Internet-based commodity identity authentication method and system

Abstract

The invention relates to the technical field of commodity identity authentication, in particular to a commodity identity authentication method and system based on the Internet. Comprising the following steps: S1, establishing a commodity information database by using the Internet, and collecting generated image data of a commodity label generation device and identification image data of a commodity identification device; the placement postures of the commodities are accurately extracted and analyzed, verification is carried out in combination with the volume deviation threshold value under different placement postures, the situation that the commodities possibly present different visual volumes due to different placement modes is considered, and the visual volumes of the commodities can be accurately verified by dynamically adjusting the volume deviation threshold value. The actual volume and the standard volume are comprehensively compared to accurately record the pasting coordinates and size information of the identification on the commodity, and the pasting coordinates and size information are compared with the standard data in the database, so that commodity confusion or fraud behaviors caused by wrong pasting, missing pasting or malicious tampering of the pasting position of the identification are prevented, and the authenticity and traceability of the commodity are guaranteed from details.

Description

Technical Field

[0001] The present invention relates to the technical field of commodity identity authentication, and in particular to a commodity identity authentication method and system based on the Internet. Background Art

[0002] In today's commercial field, product identity authentication technology plays a vital role. Its purpose is to ensure the authenticity of products, protect the rights and interests of consumers, and maintain the normal order of the market. It mainly relies on barcodes, QR codes and other labels. Consumers can obtain basic information about the product by scanning the code, such as name, origin, specifications, etc. Enterprises can also use this to achieve preliminary traceability and sales management of the product.

[0003] At present, in the retail process, when the cashier scans the code to complete the checkout, he also shows the simple information of the product to the consumer. However, it is impossible to effectively verify the true identity of the product by simply scanning the code to obtain information, which leads to the replacement of product labels and causes economic losses. Even if problems are found later, it is difficult to accurately locate the root cause of the problem, and the recall cost is high. Therefore, a product identity authentication method and system based on the Internet is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide an Internet-based commodity identity authentication method and system to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, one of the purposes of the present invention is to provide a commodity identity authentication method based on the Internet, comprising the following steps:

[0006] S1. Use the Internet to establish a commodity information database, and collect the generated image data of the commodity label generating device and the recognized image data of the commodity recognition device;

[0007] S2. When the generated image data is received, the product is analyzed according to the generated image data, and the placement posture of the product is extracted from the generated image data, and volume image analysis is performed on different placement postures;

[0008] S3, obtaining weight data of the commodity, and performing volume deviation threshold analysis on the weight data in combination with the commodity type and the shooting height of the commodity identification device and the commodity label generation device, and dynamically adjusting the volume deviation threshold in combination with the difference between different placement postures;

[0009] S4, generating a unique identification mark according to the commodity type and commodity weight, and recording the location where the identification mark is pasted according to the generated image data, and then packaging the data related to the identification mark and uploading it to the commodity information database;

[0010] S5. When the image data identifies the product identity, the corresponding product data is extracted from the product information database, and then the placement posture of the product is combined with the volume deviation threshold and the identity label pasting position for authentication and recognition, and the product is determined to be valid based on the recognition result.

[0011] As a further improvement of the present technical solution, S1 establishes a commodity information database through the Internet, and simultaneously establishes a data connection between the commodity information database and the commodity label generating device and the commodity identifying device, so that the commodity label generating device will generate image data and the commodity identifying device will identify image data and transmit it in real time.

[0012] As a further improvement of the technical solution, the commodity label generating device and the commodity identification device in S1 both include a commodity placement plate and a camera, and the commodity placement plate and the camera in the commodity label generating device and the commodity identification device have the same shooting height and angle.

[0013] As a further improvement of the technical solution, the steps of S2 are as follows:

[0014] S2.1. When the camera of the product label generating device detects the presence of a product in the product placement tray, it generates image data and sends it, and receives the generated image data in the product information database via the Internet;

[0015] S2.2, collect commodity varieties that need to be identified by the commodity label generating device, and summarize and establish a commodity variety database, then combine the generated image data with the commodity variety database to perform variety analysis, and obtain the commodity variety of the generated image data according to the analysis results;

[0016] S2.3. Extract the placement posture of the product in the generated image data, perform volume image analysis on different placement postures, and obtain a volume image corresponding to each placement posture.

[0017] As a further improvement of the technical solution, the steps of S3 are as follows:

[0018] S3.1. When the goods are placed on the goods placement tray, the goods placement tray detects the weight data of the goods in real time, and uploads the weight data when the weight data stops fluctuating;

[0019] S3.2. Perform volume deviation threshold analysis on the volume image by combining the weight data with the commodity type and the shooting height of the commodity identification device and the commodity label generation device, and dynamically adjust the volume deviation threshold based on the difference between different placement postures to obtain the volume deviation threshold corresponding to each placement posture.

[0020] As a further improvement of the technical solution, the step of S4 is as follows:

[0021] S4.1. Generate a unique identification mark in the product label generating device according to the product type and weight. After the identification mark is attached, place the product with the identification mark attached in the product label generating device for verification;

[0022] S4.2. During the verification process, the position where the identity tag is pasted is recorded according to the generated image data, the position where the identity tag is pasted on the product is obtained, and then the product variety, weight data, volume image, volume deviation threshold and the position where the identity tag is pasted are packaged and uploaded to the product information database.

[0023] As a further improvement of the technical solution, the step of S5 is as follows:

[0024] S5.1. When the camera of the commodity recognition device detects the presence of a commodity in the commodity placement tray, the recognition image data is sent, and then the image data is combined with the commodity information database to perform commodity identity identification, and the corresponding commodity data is extracted from the commodity information database according to the recognition result;

[0025] S5.2. Authentication and identification are performed on the placement posture of the commodity based on the commodity data in combination with the volume deviation threshold, the location where the identity label is pasted, and the commodity variety. When the authentication and identification result shows no error deviation, the commodity is determined to be valid and entered into the commodity identification device. On the contrary, when the authentication and identification result shows an error deviation, the commodity is determined to be invalid.

[0026] As a further improvement of the present technical solution, in the authentication and identification process, when the commodity is determined to be invalid, S5.2 blacklists the identity mark and cannot restore it to a valid state.

[0027] The second object of the present invention is to provide an Internet-based commodity identity authentication system, including any one of the above-mentioned Internet-based commodity identity authentication methods, including a database establishment unit, a data packaging and uploading unit, and a commodity identity authentication unit;

[0028] The database establishment unit is used to establish a commodity information database using the Internet, and collect the generated image data of the commodity label generating device and the recognized image data of the commodity recognition device;

[0029] The data packaging and uploading unit is used to extract the placement posture of the product in the generated image data, perform volume image analysis on different placement postures, and perform volume deviation threshold analysis at the same time, dynamically adjust the volume deviation threshold based on the difference between different placement postures, and record the location where the identity mark is pasted, and then package the data related to the identity mark and upload it to the product information database;

[0030] The commodity identity authentication unit is used to extract corresponding commodity data from the commodity information database when the commodity identity mark is identified in the recognition image data, and then authenticate and identify the placement posture of the commodity in combination with the volume deviation threshold and the identity mark pasting position, and determine the validity of the commodity based on the recognition result.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. A commodity identity authentication method and system based on the Internet, which accurately extracts and analyzes the placement posture of the commodity, verifies the volume deviation threshold under different placement postures, and takes into account that the commodity may present different visual volumes due to different placement methods. By dynamically adjusting the volume deviation threshold, the actual volume is comprehensively compared with the standard volume to accurately record the pasting coordinates and size information of the label on the commodity, and compares it with the standard data in the database to prevent commodity confusion or fraud caused by wrong label pasting, missing labeling or malicious tampering with the pasting position, and ensure the authenticity and traceability of the commodity from the details.

[0033] 2. An Internet-based product identity authentication method and system, which comprehensively considers the placement posture, volume deviation, identity label pasting position and other multi-dimensional verification results. Only when all verification links are passed, the product is deemed valid. This comprehensive and rigorous authentication method greatly reduces the risk of problematic products entering the market and guarantees product quality in all aspects.

[0034] 3. A commodity identity authentication method and system based on the Internet. During the verification process, key information such as commodity variety, weight data, volume image, volume deviation threshold, and identity label pasting location are packaged and uploaded to the commodity information database, which is convenient for subsequent query, statistics and analysis at any time, providing strong data support for the company's supply chain management, inventory counting, quality traceability, etc., and optimizing the entire commodity management process. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is the overall flow chart of the present invention;

[0036] Figure 2 A flowchart of obtaining a volume image corresponding to each placement posture according to the present invention;

[0037] Figure 3 A flowchart of obtaining a volume deviation threshold corresponding to each placement posture in the present invention;

[0038] Figure 4 This is a flowchart of placing a commodity with an identity tag attached to it in a commodity tag generating device for verification.

[0039] Figure 5This is a flowchart of the present invention for extracting corresponding commodity data from a commodity information database according to the recognition result;

[0040] Figure 6 This is a structural principle diagram of the database establishment unit of the present invention.

[0041] The meaning of each number in the figure is:

[0042] 10. Database establishment unit; 20. Data packaging and uploading unit; 30. Product identity authentication unit. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] like Figure 1 - Figure 6 As shown, one of the purposes of the present invention is to provide a commodity identity authentication method based on the Internet, comprising the following steps:

[0045] S1. Use the Internet to establish a commodity information database, and collect the generated image data of the commodity label generating device and the recognized image data of the commodity recognition device;

[0046] S1 establishes a commodity information database through the Internet, and simultaneously establishes a data connection between the commodity information database and the commodity label generation device and the commodity identification device, so that the commodity label generation device generates image data and the commodity identification device transmits the identified image data in real time. The specific steps are as follows:

[0047] Use Internet technology to build a product information database, select a suitable database management system (such as MySQL, Oracle, etc.), ensure that the database has high reliability, high availability and high performance, and at the same time establish a data connection between the product information database and the product label generating device and the product identification device. The TCP / IP protocol can be used for communication, and a fixed IP address and port number are set, so that the product information database can actively receive the generated image data from the product label generating device and the recognized image data from the product identification device.

[0048] In S1, both the commodity label generating device and the commodity identification device include a commodity placement plate and a camera. Meanwhile, the commodity placement plate and the camera in the commodity label generating device and the commodity identification device have the same shooting height and angle.

[0049] The product label generating device and the product identifying device are both equipped with a product placement tray and a camera. The product placement tray is used to stably place the product to ensure that the product remains in a fixed position during the shooting process to obtain a consistent image. The camera is responsible for collecting image data of the product.

[0050] S2. When the generated image data is received, the product is analyzed according to the generated image data, and the placement posture of the product is extracted from the generated image data, and volume image analysis is performed on different placement postures;

[0051] The steps of S2 are as follows:

[0052] S2.1. When the camera of the product label generating device detects the presence of a product in the product placement tray, it generates image data and sends it. The generated image data is received in the product information database via the Internet. The specific steps are as follows:

[0053] Product detection trigger mechanism: The camera of the product label generation device is in a continuous monitoring state. The image recognition algorithm is used to analyze the image of the area where the product placement tray is located in real time. The appearance features of various products are learned and trained in advance so that it can accurately identify whether there is a product on the placement tray. Once the product is detected in the product placement tray, the image data collection instruction is triggered;

[0054] Transmission via the Internet: The product label generating device will establish a network connection with the server where the product information database is located based on the configured network settings, and send the packaged generated image data to the receiving interface corresponding to the server where the product information database is located.

[0055] S2.2, collect the commodity varieties that need to be generated by the commodity label generating device for identification, and summarize and establish a commodity variety database, then combine the generated image data with the commodity variety database for variety analysis, and obtain the commodity variety of the generated image data according to the analysis results. The specific steps are as follows:

[0056] Commodity variety collection starts: the commodity label generation device is equipped with a corresponding operation interface or is connected to the management end system. The operator collects the variety information of the commodities that need to generate identity tags by manual input, code scanning or importing from other related systems, summarizes and organizes the collected commodity variety information, and creates a commodity variety database using the database management system;

[0057] Image feature extraction: The product label generation device transmits the collected generated image data to a dedicated image analysis module, which uses image recognition technology, such as feature extraction algorithm, to extract key information that can reflect the appearance characteristics of the product from the generated image data;

[0058] Feature matching and variety judgment: The extracted image features are matched and compared with the feature descriptions of each variety of commodities pre-stored in the commodity variety database, and the results of the variety analysis are fed back to the commodity label generation device. The formula is as follows:

[0059]

[0060] Among them, COS(θ) is the similarity value. When the value of COS(θ) is closer to 1, it means that the two vectors are more similar, that is, the commodity corresponding to the generated image data is more likely to belong to this variety. n is the total number of standard feature vectors of a certain variety, and it is also the total number of feature vectors extracted from the generated image data. a i is the i-th standard feature vector of a certain variety in the commodity variety database, b i The i-th feature vector extracted to generate the image data.

[0061] S2.3. Extract the placement posture of the product in the generated image data, perform volume image analysis on different placement postures, and obtain the volume image corresponding to each placement posture. The specific steps are as follows:

[0062] Key point extraction and description: Use feature point extraction algorithms such as SIFT (Scale Invariant Feature Transform) and SURF (Speeded Up Robust Features) to identify some representative key points on the product image and generate corresponding feature descriptors. These key points and their descriptors can reflect the local feature differences of the product under different viewing angles and different placement postures. By matching the key points in different images, the relative position and angle changes of the product can be analyzed, and then its placement posture can be inferred;

[0063] Feature matching and corresponding point search: For multiple images of the same product taken in different placement postures, the feature points corresponding to the same point of the product in different images are found using the feature matching algorithm through the feature points and their descriptors extracted previously, and the coordinate relationship of these feature points in different images is determined;

[0064] Camera calibration and posture calculation: Based on the known intrinsic parameters of the camera that took these images, the relative posture of the camera between different images is calculated by matching feature points using the principle of epipolar geometry, and a sparse 3D point cloud model is further constructed to preliminarily restore the 3D structural form of the product in different placement postures;

[0065] Dense reconstruction and volume calculation: Based on the sparse point cloud, dense reconstruction is performed using algorithms such as region growing and marching cubes to fill the sparse 3D point cloud into a complete 3D model, so that it can accurately reflect the surface shape and internal spatial structure of the product. Then, its bounding box is calculated based on the 3D model (it can be an axis-aligned bounding box AABB or an oriented bounding box OBB, etc.). The volume of the bounding box can be used as an approximate value of the volume of the product in this placement posture.

[0066] S3, obtaining weight data of the commodity, and performing volume deviation threshold analysis on the weight data in combination with the commodity type and the shooting height of the commodity identification device and the commodity label generation device, and dynamically adjusting the volume deviation threshold in combination with the difference between different placement postures;

[0067] The steps for S3 are as follows:

[0068] S3.1. When the goods are placed on the goods placement tray, the goods placement tray detects the weight data of the goods in real time until the weight data stops fluctuating, and then uploads the weight data. The specific steps are as follows:

[0069] Real-time weight data collection: When the goods are placed on the goods placement tray, the weighing sensor will output an electrical signal corresponding to the weight of the goods in real time;

[0070] Weight data fluctuation judgment and stability detection: Since there may be some short-term shaking and unstable contact during the placement of goods, the weight data collected when the goods are just placed will fluctuate to a certain extent. Therefore, a threshold of 5s is set. When the weight data is stable for 5s, it is judged to be in a stable state;

[0071] Weight data uploading steps: Once it is determined that the weight data stops fluctuating and is in a stable state, the weight data at this time can be uploaded.

[0072] S3.2. Combine the weight data with the commodity type and the shooting height of the commodity identification device and the commodity label generation device to perform volume deviation threshold analysis on the volume image, and dynamically adjust the volume deviation threshold based on the difference between different placement postures to obtain the volume deviation threshold corresponding to each placement posture. The formula is as follows:

[0073]

[0074] Among them, W is the weight data of the product, ρ is the average density of the material corresponding to the product type, V g is the estimated volume of the product;

[0075] ΔV c =k H ×|ΔH|×V g

[0076] Among them, k H is the proportional coefficient between the shooting height and the volume visual deviation, ΔH is the shooting height difference, and ΔVc is the initial volume deviation threshold;

[0077] The corresponding volume correction coefficient k is determined by experiments, statistical analysis, etc. for different placement postures. P , and then combined with the previous initial volume deviation threshold ΔV c Volume correction factor k corresponding to different placement postures P , calculate the volume deviation threshold for each placement posture:

[0078] ΔV z =k P ×ΔV c

[0079] Where, ΔV z is the volume deviation threshold for each placement posture.

[0080] S4, generating a unique identification mark according to the commodity type and commodity weight, and recording the location where the identification mark is pasted according to the generated image data, and then packaging the data related to the identification mark and uploading it to the commodity information database;

[0081] The steps of S4 are as follows:

[0082] S4.1. Generate a unique identification mark in the product label generating device according to the product type and weight. After the identification mark is attached, place the product with the identification mark attached in the product label generating device for verification;

[0083] S4.2. During the verification process, the position where the identity tag is pasted is recorded according to the generated image data, the position where the identity tag is pasted on the product is obtained, and then the product type, weight data, volume image, volume deviation threshold and the position where the identity tag is pasted are packaged and uploaded to the product information database. The specific steps are as follows:

[0084] Image coordinate system establishment: A two-dimensional coordinate system is established in the image corresponding to the generated image data collected by the product label generating device, with the upper left corner of the image as the origin, the horizontal right as the positive direction of the x-axis, and the vertical downward as the positive direction of the y-axis. The coordinate unit can be pixels.

[0085] Logo location extraction: Use image recognition technology to locate the area where the identity logo is located in the image corresponding to the generated image data;

[0086] Data packaging and uploading steps: organize and package these data (commodity type, weight data, volume image, volume deviation threshold and identity label pasting position) according to a certain data structure, and select a suitable method to upload the packaged data according to the interface specification and communication protocol of the commodity information database.

[0087] S5. When the image data identifies the product identity, the corresponding product data is extracted from the product information database, and then the placement posture of the product is combined with the volume deviation threshold and the identity label pasting position for authentication and recognition, and the product is determined to be valid based on the recognition result.

[0088] The steps of S5 are as follows:

[0089] S5.1. When the camera of the commodity recognition device detects the presence of a commodity in the commodity placement tray, the recognition image data is sent, and then the image data is combined with the commodity information database to perform commodity identity identification, and the corresponding commodity data is extracted from the commodity information database according to the recognition result. The specific steps are as follows:

[0090] Product detection trigger mechanism: The camera of the product recognition device is in a continuous monitoring state. It uses the image recognition algorithm to analyze the image of the area where the product placement tray is located in real time. It learns and trains the appearance characteristics of various products in advance so that it can accurately identify whether there is a product on the placement tray. Once the product is detected in the product placement tray, the image data collection instruction is triggered;

[0091] Transmission via the Internet: The commodity recognition device will establish a network connection with the server where the commodity information database is located based on the configured network settings, and send the packaged recognition image data to the corresponding receiving interface of the server where the commodity information database is located;

[0092] Image feature extraction: After receiving the recognition image data, the server where the product information database is located first transmits it to a dedicated image analysis module. This module uses image recognition technology, such as feature extraction algorithms, to extract key information that can reflect the appearance characteristics of the product from the recognition image data;

[0093] Feature matching and identity recognition: The extracted image features are matched and compared with the identity-related features of each product pre-stored in the product information database. Once the identity of the product is determined, a query operation is performed in the product information database to extract all product data corresponding to the identity.

[0094] S5.2. Authentication and identification are performed on the placement posture of the commodity based on the commodity data in combination with the volume deviation threshold, the location where the identity label is pasted, and the commodity variety. When the authentication and identification result shows no error deviation, the commodity is determined to be valid and entered into the commodity identification device. On the contrary, when the authentication and identification result shows an error deviation, the commodity is determined to be invalid.

[0095] S5.2 During the authentication and identification process, if the product is determined to be invalid, the identity tag will be blacklisted and cannot be restored to a valid state. The specific formula is as follows:

[0096]

[0097] Among them, R V is the volume deviation rate, V X is the actual volume of the product in the current placement position, V Y is the standard volume of the product stored in the database, and R V and ΔV z For comparison, when R V ≤ΔV z , then enter the next step of authentication and identification, otherwise it is an error deviation;

[0098] Δx=|x s -x center

[0099] Δy=|y s -y center

[0100] Among them, x s and s To identify the actual pasting location of the identity marker in the image, x center and center is the standard pasting position information recorded in the database, Δx k is the horizontal axis deviation threshold, Δy k is the vertical axis deviation threshold, when Δx≤Δx k , and Δy≤Δy k , then the coordinate deviation meets the requirements, otherwise, the product is considered invalid;

[0101] ΔW=|W s -W center

[0102] ΔH=|H s -H center

[0103] Among them, W s is the actual width, H s is the actual height, H center and W centeris the standard pasting position information recorded in the database, ΔW k is the width deviation threshold, ΔH k is the height deviation threshold, when ΔW≤ΔW k , and ΔH≤ΔH k , then the size deviation meets the requirements, otherwise, the product is considered invalid;

[0104] When the commodity does not meet any of the conditions, the commodity is determined to be valid and is entered into the commodity identification device.

[0105] The second object of the present invention is to provide an Internet-based commodity identity authentication system, including any one of the above-mentioned Internet-based commodity identity authentication methods, including a database establishment unit 10, a data packaging and uploading unit 20, and a commodity identity authentication unit 30;

[0106] The database establishment unit 10 is used to establish a commodity information database using the Internet, and collect the generated image data of the commodity label generation device and the recognized image data of the commodity recognition device;

[0107] The data packaging and uploading unit 20 is used to extract the placement posture of the product in the generated image data, perform volume image analysis on different placement postures, and perform volume deviation threshold analysis at the same time, and dynamically adjust the volume deviation threshold based on the difference between different placement postures and record the location where the identity mark is pasted, and then package the data related to the identity mark and upload it to the product information database;

[0108] The commodity identity authentication unit 30 is used to extract the corresponding commodity data from the commodity information database when the commodity identity mark is identified in the recognition image data, and then authenticate and identify the placement posture of the commodity in combination with the volume deviation threshold and the identity mark pasting position, and determine the validity of the commodity based on the recognition result.

[0109] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A commodity identity authentication method based on the Internet, characterized in that: The steps include: S1. Use the Internet to establish a commodity information database, and collect the generated image data of the commodity label generating device and the recognized image data of the commodity recognition device; S2. When the generated image data is received, the product is analyzed according to the generated image data, and the placement posture of the product is extracted from the generated image data, and volume image analysis is performed on different placement postures; S3, obtaining weight data of the commodity, and performing volume deviation threshold analysis on the weight data in combination with the commodity type and the shooting height of the commodity identification device and the commodity label generation device, and dynamically adjusting the volume deviation threshold in combination with the difference between different placement postures; S4, generating a unique identification mark according to the commodity type and commodity weight, and recording the location where the identification mark is pasted according to the generated image data, and then packaging the data related to the identification mark and uploading it to the commodity information database; S5. When the image data identifies the product identity, the corresponding product data is extracted from the product information database, and then the placement posture of the product is combined with the volume deviation threshold and the identity label pasting position for authentication and recognition, and the product is determined to be valid based on the recognition result.

2. The Internet-based commodity identity authentication method according to claim 1, characterized in that: The S1 establishes a commodity information database through the Internet, and simultaneously establishes a data connection between the commodity information database and the commodity label generating device and the commodity identifying device, so that the commodity label generating device can generate image data and the commodity identifying device can identify image data and transmit it in real time.

3. The Internet-based commodity identity authentication method according to claim 1, characterized in that: The commodity label generating device and the commodity identification device in S1 both include a commodity placement plate and a camera. Meanwhile, the commodity placement plate and the camera in the commodity label generating device and the commodity identification device have the same shooting height and angle.

4. The method for commodity identity authentication based on the Internet according to claim 1, characterized in that: The steps of S2 are as follows: S2.

1. When the camera of the product label generating device detects the presence of a product in the product placement tray, it generates image data and sends it, and receives the generated image data in the product information database via the Internet; S2.2, collect commodity varieties that need to be identified by the commodity label generating device, and summarize and establish a commodity variety database, then combine the generated image data with the commodity variety database to perform variety analysis, and obtain the commodity variety of the generated image data according to the analysis results; S2.

3. Extract the placement posture of the product in the generated image data, perform volume image analysis on different placement postures, and obtain a volume image corresponding to each placement posture.

5. The method for commodity identity authentication based on the Internet according to claim 1, characterized in that: The steps of S3 are as follows: S3.

1. When the goods are placed on the goods placement tray, the goods placement tray detects the weight data of the goods in real time, and uploads the weight data when the weight data stops fluctuating; S3.

2. Perform volume deviation threshold analysis on the volume image by combining the weight data with the commodity type and the shooting height of the commodity identification device and the commodity label generation device, and dynamically adjust the volume deviation threshold based on the difference between different placement postures to obtain the volume deviation threshold corresponding to each placement posture.

6. The Internet-based commodity identity authentication method according to claim 1, characterized in that: The steps of S4 are as follows: S4.

1. Generate a unique identification mark in the product label generating device according to the product type and weight. After the identification mark is attached, place the product with the identification mark attached in the product label generating device for verification; S4.

2. During the verification process, the position where the identity tag is pasted is recorded according to the generated image data, the position where the identity tag is pasted on the product is obtained, and then the product variety, weight data, volume image, volume deviation threshold and the position where the identity tag is pasted are packaged and uploaded to the product information database.

7. The Internet-based commodity identity authentication method according to claim 1, characterized in that: The steps of S5 are as follows: S5.

1. When the camera of the commodity recognition device detects the presence of a commodity in the commodity placement tray, the recognition image data is sent, and then the image data is combined with the commodity information database to perform commodity identity identification, and the corresponding commodity data is extracted from the commodity information database according to the recognition result; S5.

2. Authentication and identification are performed on the placement posture of the commodity based on the commodity data in combination with the volume deviation threshold, the location where the identity label is pasted, and the commodity variety. When the authentication and identification result shows no error deviation, the commodity is determined to be valid and entered into the commodity identification device. On the contrary, when the authentication and identification result shows an error deviation, the commodity is determined to be invalid.

8. The Internet-based commodity identity authentication method according to claim 7, characterized in that: In the authentication and identification process, when the commodity is determined to be invalid, the identity mark is blacklisted and cannot be restored to a valid state.

9. An Internet-based commodity identity authentication system, used to implement an Internet-based commodity identity authentication method as claimed in any one of claims 1 to 8, characterized in that: It comprises a database establishment unit (10), a data packaging and uploading unit (20) and a commodity identity authentication unit (30); The database establishment unit (10) is used to establish a commodity information database using the Internet, and collect the generated image data of the commodity label generating device and the recognized image data of the commodity recognition device; The data packaging and uploading unit (20) is used to extract the placement posture of the commodity in the generated image data, perform volume image analysis on different placement postures, perform volume deviation threshold analysis at the same time, dynamically adjust the volume deviation threshold based on the difference between different placement postures, and record the location where the identity mark is pasted, and then package the data related to the identity mark and upload it to the commodity information database; The commodity identity authentication unit (30) is used to extract corresponding commodity data from a commodity information database when the commodity identity mark is identified in the recognition image data, and then authenticate and identify the placement posture of the commodity in combination with the volume deviation threshold and the identity mark pasting position, and determine whether the commodity is valid based on the recognition result.

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