Digital collection transaction method and system based on NFT

Abstract

The invention relates to the technical field of digital collections, in particular to a digital collection transaction method and system based on NFT, and the method comprises the steps: carrying out the information layer disassembly of a to-be-transacted digital collection, obtaining a display information layer and a hidden information layer of the digital collection, obtaining a unique identification code of the digital collection through the interpretation of the hidden information layer, and carrying out the transaction of the digital collection. Acquiring account information of a first account holding the digital collection and account information of a second account waiting for receiving the digital collection, acquiring personalized customization information of the second account for the digital collection at the same time, and taking the unique identification code, the account information and the personalized customization information as casting functions of the NFT smart contract. And recording the holding right transaction of the digital collection on the block chain, transferring the digital collection from the first account to the second account, and synchronously adjusting the display information layer and the hidden information layer according to the personalized customization information.

Description

Technical Field

[0001] This invention relates to the field of digital collectibles technology, and more specifically, to a method and system for trading digital collectibles based on NFTs. Background Technology

[0002] With the development of the digital age, more and more people are paying attention to the collection and investment value of digital collectibles. Digital collectibles are unique, scarce and tradable. In the current technology, the uniqueness of digital collectibles is achieved by marking strings on the digital collectibles. This form of uniqueness authentication destroys the integrity of the displayed content of the digital collectibles themselves. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method and system for trading digital collectibles based on NFTs, in order to achieve this.

[0004] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: According to one aspect of the present invention, a method for trading NFT-based digital collectibles is provided, comprising: The digital collectibles to be traded are disassembled into information layers to obtain the display information layer and the hidden information layer of the digital collectibles. The unique identification code of the digital collectibles is obtained by interpreting the hidden information layer. Obtain the account information of the first account holding the digital collectible and the second account waiting to receive the digital collectible, and at the same time obtain the personalized customization information of the second account for the digital collectible; The unique identifier, account information, and personalized customization information are used as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain. The digital collection is transferred from the first account to the second account, and the displayed information layer and the hidden information layer are adjusted synchronously according to the personalized customization information.

[0005] According to another aspect of the present invention, a multi-account transaction management system based on NFT tokens is provided, comprising: The encoding and decoding module is used to deconstruct the information layer of the digital collectibles to be traded, to obtain the display information layer and the hidden information layer of the digital collectibles, and to obtain the unique identification code of the digital collectibles by decoding the hidden information layer. The information acquisition module is used to acquire the account information of a first account holding the digital collectible and a second account waiting to receive the digital collectible, and at the same time acquire the personalized customization information of the second account for the digital collectible; The transaction record module is used to use the unique identifier code, the account information, and the personalized customization information as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain. The collection adjustment module is used to transfer the digital collection from the first account to the second account, and to synchronously adjust the displayed information layer and the hidden information layer according to the personalized customization information.

[0006] As can be seen from the above technical solution, the NFT-based digital collectible trading method provided by this invention has the following beneficial effects: This invention disassembles the information layer to obtain a unique identifier code, ensuring the uniqueness and traceability of digital collectibles. It also obtains account and customized information, supports personalized transactions, meets diverse user needs, and uses NFT smart contracts to record transactions on the blockchain, ensuring transparency and immutability, improving security and credibility. The invention transfers collectibles and simultaneously adjusts the information layer, enabling digital collectibles to be presented according to user customization after the transaction, enhancing user experience and promoting the healthy development of the digital collectibles market. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort: Figure 1 A schematic diagram illustrating the steps of an NFT-based digital collectibles trading method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a multi-account transaction management system based on NFT tokens provided in an embodiment of the present invention. Detailed Implementation

[0008] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0009] With the development of the digital age, more and more people are paying attention to the collection and investment value of digital collectibles. Digital collectibles are unique, scarce and tradable. In the current technology, the uniqueness of digital collectibles is achieved by marking strings on the digital collectibles. This form of uniqueness authentication destroys the integrity of the displayed content of the digital collectibles themselves.

[0010] In view of this, the present invention provides a method for trading digital collectibles based on NFTs, the steps of which are as follows: Figure 1 As shown, it includes: The first step is to disassemble the digital collectibles to be traded into information layers, obtaining the display information layer and the hidden information layer of the digital collectibles, and to obtain the unique identification code of the digital collectibles by interpreting the hidden information layer.

[0011] Specifically, in the first step of the embodiment provided by the present invention, the digital collectible to be traded is disassembled into an information layer to obtain a display information layer and a hidden information layer of the digital collectible. It can be seen that the digital collectible targeted by the present invention is obtained by superimposing and combining a display information layer and a hidden information layer.

[0012] More specifically, digital collectibles are digital assets based on blockchain technology. They digitize specific works, artworks, virtual goods, etc., and assign them unique identifiers. These identifiers are recorded on the blockchain, ensuring the uniqueness, authenticity, and immutability of digital collectibles. Digital collectibles can take many forms, such as pictures, music, videos, 3D models, and electronic tickets, and have value for collection, appreciation, and use.

[0013] More specifically, the unique identifier of a digital collectible is usually a string of characters directly marked on the digital collectible. This design has several drawbacks, such as ruining the visual appeal of the digital collectible and lacking differentiation between digital collectibles. In this technical solution, the digital collectible is designed with two layers: a display information layer and a hidden information layer. The display information layer contains the original information expressed by the digital collectible, while the hidden information layer contains the unique identifier code of the digital collectible. That is, the unique identifier code is converted into information hidden in the digital collectible itself and superimposed on the original information, thereby generating a digital collectible without obvious character identifiers and with unique differences from other digital collectibles.

[0014] More specifically, since the hidden information layer expresses the unique identifier of the digital collectible, it is necessary to interpret the hidden information layer before trading the digital collectible in order to obtain the unique identifier of the digital collectible, so as to record the transaction content of the digital collectible based on blockchain in the subsequent transaction process.

[0015] The second step is to obtain the account information of the first account holding the digital collectible and the second account waiting to receive the digital collectible, and at the same time obtain the personalized customization information of the second account for the digital collectible.

[0016] Specifically, in the second step of the embodiment provided by this invention, the digital collectibles will be transferred from the first account holding the digital collectibles to the second account waiting to receive the digital collectibles. Therefore, in order to record the digital collectibles transaction based on blockchain in the subsequent process, it is necessary to obtain the account information of the first account and the second account so as to record the source and object of the transaction, thereby ensuring the security and traceability of the digital collectibles transaction.

[0017] More specifically, in the trading of digital collectibles, a second account can submit a personalized customization request for the digital collectible. This allows the system to obtain personalized customization information from the second account. Personalization requests involve modifying and adjusting the displayed content of the digital collectible within a predetermined range, thereby further differentiating it from other digital collectibles and increasing its holding value. It's also easy to understand that the first account can also provide unique personalization for digital collectibles in previous transactions, giving them value and advantages that traditional digital collectibles lack. Traditionally, digital collectibles only differ in their unique identifier strings, without additional differences in displayed content. Therefore, digital collectibles of the same creation do not inherently possess differentiated value, and users only consider the differences in identifier strings when trading digital collectibles, causing their value to deviate. In this technical solution, through the design of a hidden information layer and personalized customization, a new form of digital collectible can be constructed, possessing greater value for collection and trading compared to traditional digital collectibles.

[0018] The third step involves using the unique identifier code, the account information, and the personalized customization information as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain.

[0019] Specifically, in the third step of the embodiment provided by the present invention, the content of this digital collectible transaction is recorded on the blockchain through an NFT smart contract. The recorded content includes the unique identifier code of the digital collectible, the account information of the buyer and seller, and the seller's personalized customization information for the digital collectible.

[0020] More specifically, the unique code and account information serve to record the circulation path of digital collectibles, so as to achieve the traceability of the transaction flow of digital collectibles and ensure that the authenticity of digital collectibles can be certified. The recording of personalized customization information is used to connect the digital collectibles before and after customization, so as to ensure that the customized digital collectibles can be traced back to the digital collectibles before the modification.

[0021] More specifically, an NFT smart contract is a computer program based on blockchain technology. It exists on the blockchain in the form of code and follows specific standards to create, manage, and trade non-fungible tokens. Non-fungible tokens represent unique digital assets, such as digital artworks, game items, and virtual land. Smart contracts are characterized by automatic execution, immutability, and transparency. Once preset conditions are met, the smart contract will automatically execute the corresponding operation without the intervention of a third-party intermediary. All transaction records and operations are recorded on the blockchain, which can be viewed by anyone, ensuring the fairness and traceability of transactions. In this technical solution, NFT smart contracts are used to record the transaction content of digital collectibles to ensure the security of digital collectible transactions.

[0022] More specifically, the minting function is the core function in an NFT smart contract used to generate new non-fungible tokens. When the minting function is called, it creates a new NFT instance on the blockchain and assigns it a unique identifier. In this step, the unique identifier code, account information, and personalized customization information are substituted into the minting function so that the content fed back by the minting function can be recorded on the blockchain through the NFT smart contract.

[0023] The fourth step is to transfer the digital collection from the first account to the second account, and to synchronize and adjust the display information layer and the hidden information layer according to the personalized customization information.

[0024] Specifically, in the fourth step of the embodiment provided by the present invention, the existing form of the display information layer is parsed to generate existing display information. This means that the appearance, content and other information of the digital collection currently presented to the user are extracted and organized to form an operable data form. The existing display information is adjusted according to the personalized customization information provided by the second account user to obtain the expected display information. For example, if the user requests to change the color of the digital collection or add a specific pattern, the existing display information will be modified accordingly.

[0025] More specifically, when trading digital collectibles, users may want to personalize their appearance and other display information. By adjusting the display information layer, users' personalized needs can be met, improving their satisfaction and user experience with digital collectibles. Personalized digital collectibles can better reflect users' unique taste and creativity, increasing their value and attractiveness, and making the transaction more meaningful.

[0026] More specifically, the existing form of the hidden information layer is parsed to generate existing hidden information, which is then broken down into several hidden information units. Each hidden information unit is a relatively independent information fragment in the hidden information layer, which facilitates subsequent analysis and processing. The positional mapping relationship between each hidden information unit and the expected display information is analyzed. This step is to determine the specific position of the hidden information unit when it is superimposed with the expected display information, so as to accurately simulate the superposition effect.

[0027] More specifically, based on the positional mapping relationship, each hidden information unit is overlaid with the expected display information, and a spatial window is constructed based on the overlay position of the hidden information units. The spatial window is an area used to limit the range of information overlay. The human eye observation effect after the expected display information and hidden information units are overlaid within the spatial window is simulated to generate the observation effect features of the hidden information units. This usually uses a pre-trained human eye observation simulation model. Considering the human eye's visual perception of different information overlays, the observation effect features of each hidden information unit are combined to obtain the expected observation effect. By integrating the observation effect features of each hidden information unit, the final expected observation effect of the entire digital collection after the display information layer and hidden information layer are overlaid after personalization can be obtained.

[0028] More specifically, the display and hidden information layers of digital artifacts are superimposed during actual display. It is necessary to consider their overall coordination. By simulating the expected observation effect, the visual effect after superposition can be evaluated in advance to avoid information conflicts or inconsistencies, ensuring that the digital artifacts have a good visual effect when displayed. The human eye observation effect is what users directly perceive. Simulating the human eye observation effect can ensure that the digital artifacts presented to users in the end meet their visual expectations and provide a better user experience.

[0029] More specifically, using the expected observation effect as a monitoring condition, the existing hidden information is adjusted in terms of its representation and the superimposed display effect is simulated. Different representation forms are tried continuously, and the superimposed display effect is simulated after each adjustment until the representation form with the best expected observation effect is obtained. Finally, the existing form of the hidden information layer is adjusted according to this representation form.

[0030] More specifically, after the display information layer is personalized, the hidden information layer also needs to be adjusted accordingly to maintain consistency and coordination with the display information layer. By adjusting based on the expected observation effect as the monitoring condition, it can be ensured that the hidden information layer can still perfectly blend with the display information layer in the context of the new display information layer, and together present the best overall effect.

[0031] More specifically, the hidden information layer usually contains key information related to the uniqueness and copyright of digital collectibles. In the adjustment process, it is necessary to meet the needs of personalized customization while ensuring the security and identifiability of this key information. Through continuous trial and adjustment and simulation, the best form of expression can be found to balance these two aspects.

[0032] As can be seen from the above technical solution, the NFT-based digital collectible trading method provided by this invention has the following beneficial effects: This invention disassembles the information layer to obtain a unique identifier code, ensuring the uniqueness and traceability of digital collectibles. It also obtains account and customized information, supports personalized transactions, meets diverse user needs, and uses NFT smart contracts to record transactions on the blockchain, ensuring transparency and immutability, improving security and credibility. The invention transfers collectibles and simultaneously adjusts the information layer, enabling digital collectibles to be presented according to user customization after the transaction, enhancing user experience and promoting the healthy development of the digital collectibles market.

[0033] Furthermore, the steps of disassembling the digital collectibles to be traded into information layers to obtain the display information layer and the hidden information layer, and obtaining the unique identifier code of the digital collectibles by interpreting the hidden information layer, include: S11: Activate the corresponding digital key by receiving several mnemonic phrases input by the user through a pre-deployed first account; S12: Unlock the digital collectible to be traded using the digital key, so that the digital collectible changes from a locked state to an unlocked state; S13: Call the information layer decomposition algorithm corresponding to the digital collectible to decompose the information layer of the digital collectible in the unlocked state, and obtain the display information layer and hidden information layer of the digital collectible; S14: Based on the preset identification coding standard, the hidden information layer is interpreted to obtain the unique identification code of the digital collection.

[0034] Specifically, the system receives several mnemonic phrases input by the user in advance through the first account to activate the corresponding digital key. On the interface of the first account holding the digital collectible to be traded, the user enters several pre-set mnemonic phrases as prompted by the system. After receiving these mnemonic phrases, the system will verify them. If the verification is successful, the corresponding digital key will be activated. For example, if the user has pre-set three mnemonic phrases: "apple, banana, orange", when these three mnemonic phrases are entered correctly in the first account, the system will activate the corresponding digital key for that user.

[0035] More specifically, a mnemonic phrase is a convenient way for users to remember and manage their private keys. Only users who know the correct mnemonic phrase can activate the corresponding digital key. This sets up a security barrier for accessing and operating digital collectibles, preventing unauthorized personnel from obtaining and tampering with digital collectible information. The digital key is closely linked to the user's identity. Activating the digital key by entering the mnemonic phrase is equivalent to identity verification, ensuring that only the legitimate holder of the digital collectible can conduct subsequent transaction operations.

[0036] More specifically, using the activated digital key, an unlocking command is sent to the storage system or smart contract of the digital collectible to be traded. After receiving the command, the storage system or smart contract verifies the validity of the digital key. If valid, the digital collectible's status is changed from locked to unlocked. In the locked state, the digital collectible is protected and cannot be traded or modified at will. The unlocking operation is a necessary step in the transaction process. Only in a legal transaction scenario, by unlocking the digital collectible with the correct digital key, can the compliance and legality of the transaction be guaranteed. In the locked state, the data of the digital collectible is under security protection, preventing accidental modification or damage. Only after unlocking can subsequent operations such as information disassembly be performed, while also ensuring the integrity of the data during the operation.

[0037] More specifically, once the digital collectible is unlocked, the system invokes a specially designed information layer decomposition algorithm. This algorithm analyzes and processes the overall information of the digital collectible, dividing it into two parts: a display information layer and a hidden information layer. This division facilitates the classification, management, and protection of different types of information. The display information layer satisfies users' needs for viewing the appearance and basic content of the digital collectible, while the hidden information layer contains critical information that requires higher security protection. This layered structure better achieves this goal. In subsequent transactions, the display information layer can be adjusted according to the user's personalized needs, while the critical information in the hidden information layer remains relatively stable. This layered structure provides greater flexibility for the personalization and trading of digital collectibles.

[0038] More specifically, based on the pre-set identification coding standards, the information content in the hidden information layer is interpreted in detail. The system will search for specific fields, codes or data combinations that meet the identification standards in the hidden information layer and extract the unique identification code of the digital collection. The pre-set identification coding standards are like a password decryption rule. The hidden information layer is a string of encrypted information. By deciphering this string of encrypted information according to the rules, the "password" (unique identification code) representing the unique identity of the digital collection can be found.

[0039] More specifically, the unique identifier code is a method of authenticating digital collectibles. It plays a crucial role in the entire transaction process. By obtaining the unique identifier code, the uniqueness and traceability of digital collectibles on the blockchain can be ensured, making it convenient to record and query the transaction history and ownership changes of digital collectibles. The unique identifier code can be used to verify the authenticity and copyright ownership of digital collectibles. During the transaction process, by verifying the unique identifier code, the counterfeiting and piracy of digital collectibles can be effectively prevented, protecting the legitimate rights and interests of creators and holders.

[0040] Furthermore, the step of using the unique identifier code, the account information, and the personalized customization information as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain includes: S31: Convert the unique identifier code, the account information, and the personalized customization information to obtain the collection identifier factor, the account transaction factor, and the display customization factor; S32: Adjust the parameters of the NFT smart contract's casting function by the display customization factor, the collection identification factor, and the account transaction factor to obtain the casting function of the NFT smart contract corresponding to the current transaction; S33: Upload the NFT smart contract containing the casting function to the blockchain to record the ownership transactions of the digital collectible.

[0041] Specifically, the system performs a series of processes on the unique identifier code, such as hashing it or re-encoding it according to specific encoding rules, converting it into a collectible identifier factor suitable for use in smart contracts. This factor can uniquely and efficiently represent the digital collectible in the smart contract. Account information usually includes relevant information about the first account (seller) and the second account (buyer), such as account addresses. The system extracts this key information, performs format conversion and encryption processing, and generates an account transaction factor. This factor is used to identify the identities of the two parties in the transaction in the smart contract. Personalized customization information is parsed and processed. For example, the user's requested colors, patterns, and other customized information are converted into a digital feature matrix, and then compressed and converted to generate a display customization factor. This factor is used to record the user's customization requirements for the display information of the digital collectible in the smart contract.

[0042] More specifically, the original formats of unique identifier codes, account information, and personalized customization information are not suitable for direct use in smart contracts. By converting them into collectible identification factors, account transaction factors, and display customization factors, this information can be transformed into a format that smart contracts can understand and process, ensuring that smart contracts can accurately process and record transaction information. During the conversion process, the information can be encrypted and compressed to improve data security and privacy. For example, account information can be encrypted to prevent it from being leaked during transactions.

[0043] More specifically, the generated collectible identification factor, account transaction factor, and display customization factor are injected as parameters into the minting function of the NFT smart contract. The minting function is a key part of the smart contract used to create and define digital assets. Based on the injected parameters, the minting function is adjusted accordingly. For example, the uniqueness of the digital collectible is determined by the collectible identification factor, the parties and transaction rules are determined by the account transaction factor, and the display characteristics of the digital collectible are determined by the display customization factor. After adjustment, the minting function can accurately reflect the specific situation of the current digital collectible transaction.

[0044] More specifically, different digital collectible transactions have different rules and requirements. By adjusting the parameters of the minting function, the behavior of the smart contract can be customized according to the specific circumstances of the current transaction. For example, the display characteristics of the digital collectible can be adjusted according to personalized customization information to ensure that the digital collectible meets the user's needs after the transaction. Parameter adjustment enables the minting function to accurately reflect the uniqueness of the digital collectible, the identities of the two parties in the transaction, and the transaction rules, thereby ensuring that the transaction information recorded on the blockchain is accurate and avoiding transaction disputes.

[0045] More specifically, the parameter-adjusted casting function is integrated and packaged with other parts of the NFT smart contract to form a complete, executable smart contract. This packaged smart contract is then sent to the blockchain network. Blockchain nodes verify the smart contract. Upon successful verification, the relevant information is recorded on the blockchain's distributed ledger. This information includes the unique identifier of the digital collectible, the account information of both parties to the transaction, and personalized customization details, thus completing the record of the digital collectible's ownership transaction.

[0046] More specifically, blockchain possesses the characteristics of immutability and traceability. Uploading smart contracts containing minting functions to the blockchain ensures that the records of digital collectible ownership transactions are secure and reliable, and can be queried and verified at any time. Once a transaction record is written into the blockchain, it cannot be easily tampered with, guaranteeing the fairness and transparency of the transaction. Nodes in the blockchain network verify and reach consensus on the smart contract, ensuring that the transaction complies with established rules and protocols. This distributed consensus mechanism can prevent single points of failure and malicious attacks, improving the reliability and security of transactions.

[0047] Furthermore, the step of converting the personalized customization information to obtain the display customization factor includes: S311: Interpret the display content of the digital collection's display information layer and express it in vector form to obtain the display content feature matrix; S312: Based on the personalized customization information, perform a change analysis on the display content feature matrix to obtain the customized display feature matrix of the digital collection corresponding to the personalized customization information; S313: Compress and transform the information of the display content feature matrix and the customized display feature matrix to generate a display customization factor.

[0048] Specifically, the system analyzes various elements in the digital artifact display information layer, such as the color, shape, and texture of images, and the font, size, and content of text. Through technologies such as computer vision and natural language processing, it identifies and extracts the key features of these display contents, converts the interpreted display content features into vector form, and each feature can be represented by a single value or a set of values. Then, these vectors are combined according to certain rules to form a matrix, namely the display content feature matrix. For example, for a digital image containing color, shape, and size features, color is represented by an RGB value vector, shape by a geometric parameter vector, and size by a dimension vector. These vectors are then combined into a matrix.

[0049] More specifically, by expressing the display content of digital artifacts in a vectorized form and forming a matrix, data standardization is achieved. Different types of digital artifacts have different display formats and content, but through vectorization and matrix processing, they can be uniformly represented in a form that is easy for computers to process and analyze, providing a foundation for subsequent customized analysis and processing. By interpreting the display content and converting it into a vector matrix, the key features of digital artifacts can be accurately extracted and these features can be quantified into specific values. This allows for a more precise description of the display characteristics of digital artifacts, facilitating comparison and analysis.

[0050] More specifically, the personalized customization information provided by the user is analyzed in detail to clarify what changes the user wants to make to the displayed information of the digital artifact, such as changing colors, adding patterns, or adjusting text content. Based on the analyzed customization requirements, the display content feature matrix is ​​analyzed and adjusted accordingly. If the user requests to change the color of the image, the vector representing the color in the display content feature matrix will be modified; if a pattern is requested, the corresponding feature vector will be added to the matrix. After these adjustments, a customized display feature matrix is ​​obtained, which reflects the display characteristics of the digital artifact after personalization.

[0051] More specifically, adjusting the display content feature matrix based on personalized customization information can accurately reflect the user's customization needs in the display characteristics of the digital artifacts. The customized display feature matrix records the new characteristics of the digital artifacts after meeting the user's personalized needs, providing a basis for subsequent information processing and display adjustments. By comparing the display content feature matrix and the customized display feature matrix, the differences between the digital artifacts before and after customization can be clearly understood, facilitating the evaluation and optimization of the customization effect.

[0052] More specifically, since the display content feature matrix and the customized display feature matrix contain a large amount of data, in order to reduce the amount of data and improve processing efficiency, it is necessary to compress the information of these two matrices. Some common data compression algorithms, such as Huffman coding and run-length encoding, can be used to remove redundant information in the matrix, retain key features, and convert the compressed matrix information into a format suitable for use in NFT smart contracts to generate a display customization factor. This factor can be a simple numerical value, a string, or a specific data structure, used to record and transmit personalized customization information of digital collectibles in smart contracts.

[0053] More specifically, in NFT smart contracts, various information about digital collectibles needs to be recorded and processed. The display content feature matrix and the customized display feature matrix contain a large amount of data. If these matrices are used directly, they will occupy a lot of storage space and transmission bandwidth. By compressing and converting information to generate display customization factors, the amount of data can be reduced and the efficiency of data transmission and storage can be improved. Display customization factors are a format suitable for use in smart contracts, which can easily interact and process with other parts of the smart contract. Converting personalized customization information into display customization factors can ensure that the smart contract can accurately identify and process the customization needs of digital collectibles, and realize personalized customization transactions of digital collectibles.

[0054] Furthermore, the step of compressing information between the display content feature matrix and the customized display feature matrix includes: Based on the display content feature matrix and the customized display feature matrix, a covariance matrix is ​​calculated to obtain a first covariance matrix corresponding to the display content feature matrix and a second covariance matrix corresponding to the customized display feature matrix; The first covariance matrix and the second covariance matrix are decomposed into eigenvalues, and the first projection matrix and the second projection matrix are formed based on the eigenvalues ​​and eigenvectors obtained from the decomposition. The display content feature matrix and the customized display feature matrix are projected onto the first projection matrix and the second projection matrix, respectively, to obtain the first compression matrix and the second compression matrix.

[0055] Furthermore, the step of synchronizing the display information layer and the hidden information layer according to the personalized customization information includes: S41: Parse the existing form of the display information layer to generate existing display information, and adjust the existing display information according to the personalized customization information to obtain the expected display information; S42: Parse the existing form of the hidden information layer to generate existing hidden information, and combine the expected display information with the existing hidden information to simulate the superposition display effect and generate the expected observation effect; S43: Using the expected observation effect as a supervision condition, the existing hidden information is subjected to trial adjustment of the representation form and simulation of the superimposed display effect until the representation form with the best expected observation effect is obtained, and the existing form of the hidden information layer is adjusted according to the representation form.

[0056] Specifically, the system uses a specific parsing algorithm to analyze the existing format of the digital artifact display information layer. If the display information layer is presented in image form, it will analyze the image's pixels, color mode, resolution, etc.; if it contains text, it will analyze the font, font size, content, etc., thereby converting it into existing display information that the computer can understand and process. Based on the personalized customization information provided by the user, such as changing image colors, adding specific text, adjusting layout, etc., the existing display information will be modified accordingly. For example, if the user requests to change the main color of the image from blue to red, the system will adjust the color values ​​of the image pixels; if text descriptions are required, the system will add text in appropriate positions and set the format, ultimately obtaining the expected display information.

[0057] More specifically, when users trade digital collectibles, they usually hope that the digital collectibles can be customized according to their own wishes. Adjusting the display information layer can directly meet users' personalized needs in terms of appearance, content, etc., improve users' satisfaction and user experience with digital collectibles, and obtain the expected display information provides a basis and reference for the subsequent adjustment of the hidden information layer. The adjustment of the hidden information layer needs to be coordinated with the display information layer. The expected display information determines the overall display framework and style, which helps to achieve the synchronization and unification of the two layers of information in the future.

[0058] More specifically, a parsing method specifically designed for the hidden information layer is used to process its existing form. The hidden information layer contains encrypted data, metadata, etc. The parsing process will decrypt this data, extract key information, and convert it into existing hidden information that can be used for subsequent simulation. The existing hidden information is then decomposed to obtain several hidden information units. The positional mapping relationship between each hidden information unit and the expected display information is analyzed. For example, if a hidden information unit corresponds to a specific area or element in the expected display information, the relative position and association between them are determined.

[0059] More specifically, based on the positional mapping relationship, each hidden information unit is overlaid with the expected display information. Using the overlaid position of the hidden information unit as a reference point, information within a specified range of the expected display information is selected to construct a spatial window. The expected display information within the spatial window and the hidden information units at the reference point are then substituted into a pre-trained human eye observation simulation model to simulate the human eye observation effect after their overlay, generating observation effect features for each hidden information unit. Finally, the observation effect features of each hidden information unit are combined to obtain the expected observation effect.

[0060] More specifically, the display and hidden information layers of digital artifacts are superimposed during actual display. Their combined effect directly affects the user's visual experience. By simulating the expected observation effect, the overall coordination of the two layers of information superimposed can be assessed in advance, avoiding problems such as information conflicts and visual interference. This ensures that the digital artifacts have a good visual effect when displayed. The human eye observation effect is what the user directly perceives. Simulating the human eye observation effect can ensure that the digital artifacts presented to the user in the end meet the user's visual expectations, providing a better user experience. At the same time, it also helps to discover potential display problems and make timely adjustments and optimizations.

[0061] More specifically, with the expected observation effect as the goal, the existing form of hidden information is adjusted experimentally, such as changing the transparency, color, and shape of the hidden information units. After each adjustment, the superimposed display effect is simulated again to evaluate the degree of matching between the new observation effect and the expected observation effect. The process of trial adjustment and simulation is repeated continuously. By comparing the observation effects obtained from each simulation, the form of expression that best matches the expected observation effect is found, that is, the form of expression with the best expected observation effect. Based on the determined best form of expression, the existing form of the hidden information layer is adjusted so that the hidden information layer can achieve the best visual effect when superimposed on the display information layer.

[0062] More specifically, after the displayed information layer is personalized, the hidden information layer also needs corresponding adjustments to maintain consistency and coordination with it. By adjusting based on the expected observation results, it can be ensured that the hidden information layer can still perfectly integrate with the displayed information layer in the context of the new display information layer, jointly presenting the best overall effect. The hidden information layer usually contains key information related to the uniqueness and copyright of digital collectibles. During the adjustment process, it is necessary to meet the needs of personalized customization while ensuring the security and identifiability of this key information. Through continuous trial adjustments and simulations, the optimal form of expression can be found to balance these two aspects.

[0063] Furthermore, the step of simulating the overlay display effect by combining the expected display information with the existing hidden information to generate the expected observation effect includes: S421: Decompose the existing hidden information to obtain several hidden information units, and analyze the positional mapping relationship of each hidden information unit corresponding to the expected display information; S422: Based on the position mapping relationship, the hidden information units are overlaid with the expected display information, and a spatial window is constructed based on the overlay position of the hidden information units to simulate the human eye observation effect after the expected display information and the hidden information units are overlaid in the spatial window, and to generate the observation effect features of the hidden information units. S423: Combine the observation effect features of each of the hidden information units to obtain the expected observation effect.

[0064] Specifically, using specific algorithms or rules, existing hidden information is decomposed into multiple relatively independent hidden information units with specific meanings. For example, if the hidden information is an encrypted text description, it can be decomposed according to sentences, keywords, etc.; if it is graphical hidden information, it can be divided according to different parts of the graphic. By comparing the content and structure of each hidden information unit with the expected display information, the positional correspondence between them can be determined. This mapping relationship can be described by coordinates, area range, etc. For example, a certain hidden information unit corresponds to the upper left corner of the image in the expected display information, or corresponds to a specific paragraph in a text description.

[0065] More specifically, existing hidden information is broken down into multiple hidden information units, which facilitates more detailed analysis and processing of the hidden information. Different hidden information units have different functions and roles. By breaking them down, they can be operated and adjusted separately. Analyzing the positional mapping relationship between the hidden information units and the expected display information is the key to achieving accurate overlay. Only by clarifying the positional correspondence between the two can the hidden information units be correctly placed into the expected display information to ensure that the overlay effect meets the design requirements.

[0066] More specifically, based on the obtained positional mapping relationship, each hidden information unit is accurately placed in the corresponding position of the expected display information to achieve superposition of the two. Taking the superposition position of the hidden information unit as the reference point, a certain range of area is selected in the expected display information to construct a spatial window. The size and shape of this spatial window can be set according to actual needs and simulation accuracy. It usually includes the hidden information unit and the expected display information within a certain range around it. The expected display information inside the spatial window and the hidden information unit at the reference point are substituted into a pre-trained human eye observation simulation model. This model takes into account the visual characteristics of the human eye, such as contrast perception, color sensitivity, attention distribution, etc., and simulates the human eye observation effect after information superposition, outputting the observation effect features of each hidden information unit. These features can be represented by numerical values, vectors, or other data structures.

[0067] More specifically, when observing digital artifacts, the human eye typically focuses on specific local areas. By constructing spatial windows and overlaying information within these windows, as well as simulating the effects of human observation, we can more realistically reflect the visual experience of the human eye during actual observation. This avoids the computational complexity and inaccuracies associated with globally simulating the entire digital artifact, generating observational effect characteristics of hidden information units. This transforms the subjective visual experience of the human eye into quantifiable data, facilitating subsequent analysis and comparison. These characteristics can serve as a basis for adjusting the representation of the hidden information layer to achieve the best visual effect.

[0068] More specifically, the observation effect features of each hidden information unit can be integrated according to certain rules. Simple methods such as splicing and weighted summation can be used to combine the features into a whole expected observation effect. This expected observation effect can reflect the visual performance of the entire digital collection after the display information layer and the hidden information layer are superimposed.

[0069] More specifically, the observation effect characteristics of a single hidden information unit can only reflect its local visual performance. By combining the observation effect characteristics of all hidden information units, the expected observation effect of the entire digital collection can be obtained, thereby comprehensively evaluating the overall visual effect of the digital collection. The expected observation effect can be used as a monitoring condition to guide the adjustment of the presentation of the hidden information layer. By continuously optimizing the presentation of the hidden information units, the final expected observation effect can be optimized, achieving the coordination and unity of the display information layer and the hidden information layer.

[0070] Furthermore, the step of constructing a spatial window based on the superposition position of the hidden information unit, and simulating the human eye's observation effect after superimposing the expected display information and the hidden information unit within the spatial window, to generate the observation effect features of the hidden information unit includes: S4221: Using the superposition position of the hidden information unit as a reference point, select information within a specified range for the expected display information to construct a spatial window for the hidden information unit; S4222: Substitute the expected display information inside the spatial window and the hidden information unit at the reference point into the pre-trained human eye observation simulation model to simulate the human eye observation effect after the hidden information unit and the expected display information are superimposed, and generate the observation effect feature of the hidden information unit.

[0071] Specifically, first, the superposition position of the hidden information unit in the expected display information is determined, and this position is used as a reference point. This reference point can be a specific coordinate (such as pixel coordinates on a two-dimensional plane) to determine the starting position of the spatial window. According to preset rules or actual needs, a certain range is expanded outward from the reference point. Information within this range is selected from the expected display information. The size of the range can be adjusted according to different situations, such as the size and importance of the hidden information unit and the visual attention range of the human eye. The selected information constitutes the spatial window of the hidden information unit, and this window contains the expected display information part related to the hidden information unit.

[0072] More specifically, when observing an object, the human eye usually focuses on a specific local area rather than paying attention to the entire image at the same time. By constructing a spatial window based on the superposition position of the hidden information unit, attention can be focused on the key information related to the hidden information unit, reducing unnecessary information interference and improving the accuracy and efficiency of the simulation. Performing a comprehensive human eye observation simulation of the entire expected display information would bring a huge computational burden. Constructing a spatial window to select only the part of the information related to the hidden information unit for simulation can significantly reduce the amount of computation, improve the processing speed, and at the same time ensure the validity of the simulation results.

[0073] More specifically, the expected display information within the spatial window and the hidden information units at the reference point are used as input data and passed to the pre-trained human eye observation simulation model. These input data need to undergo certain format conversion and preprocessing to adapt to the model's requirements.

[0074] More specifically, the human eye observation simulation model processes and analyzes the input information, simulating the visual experience of the human eye after seeing the hidden information unit superimposed with the expected display information. The model considers various factors, such as color contrast, brightness, shape, texture, etc., as well as the visual characteristics of the human eye, such as attention distribution and visual sensitivity. After simulation calculation, the model outputs the observation effect characteristics of the hidden information unit. These characteristics can be numerical, vector, or other data structures, used to describe the visual performance of the hidden information unit after superposition, such as clarity, recognizability, and visual appeal.

[0075] More specifically, human visual perception is subjective and complex, influenced by a variety of factors. Human eye observation simulation models, through learning and training on a large amount of visual data, can simulate the visual response of the human eye under different conditions, thus more realistically reflecting the actual observation effect after the hidden information unit and the expected display information are superimposed. The generated observation effect features transform the subjective visual perception of the human eye into quantifiable data, providing a clear evaluation standard for subsequent adjustments and optimizations of the hidden information unit. By comparing the observation effect features of different hidden information units, it is possible to determine which aspects need improvement and how to improve them to achieve the best visual effect.

[0076] Furthermore, during the trial adjustment of the representation of the existing hidden information, the unique identifier code of the digital collection is analyzed through the information image expression standard to obtain several representation forms for feedback of the unique identifier code.

[0077] Specifically, the function of the hidden information layer is to use information hidden within the digital artifact to provide feedback on the unique identifier code of the digital artifact, thereby authenticating the authenticity and uniqueness of the digital artifact. Therefore, all existing forms of hidden information need to have the function of providing feedback on the unique identifier code. That is, the unique identifier code is parsed through the information image expression standard to obtain several forms of expression. Then, the effect characteristics of various forms of expression are analyzed and compared to determine the best form of expression.

[0078] Based on the technical content of the NFT-based digital collectible trading method described in the above-disclosed embodiments, the present invention provides a multi-account trading management system based on NFT tokens, the structure of which is as follows: Figure 2 The method for implementing the NFT-based digital collectible trading method described in any one of the first aspects includes: The encoding and decoding module is used to deconstruct the information layer of the digital collectibles to be traded, to obtain the display information layer and the hidden information layer of the digital collectibles, and to obtain the unique identification code of the digital collectibles by decoding the hidden information layer. The information acquisition module is used to acquire the account information of a first account holding the digital collectible and a second account waiting to receive the digital collectible, and at the same time acquire the personalized customization information of the second account for the digital collectible; The transaction record module is used to use the unique identifier code, the account information, and the personalized customization information as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain. The collection adjustment module is used to transfer the digital collection from the first account to the second account, and to synchronously adjust the displayed information layer and the hidden information layer according to the personalized customization information.

[0079] In this embodiment, the specific implementation of each module in the above system embodiment is described in the above method embodiment, and will not be repeated here.

[0080] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0081] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0082] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for trading digital collectibles based on NFTs, characterized in that, include: The digital collectibles to be traded are disassembled into information layers to obtain the display information layer and the hidden information layer of the digital collectibles. The unique identification code of the digital collectibles is obtained by interpreting the hidden information layer. Obtain the account information of the first account holding the digital collectible and the second account waiting to receive the digital collectible, and at the same time obtain the personalized customization information of the second account for the digital collectible; The unique identifier, account information, and personalized customization information are used as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain. The digital collection is transferred from the first account to the second account, and the displayed information layer and the hidden information layer are adjusted synchronously according to the personalized customization information.

2. The method for trading NFT-based digital collectibles as described in claim 1, characterized in that, The steps of disassembling the digital collectible to be traded into a display information layer and a hidden information layer, and obtaining the unique identifier code of the digital collectible by interpreting the hidden information layer, include: By pre-deploying a first account to receive several mnemonic phrases input by the user, the corresponding digital key is activated; The digital key is used to unlock the digital collectible to be traded, so that the digital collectible can be switched from a locked state to an unlocked state. The information layer decomposition algorithm corresponding to the digital collectible is invoked to decompose the information layer of the digital collectible in the unlocked state, thereby obtaining the display information layer and the hidden information layer of the digital collectible. The hidden information layer is interpreted based on a preset identification coding standard to obtain the unique identification code of the digital collection.

3. The method for trading NFT-based digital collectibles as described in claim 1, characterized in that, The steps of using the unique identifier code, the account information, and the personalized customization information as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain include: The unique identifier code, the account information, and the personalized customization information are converted to obtain the collection identifier factor, the account transaction factor, and the display customization factor. The parameters of the NFT smart contract's minting function are adjusted based on the display customization factor, the collection identification factor, and the account transaction factor to obtain the minting function of the NFT smart contract corresponding to the current transaction. The NFT smart contract containing the casting function is uploaded to the blockchain to record the ownership transactions of the digital collectible.

4. The method for trading NFT-based digital collectibles as described in claim 3, characterized in that, The steps for converting the personalized information to obtain the display customization factor include: The display information layer of the digital collection is interpreted and expressed in vector form to obtain the display content feature matrix; Based on the personalized customization information, the display content feature matrix is ​​analyzed to obtain the customized display feature matrix of the digital collection corresponding to the personalized customization information. The display content feature matrix and the customized display feature matrix are compressed and transformed to generate a display customization factor.

5. The method for trading NFT-based digital collectibles as described in claim 1, characterized in that, The steps of synchronizing the display information layer and the hidden information layer according to the personalized customization information include: The existing form of the display information layer is parsed to generate existing display information, and the existing display information is adjusted according to the personalized customization information to obtain the expected display information; The existing form of the hidden information layer is parsed to generate existing hidden information, and the expected display information is combined with the existing hidden information to simulate the superposition display effect and generate the expected observation effect. Using the expected observation effect as a monitoring condition, the existing hidden information is subjected to trial adjustments and superimposed display effect simulation until the best expected observation effect is obtained, and the existing form of the hidden information layer is adjusted according to the expected observation effect.

6. The method for trading NFT-based digital collectibles as described in claim 5, characterized in that, The steps for simulating the overlay display effect by combining the expected display information with the existing hidden information to generate the expected observation effect include: The existing hidden information is decomposed to obtain several hidden information units, and the positional mapping relationship between each hidden information unit and the expected display information is analyzed. According to the position mapping relationship, each of the hidden information units and the expected display information are overlaid in position, and a spatial window is constructed based on the overlay position of the hidden information units to simulate the human eye observation effect after the expected display information and the hidden information units are overlaid in the spatial window, and to generate the observation effect features of the hidden information units. The observation effect features of each of the hidden information units are combined to obtain the expected observation effect.

7. The method for trading NFT-based digital collectibles as described in claim 6, characterized in that, The steps of constructing a spatial window based on the superposition position of the hidden information unit, simulating the human eye's observation effect after superimposing the expected display information and the hidden information unit within the spatial window, and generating the observation effect features of the hidden information unit include: Using the superposition position of the hidden information unit as a reference point, information within a specified range is selected for the expected display information to construct a spatial window for the hidden information unit; The expected display information inside the spatial window and the hidden information unit at the reference point are substituted into a pre-trained human eye observation simulation model to simulate the human eye observation effect after the hidden information unit and the expected display information are superimposed, and to generate the observation effect features of the hidden information unit.

8. The method for trading NFT-based digital collectibles as described in claim 6, characterized in that, During the trial adjustment of the representation of the existing hidden information, the unique identifier code of the digital collection is analyzed through the information image expression standard to obtain several representation forms for feedback of the unique identifier code.

9. A multi-account transaction management system based on NFT tokens, characterized in that, include: The encoding and decoding module is used to deconstruct the information layer of the digital collectibles to be traded, to obtain the display information layer and the hidden information layer of the digital collectibles, and to obtain the unique identification code of the digital collectibles by decoding the hidden information layer. The information acquisition module is used to acquire the account information of a first account holding the digital collectible and a second account waiting to receive the digital collectible, and at the same time acquire the personalized customization information of the second account for the digital collectible; The transaction record module is used to use the unique identifier code, the account information, and the personalized customization information as the minting function of the NFT smart contract to record the ownership transaction of the digital collectible on the blockchain. The collection adjustment module is used to transfer the digital collection from the first account to the second account, and to synchronously adjust the displayed information layer and the hidden information layer according to the personalized customization information.

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