match the collected metallographic identification of the product to be tested with the original metallographic identification in the product identity database to identify the authenticity.

[0038] As a further optimization solution of the present invention, the metallographic formation subsystem includes:

[0039] Surface pretreatment module, used to clean the surface of the metallographic formation area and remove dirt;

[0040] A grinding and polishing module is used to polish the surface of the metallographic formation area;

[0041] Etching module, used to etch out the grains and grain boundaries in the marked area;

[0042] Cleaning module, used to remove corrosion solution and water stains;

[0043] Drying and deoxidation module, used to remove water molecules and oxygen molecules on the surface of the metallographic formation area;

[0044] Covering and sealing module, used to seal the corroded area and isolate it from the air;

[0045] Auxiliary modules for additional auxiliary processes, including checking for defective products.

[0046] As a further optimization solution of the present invention, the imaging subsystem includes:

[0047] Metallographic imaging camera, used to capture metallographic identification of goods;

[0048] Ordinary imaging camera, used to collect QR code or barcode information of products;

[0049] The metallographic imaging light source and the ordinary imaging light source are used to provide light sources for the metallographic display imaging camera and the ordinary imaging camera respectively;

[0050] The imaging subsystem also includes a processor, a memory and a communication unit, wherein the processor is used to complete data reception and light source control of the metallographic display imaging camera and the ordinary imaging camera, and digitize the metallographic identification image to form the original image or the image to be matched, and store it in the memory; the communication unit is used to exchange data with the identity library recognition subsystem.

[0051] As a further optimization solution of the present invention, the identity database recognition subsystem includes:

[0052] An identity database building module, configured to receive an original image from the imaging subsystem;

[0053] An identity recognition module, configured to receive an image to be matched from the imaging subsystem;

[0054] The data processing module is used to search and match the image to be matched with the original image, identify the authenticity of the image to be matched, and complete the sending, receiving and access of data;

[0055] The identity library recognition subsystem also includes a storage module, a network transmission module and a database, wherein the network transmission module interacts with the imaging subsystem for data and stores the data in the database through the storage module, and the storage module is used to complete the storage and reading process of the original image and the image data to be matched.

[0056] The beneficial effects of the present invention are:

[0057] (1) The present invention uses the microscopic metallographic structure of metal materials as an identifier, which is stable, unique, and non-replicable. The process of metal transformation from liquid to solid is its solidification process. The solidification process can be considered as a transition from a liquid disordered atomic state to an ordered state at the atomic level. This process is a transition from a disordered metal atomic group to a solid structure arranged according to certain rules.

[0058] (2) The present invention is applicable to a wide range of commodities and applications. For example, the bottle caps of alcoholic products are often made of aluminum alloy materials. At the same time, the bottle caps are parts that must be removed before the product can be used. Therefore, it is very suitable to use the metal metallographic structure of the bottle cap itself to form a unique metallographic mark. For luxury luggage, metallographic marks can be formed on metal parts such as metal zippers, metal buckles, and rivets.

[0059] (3) The present invention is low-cost and does not occupy too much area and volume. For commonly used metal materials, an area with a diameter of 1 mm is sufficient to complete the observation, imaging, and identification of the metallographic area. Therefore, the area occupied by the product itself is very small.

[0060] (4) The metallographic marking process of the present invention is simple and easy to be inserted into the production line. Because the surface area to be marked is very small, each link is integrated into a piece of equipment and can be freely inserted into the existing product production process.

[0061] (5) The present invention adopts a multi-dimensional information fusion method to achieve the purpose of rapid identification, and uses the information attached to the product itself to form a multi-dimensional information fusion as much as possible, so as to gradually narrow the search scope and improve the search efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a subsystem diagram of the metallographic formation process of the present invention;

[0063] Figure 2 It is a flow chart of the use process of the present invention;

[0064] Figure 3 is a diagram of the imaging subsystem of the present invention;

[0065] Figure 4 is a diagram of the identity database and identification subsystem of the present invention;

[0066] Figure 5 This is a schematic diagram of the general imaging and microscopic imaging device of the present invention. Figure 1 ;

[0067] Figure 6 This is a schematic diagram of the general imaging and microscopic imaging device of the present invention. Figure 2 ;

[0068] Figure 7 The recessed sign area of the present invention is covered with transparent glass;

[0069] Figure 8 The concave marking area of the present invention is covered with a transparent resin;

[0070] Figure 9 The outer convex logo area of the present invention is covered with transparent glass;

[0071] Figure 10 The outer convex marking area of the present invention is covered with a transparent resin;

[0072] In the figure: 10 metallographic formation subsystem; 100 surface pretreatment module; 101 polishing module; 102 corrosion module; 103 cleaning module; 104 drying and deoxidation module; 105 covering and sealing module; 106 auxiliary module; 150 metallographic area; 151 metallographic identification; 152 transparent glass; 153 transparent resin; 154 glass fixing part; 20 imaging subsystem; 200 general imaging light source; 201 general imaging camera; 202 general imaging subunit; 203 metallographic imaging light source; 204 metallographic imaging microscope; 205 metallographic microscope imaging objective lens; 206 metallographic microscope imaging eyepiece; 207 metallographic microscope imaging tube; 208 metallographic microscope imaging camera; 209 metallographic display imaging subunit; 220 metallographic white light LED; 221 metallographic ultraviolet LED; 222 metallographic green light LED; 223 Processor; 224 communication unit; 225 memory; 30 identity database and identification subsystem; 300 identity database establishment module; 301 identity identification module; 302 data storage module; 303 network transmission module; 304 data processing module; 305 database. DETAILED DESCRIPTION

[0073] The present application is described in further detail below in conjunction with the accompanying drawings. It is necessary to point out that the following specific implementation methods are only used to further illustrate the present application and cannot be understood as limiting the scope of protection of the present application. Technicians in this field can make some non-essential improvements and adjustments to the present application based on the above application content.

[0074] Example 1

[0075] like Figure 1-10 As shown:

[0076] A method for preparing a product identity information label comprises the following steps:

[0077] Step S1: Preselect an inseparable metal region M in the product body, grind, polish, and etch the surface of the metal region M in sequence to obtain a metal region N;

[0078] Step S2: Clean the corroded area on the surface of the metal area N with clean water, then preheat the metal area N and blow hot air with inert gas to remove residual water;

[0079] Step S3: using a vacuum suction cup to extract air from the corroded area on the surface of the metal area N;

[0080] Step S4: using transparent glass or transparent resin to seal and cover the corroded area of the metal area N to obtain the metal area P. The transparent and sealed corroded area on the surface of the metal area P is the metallographic mark.

[0081] Among them, the inseparable metal area M is the part of the product that cannot be disassembled. For example, the bottle cap of a wine bottle is often made of aluminum alloy. At the same time, the bottle cap is the part that must be removed before the product can be used. Therefore, it is very suitable to use the metal metallographic structure of the bottle cap itself to form a unique metallographic identification. For luxury luggage, metallographic identification can be formed on metal parts such as metal zippers, metal buckles, and rivets. The metallographic identification area is less than 1mm in diameter and will not affect the appearance integrity of the product itself.

[0082] The printing and printing equipment currently used all use dpi as the output resolution. Currently, the highest resolution for both inkjet and laser printing is 9600dpi, which means that the distance between each dot is 2.6458um. The spacing between grain boundaries or internal grain structures in metallographic identification is much smaller than this value. Therefore, it is impossible to fully print or print out the resolution of the metallographic identification using current printing technology, so the metallographic identification cannot be imitated.

[0083] The present invention also proposes a method for identifying the above-mentioned metallographic mark, comprising the following steps:

[0084] Step C1: establishing a commodity identity database based on metallographic identifications of different commodities, wherein the commodity identity database includes original images based on metallographic identifications;

[0085] Step C2: Receive a request for product metallographic identification sent by the user, extract the metallographic identification of the product to be detected, form an image to be matched, and perform a matching search on images under different image modes based on an image matching algorithm, and return the result of identifying the authenticity. The image matching search for images under different image modes based on the image matching algorithm includes: using an alignment search algorithm to search and match images with near-translation, no rotation, and no scaling, and using a non-alignment search algorithm to process images with translation, rotation, and scaling.

[0086] The step C1 of establishing the identity database specifically includes the following steps:

[0087] Step C1.1: Use a light source to illuminate the metallographic marking area of the product;

[0088] Step C1.2: Use a microscopic imaging camera to capture the metallographic markings of the product and generate an image X;

[0089] Step C1.3: Convert the generated image X into a digital image Y. Aggregate all digital images Y of the same product to create an identity database to form the original image.

[0090] Among them, the external light source that is as consistent as possible is required during the metallographic identification collection process. Generally, white light source is used for metallographic identification collection. According to the different metal materials of the customer's identification products, the light source adopts white light, ultraviolet light and green light to work independently or in combination to complete the reliable identification and imaging of metallographic identification on the surfaces of various different materials.

[0091] The identification process of step C2 specifically includes the following steps:

[0092] Step C2.1: The user initiates a metallographic identification request. The user first captures the product's QR code or barcode information to determine the product type and narrow the search scope. The user then captures the product's metallographic identification and obtains a complete metallographic identification image of the product. If the metallographic identification is incomplete, a partial metallographic identification image is captured. The captured metallographic identification image is digitized to form the image to be matched.

[0093] Step C2.2: Send the image to be matched to the identity database and initiate a recognition request;

[0094] Step C2.3: Determine whether the image pattern of the image to be matched is a nearly translated image without rotation or scaling. If so, use an alignment search algorithm to search and match the image to be matched with the original image in the identity database. If the image pattern is a nearly translated image without rotation or scaling, use a non-alignment search algorithm to search and match the image to be matched with the original image in the identity database.

[0095] Step C2.4: Return the result of authenticity identification after matching.

[0096] If the image is a near-translation image without rotation or scaling, an alignment search algorithm is used to search and match the image to be matched with the original image in the identity database. Assuming the resolution of the original image A is m×n and the resolution of the image to be matched B is v×w, the following steps are performed:

[0097] Step L1: Set a sliding window with a resolution of v×w. The number of times the image B to be matched can slide on the original image A is: (m-v+1)×(n-w+1);

[0098] Step L2: The image to be matched B starts to slide on the original image A, sliding pixel by pixel from the origin of the original image A. The similarity between the original image A and the image to be matched B is calculated once each slide. The similarity is the Euclidean distance value. The smaller the Euclidean distance value, the higher the similarity. There are a total of (m-v+1)×(n-w+1) values.

[0099] Step L3: Find the minimum value from the (m-v+1)×(n-w+1) Euclidean distance values, and the corresponding window is the best matching area.

[0100] If the image is translated, rotated, and scaled, a non-aligned search algorithm is used to search and match the image to be matched with the original image in the identity library. Assume that the resolution of the original image A is m×n and the resolution of the image to be matched B is v×w. This is achieved through the following steps:

[0101] Step R1: Calculate the Surf features of the original image A and the image to be matched B;

[0102] Step R2: Use the Surf features of the original image A and the image to be matched B to obtain the transformation matrix H;

[0103] Step R3: Generate an image with all zeros, the image size is the same as the original image A, let this image be C;

[0104] Step R4: transform the image B to be matched to the image C according to the transformation matrix H, set the grayscale values of the image B to be matched to 255, and set the transformed image to be image D;

[0105] Step R5: The area in image D that is all 255 values is the matching area.

[0106] In actual use, when a customer initiates a metallographic identification request, a fast identification system can also be built using multi-dimensional information fusion:

[0107] Method 1: Product name plus metallographic area identification;

[0108] Method 2: Combination of product name, production date and metallographic area identification;

[0109] Method 3: Combination of product name, product serial number and metallographic area identification.

[0110] In the above methods, the product name can be obtained by the user taking pictures of the product packaging information, the existing barcode on the product, the existing QR code, etc. The metallographic identification is collected by using a dedicated camera together with the metallographic identification of the product. By combining the QR code with the metallographic identification, the information attached to the product body is used to form a multi-dimensional information fusion, so as to gradually narrow the search scope.

[0111] At the same time, the identification of metallographic marks can also be carried out by combining explicit metallography and invisible metallography. Printing and spraying can be directly performed using printing coatings, etc., to prevent oxidation and rust in the metallographic mark area. When performing identification, the surface covering can be removed and cleaned to re-collect the metallographic mark.

[0112] According to an embodiment of the present invention, the present invention further proposes a commodity identity information recognition system, which includes the following subsystems:

[0113] Metallographic formation subsystem 10: used to process the inseparable metal area of the product itself to form a metallographic mark;

[0114] Imaging subsystem 20: used to collect and record the metallographic marks generated for commodities, and also used to collect metallographic marks for subsequent commodity identification and appraisal;

[0115] The identity database recognition subsystem 30 is used to search and match the collected metallographic identification of the commodity to be tested with the original metallographic identification in the commodity identity database to identify the authenticity.

[0116] The metallographic formation subsystem 10 includes:

[0117] The surface pretreatment module 100 is used to clean the surface of the metallographic formation area and remove dirt;

[0118] A grinding and polishing module 101 is used to polish the surface of the metallographic formation area;

[0119] Etching module 102, used for etching out the grains and grain boundaries of the marked area;

[0120] Cleaning module 103, used to remove the solution and water stains after corrosion;

[0121] Drying and deoxidation module 104, used to remove water molecules and oxygen molecules on the surface of the metallographic formation area;

[0122] The covering and sealing module 105 is used to seal the corroded area and isolate it from the air;

[0123] The auxiliary module 106 is used for additional auxiliary processes, including checking whether there are defective products.

[0124] like Figure 7-10 In the metallographic subsystem, the metallographic identification can be produced in the following forms according to the actual needs of the product: transparent glass covering of the concave identification area, transparent resin covering of the concave identification area, transparent glass covering of the convex identification area, and transparent resin covering of the convex identification area.

[0125] The imaging subsystem 20 includes:

[0126] A metallographic imaging camera 204 is used to capture metallographic identification of the product;

[0127] A common imaging camera 200 is used to collect the QR code or barcode information of the product;

[0128] The metallographic imaging light source 203 and the common imaging light source 201 are used to provide light sources for the metallographic display imaging camera 204 and the common imaging camera 200 respectively;

[0129] The imaging subsystem also includes a processor 223, a memory 225 and a communication unit 224, wherein the processor 223 is used to complete data reception and light source control of the metallographic display imaging camera and the ordinary imaging camera, and digitize the metallographic identification image to form the original image or the image to be matched, and store it in the memory 225; the communication unit 224 is used to interact with the identity library recognition subsystem for data.

[0130] Among them, the imaging subsystem 20 is mainly used for two parts: 1. After the product is produced and the metallographic mark is formed, the metallographic mark of the product is collected; 2. When the user needs to identify the product, the system is used to collect the metallographic mark and barcode of the product. The barcode is used to identify the type of product, and the metallographic mark is used to identify the authenticity of the product. The metallographic imaging light source 203 includes a metallographic white light LED 220, a metallographic ultraviolet LED 221, and a metallographic green light LED 222, which are respectively used to complete the reliable identification and imaging of the metallographic marks on the metal surfaces of various different materials. The ordinary imaging light source 201 is an ordinary LED white light source, which is used for illumination when collecting barcodes or QR codes.

[0131] The identity database recognition subsystem 30 includes:

[0132] The identity database establishment module 300 is used to receive the original image from the imaging subsystem 20;

[0133] The identity recognition module 301 is used to receive the image to be matched from the imaging subsystem 20;

[0134] The data processing module 304 is used to search and match the image to be matched with the original image, identify the authenticity of the image to be matched, and complete the sending, receiving and access of data;

[0135] The identity library recognition subsystem 30 also includes a storage module 302, a network transmission module 303 and a database 305, wherein the network transmission module 303 interacts with the imaging subsystem for data and stores the data in the database 305 through the storage module 302. The storage module 302 is used to complete the storage and reading process of the original image and the image data to be matched.

[0136] The identity recognition module 301 receives the image to be matched from the user-side imaging subsystem 20 according to the user's need for identity recognition, performs search and matching, completes the identity recognition and identification needs initiated by the user, and returns the original image and the judgment information after recognition for the user to verify the authenticity. For images with covered and hidden parts, if the image uploaded by the user is an incomplete metallographic identification image, the image returned to the user by the server only displays the overlapping area with the user's upload, and the area not opened and covered by the user will not be transmitted to the user.

[0137] The above-described embodiments merely illustrate several implementations of the present invention. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, and all such variations and improvements fall within the scope of protection of the present invention.

Claims

1. A method for identifying a commodity identity information mark, characterized by: The following steps are involved: Step S1: Preselect an inseparable metal region M in the product body, grind, polish, and etch the surface of the metal region M in sequence to obtain a metal region N; Step S2: Clean the corroded area on the surface of the metal area N with clean water, then preheat the metal area N and blow hot air with inert gas to remove residual water; Step S3: using a vacuum suction cup to extract air from the corroded area on the surface of the metal area N; Step S4: using transparent glass or transparent resin to seal and cover the corroded area of the metal area N to obtain a metal area P. The transparent and sealed corroded area on the surface of the metal area P is the metallographic mark; Step C1: establishing a commodity identity database based on metallographic identifications of different commodities, wherein the commodity identity database includes original images based on metallographic identifications; Step C2: Receive a request for product metallographic identification sent by the user, extract the metallographic identification of the product to be detected, form an image to be matched, and perform a matching search on images under different image modes based on an image matching algorithm, and return the result of identifying the authenticity. The image matching search for images under different image modes based on the image matching algorithm includes: using an alignment search algorithm to search and match images with near-translation, no rotation, and no scaling, and using a non-alignment search algorithm to process images with translation, rotation, and scaling.

2. A method for identifying a commodity identity information mark according to claim 1, characterized in that: The step C1 of establishing the identity database specifically includes the following steps: Step C1.1: Use a light source to illuminate the metallographic marking area of the product; Step C1.2: Use a microscopic imaging camera to capture the metallographic markings of the product and generate an image X; Step C1.3: Convert the generated image X into a digital image Y. Aggregate all digital images Y of the same product to create an identity database to form the original image.

3. The method for identifying a commodity identity information mark according to claim 1, characterized in that: The identification process of step C2 specifically includes the following steps: Step C2.1: The user initiates a metallographic identification request. The user first captures the product's QR code or barcode information to determine the product type and narrow the search scope. The user then captures the product's metallographic identification and obtains a complete metallographic identification image of the product. If the metallographic identification is incomplete, a partial metallographic identification image is captured. The captured metallographic identification image is digitized to form the image to be matched. Step C2.2: Send the image to be matched to the identity database and initiate a recognition request; Step C2.3: Determine whether the image pattern of the image to be matched is a nearly translated image without rotation or scaling. If so, use an alignment search algorithm to search and match the image to be matched with the original image in the identity database. If the image pattern is a nearly translated image without rotation or scaling, use a non-alignment search algorithm to search and match the image to be matched with the original image in the identity database. Step C2.4: Return the result of authenticity identification after matching.

4. A method for identifying a commodity identity information mark according to claim 3, characterized in that: If the image is a near-translation image without rotation or scaling, an alignment search algorithm is used to search and match the image to be matched with the original image in the identity database. The specific process is as follows: assuming that the resolution of the original image A is m×n and the resolution of the image to be matched B is v×w, the following steps are performed: Step L1: Set a sliding window with a resolution of v×w. The number of times the image B to be matched can slide on the original image A is: (m-v+1)×(n-w+1); Step L2: The image to be matched B starts to slide on the original image A, sliding pixel by pixel from the origin of the original image A. The similarity between the original image A and the image to be matched B is calculated once each slide. The similarity is the Euclidean distance value. The smaller the Euclidean distance value, the higher the similarity. There are a total of (m-v+1)×(n-w+1) values. Step L3: Find the minimum value from the (m-v+1)×(n-w+1) Euclidean distance values, and the corresponding window is the best matching area.

5. The method for identifying a commodity identity information mark according to claim 3, characterized in that: If the image is translated, rotated, and scaled, a non-aligned search algorithm is used to search and match the image to be matched with the original image in the identity database. The process includes: assuming that the resolution of the original image A is m×n and the resolution of the image to be matched B is v×w, the following steps are implemented: Step R1: Calculate the Surf features of the original image A and the image to be matched B; Step R2: Use the Surf features of the original image A and the image to be matched B to obtain the transformation matrix H; Step R3: Generate an image with all zeros, the image size is the same as the original image A, let this image be C; Step R4: transform the image B to be matched to the image C according to the transformation matrix H, set the grayscale values of the image B to be matched to 255, and set the transformed image to be image D; Step R5: The area in image D that is all 255 values is the matching area.

6. A commodity identity information recognition system, applied to the method according to any one of claims 1 to 5, characterized in that: The identification system includes the following subsystems: Metallographic formation subsystem (10): used to process the inseparable metal area of the product itself to form a metallographic mark; Imaging subsystem (20): used to collect and record the metallographic identifications generated for the goods, and also used to collect the metallographic identifications for subsequent goods identification and appraisal; Identity database identification subsystem (30): used to search and match the metallographic identification of the product to be tested with the original metallographic identification in the product identity database to identify the authenticity.

7. A commodity identity information recognition system according to claim 6, characterized in that: The metallographic formation subsystem (10) comprises: A surface pretreatment module (100) is used to clean the surface of the metallographic formation area and remove dirt; A grinding and polishing module (101) is used to polish the surface of the metallographic formation area; An etching module (102) is used to etch out the grains and grain boundaries of the marked area; A cleaning module (103) for removing the solution and water stains after corrosion; A drying and deoxidation module (104) is used to remove water molecules and oxygen molecules from the surface of the metallographic formation area; A covering and sealing module (105) is used to seal the corroded area and isolate it from the air; The auxiliary module (106) is used for additional auxiliary processes, including checking whether there are defective products.

8. A commodity identity information recognition system according to claim 6, characterized in that: The imaging subsystem (20) includes: A metallographic display imaging camera (204) for collecting metallographic identification of commodities; A common imaging camera (200) for collecting QR code or barcode information of a product; The metallographic imaging light source (203) and the common imaging light source (201) are used to provide light sources for the metallographic display imaging camera (204) and the common imaging camera (200), respectively; The imaging subsystem further comprises a processor (223), a memory (225) and a communication unit (224), wherein the processor (223) is used to complete data reception and light source control of the metallographic display imaging camera and the ordinary imaging camera, and to digitally process the metallographic identification image to form an original image or an image to be matched, and store it in the memory (225); and the communication unit (224) is used to perform data interaction with the identity library recognition subsystem.

9. A commodity identity information recognition system according to claim 6, characterized in that: The identity database identification subsystem (30) includes: An identity database building module (300) is configured to receive an original image from an imaging subsystem (20); An identity recognition module (301) is used to receive an image to be matched from the imaging subsystem (20); The data processing module (304) is used to search and match the image to be matched with the original image, identify the authenticity of the image to be matched, and complete the sending, receiving and access of data; The identity library recognition subsystem (30) further includes a storage module (302), a network transmission module (303) and a database (305), wherein the network transmission module (303) performs data interaction with the imaging subsystem and stores the data in the database (305) through the storage module (302), and the storage module (302) is used to complete the storage and reading process of the original image and the image data to be matched.

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