Data processing method, data recognition device, medium, and program product

Abstract

The embodiment of the application discloses a data processing method, a data recognition device, a medium and a program product, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving. The method comprises the following steps: obtaining target digital collectible data from a digital collectible request, obtaining collectible attribute information of the target digital collectible data, determining a feature extraction algorithm for the target digital collectible data, performing feature extraction on the target digital collectible data according to the determined feature extraction algorithm, obtaining reference features of the target digital collectible data, recording the reference features into a metadata field, obtaining metadata text of the target digital collectible data, generating block data, and performing chain processing on the block data. By adopting the embodiment of the application, the subsequent processing of the related data of the digital collectible can be facilitated by optimizing the stored content.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a data processing method, a data recognition device, a medium and a program product. BACKGROUND

[0002] Copyright, also known as copyright, mainly involves various works, such as novels, pictures, videos, and various design drawings, etc. For these works, copyright can be confirmed through copyright registration; for digital works, their copyright can also be registered and recorded by third-party platforms (such as relevant industry associations, etc.), especially some digital collections (also known as digital assets) can choose a mass copyright protection platform associated with third-party technologies such as digital fingerprint technology and notarized mailbox to confirm rights.

[0003] In the storage process of data copyright related to various digital collections, how to optimize the storage method to make the subsequent use of the data related to the digital collections more convenient has become a hot research problem. SUMMARY

[0004] The embodiments of the present application provide a data processing method, a data recognition device, a medium and a program product, which optimize the stored content and facilitate subsequent processing of data related to digital collections.

[0005] In one aspect, the embodiments of the present application provide a data processing method, which comprises:

[0006] Obtaining target digital collection data from a digital collection request, and obtaining collection attribute information of the target digital collection data; the digital collection request is generated based on a digital collection block protocol;

[0007] Determining a feature extraction algorithm for the target digital collection data, and performing feature extraction on the target digital collection data according to the determined feature extraction algorithm to obtain reference features of the target digital collection data;

[0008] Recording the reference features into a metadata field of the target digital collection data to obtain a metadata text of the target digital collection data; the metadata field is a data storage field defined in the digital collection block protocol;

[0009] Generating block data, and performing on-chain processing on the block data; wherein the collection attribute information and the metadata text are recorded in the block data.

[0010] In one aspect, the embodiments of the present application provide a data acquisition method, which comprises:

[0011] Receiving a recognition result of data recognition on to-be-detected digital collection data;

[0012] The object data displayed in the object display area of the display interface includes to-be-detected digital collectible data, and / or reference digital collectible data matched with the to-be-detected digital collectible data.

[0013] The identification result displayed in the attribute display area of the display interface includes collectible attribute information obtained for the to-be-detected digital collectible data.

[0014] In an aspect, an embodiment of the present application provides a data processing apparatus, which comprises:

[0015] The acquisition module is configured to acquire target digital collectible data from a digital collectible request and acquire collectible attribute information of the target digital collectible data; the digital collectible request is generated based on a digital collectible block protocol;

[0016] The processing module is configured to determine a feature extraction algorithm for the target digital collectible data and perform feature extraction on the target digital collectible data according to the determined feature extraction algorithm to obtain reference features of the target digital collectible data.

[0017] The processing module is further configured to record the reference features in a metadata field to obtain a metadata text of the target digital collectible data; the metadata field is a data storage field defined in the digital collectible block protocol.

[0018] The processing module is further configured to generate block data and perform on-chain processing on the block data; wherein the collectible attribute information and the metadata text are recorded in the block data.

[0019] In an aspect, an embodiment of the present application provides a data acquisition apparatus, which comprises:

[0020] The receiving module is configured to receive an identification result of data identification on to-be-detected digital collectible data.

[0021] The display module is configured to display object data in an object display area of a display interface, the object data including to-be-detected digital collectible data, and / or reference digital collectible data matched with the to-be-detected digital collectible data.

[0022] The display module is further configured to display the identification result in an attribute display area of the display interface, the identification result including collectible attribute information obtained for the to-be-detected digital collectible data.

[0023] In an aspect, an embodiment of the present application provides a data identification device, which comprises a processor and a memory, wherein the memory is configured to store a computer program, the computer program comprising program instructions, and the processor is configured to invoke the program instructions to execute part or all of the steps in the above method.

[0024] In one aspect, the embodiments of the present application provide a computer readable storage medium, which stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, the program instructions are used to execute part or all of the steps in the above method.

[0025] Accordingly, according to an aspect of the present application, a computer program product or computer program is provided. The computer program product or computer program includes program instructions stored in a computer readable storage medium. A processor of a computer device reads the program instructions from the computer readable storage medium. The processor executes the program instructions, so that the computer device executes the above-provided data processing method.

[0026] In the embodiments of the present application, the target digital collectible data can be obtained from the digital collectible request, the collectible attribute information of the target digital collectible data can be obtained, the feature extraction algorithm for the target digital collectible can be determined, the feature extraction algorithm for the target digital collectible can be determined, the reference feature of the target digital collectible can be obtained, the reference feature can be recorded in the metadata field, the metadata text of the target digital collectible can be obtained, the block data can be generated, and the block data can be processed. By the above method, the reference feature can be added to the block data of the target digital collectible, which can better meet the use demand of the data feature of the subsequent digital collectible related data to a certain extent. BRIEF DESCRIPTION OF DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application. Those skilled in the art can obtain other drawings according to these drawings without creating any creative labor.

[0028] Figure 1 An application architecture schematic diagram is provided for the embodiments of the present application.

[0029] Figure 2 A flowchart of a data processing method is provided for the embodiments of the present application.

[0030] Figure 3a A flowchart of a data processing method is provided for the embodiments of the present application.

[0031] Figure 3b A flowchart of a data processing method is provided for the embodiments of the present application.

[0032] Figure 4a A scene schematic diagram for determining feature similarity is provided for the embodiments of the present application.

[0033] Figure 4b A scene schematic diagram for determining feature similarity provided for an embodiment of the present application;

[0034] Figure 4c A scene schematic diagram for determining feature similarity provided for an embodiment of the present application;

[0035] Figure 5 A scene schematic diagram for on-chain of reference digital collection data provided for an embodiment of the present application;

[0036] Figure 6 A scene schematic diagram for identifying digital collection data to be detected provided for an embodiment of the present application;

[0037] Figure 7 A flow schematic diagram of a data acquisition method provided for an embodiment of the present application;

[0038] Figure 8 A schematic diagram of a display interface provided for an embodiment of the present application;

[0039] Figure 9 A structural schematic diagram of a data processing apparatus provided for an embodiment of the present application;

[0040] Figure 10 A structural schematic diagram of a data acquisition apparatus provided for an embodiment of the present application;

[0041] Figure 11 A structural schematic diagram of a data recognition device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0043] The data processing method provided in the embodiments of the present application is implemented in a data identification device, which can be a server or a terminal. The server can be a standalone physical server, a server cluster or a distributed system composed of multiple physical servers, a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN (Content Delivery Network), and big data and artificial intelligence platform, etc. The terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a smart voice interaction device, a smart home appliance, a flying vehicle, etc., but is not limited thereto. The embodiments of the present application can be applied to various scenarios, including but not limited to cloud technology, artificial intelligence, intelligent transportation, and assisted driving.

[0044] Next, the technical terms and concepts related to the embodiments of the present application are introduced as follows:

[0045] The present application relates to the blockchain technology. The blockchain is a stringed text record (also known as a block) that is stringed and protected by cryptography. Each block contains the cryptographic hash of the previous block, the corresponding timestamp, and transaction data (usually represented by the hash value calculated by the Merkle tree algorithm), which makes the block content difficult to tamper with. The distributed ledger stringed by the blockchain technology can effectively record transactions between two parties and permanently verify the transactions. The technical solution of the present application can identify the data on the blockchain to achieve authentication and search of the blockchain data. One of the core technologies of the blockchain is the smart contract, which is a computer protocol designed to disseminate, verify, or execute contracts in an information-based way. The smart contract allows trusted transactions without a third party, which can be traced and irreversible.

[0046] In some embodiments, please refer to Figure 1 , Figure 1 An application architecture diagram is provided for the embodiments of the present application, and the data processing method provided in the present application can be executed through the application architecture. As Figure 1As shown, the data recognition device and the electronic device can be included; the data recognition device can obtain target digital collectible data to be chained and corresponding collectible attribute information thereof, perform feature extraction on the target digital collectible data according to a feature extraction algorithm determined based on the target digital collectible data to obtain reference features, record the reference features in a metadata field to obtain a metadata text, and generate block data recording the collectible attribute information and the metadata text, which can be chained and stored on a blockchain, such as a reference block associated with the target digital collectible, i.e., the block data can serve as a reference block on the blockchain; the reference features can be used for data recognition on the blockchain, i.e., the electronic device can generate a data recognition request carrying to-be-detected digital collectible data and send it to the data recognition device, the data recognition device determines verification features corresponding to the to-be-detected digital collectible data according to the feature extraction rule, determines a target reference block from a plurality of reference blocks on the blockchain based on the verification features, the target reference block records target reference features matching the verification features, obtains collectible attribute information recorded in the target reference block and returns it to the electronic device, and the electronic device displays the collectible attribute information and / or reference digital collectible data associated with the target reference block in a display interface, to realize data recognition on the blockchain. The electronic device can be a terminal or a background server corresponding to the terminal.

[0047] It can be understood that, Figure 1 The application architecture is only illustrative of possible application architectures of the technical solution of the present application, and does not limit the specific architecture of the technical solution of the present application, i.e., the technical solution of the present application can also provide other forms of application architectures.

[0048] In one possible implementation, the data recognition device can execute the data processing method according to actual business needs to realize searching for existing stored digital collectible data on the blockchain. The various digital collectibles involved in the present application can refer to various versions of works and other data. The technical solution of the present application can be applied to any blockchain data recognition scenario, i.e., the data recognition device can obtain reference features of reference digital collectible data and record them in a metadata field to obtain metadata text of the reference digital collectible data when the reference digital collectible data is chained, and generate block data recording the metadata text, and subsequently, when to-be-detected digital collectible data is obtained, verification features of the to-be-detected digital collectible data can be determined according to a feature extraction rule, the target reference block can be determined by matching the verification features and reference features recorded in each reference block on the blockchain, and collectible attribute information recorded in the target reference block can be obtained to realize data recognition on the blockchain. The feature matching method can improve recognition accuracy and efficiency.

[0049] In a possible implementation, the data such as the reference digital collection data, the reference features of the reference digital collection data, and the like involved in the present application can be stored in a database or can be stored in a blockchain, such as being stored by a blockchain distributed system, which is not limited in the present application.

[0050] It should be noted that in each specific implementation of the present application, when the relevant data in the case of involving user information or any data acquisition scenario needs to be obtained, the user's permission or consent needs to be obtained when the embodiments of the present application acquire these information or data for use in specific products or technologies, and the collection, use and processing of the relevant data need to comply with relevant laws, regulations and standards of the country and region. In some embodiments, when the terminal is requested to acquire data, data acquisition prompt information or a data acquisition interface can be generated to apply for the right to acquire data from the user. On the prompt information or interface, the user will be clearly prompted with the indication information of the data to be acquired so as to prompt the user that the data to be acquired this time is which data. Only after the user determines to collect, the information or data will be collected and uploaded. For example, when generating block data, the blockchain address of the user to which the target digital collection belongs also needs to be acquired. When acquiring the blockchain address, data acquisition prompt information can be sent to the terminal of the user, and the data recognition device can have the right to acquire the blockchain address after the user allows, and then the data is collected. Otherwise, the relevant data will not be collected, and a data acquisition failure prompt information will be sent to prompt the relevant user object in time.

[0051] It can be understood that the above scenarios are only examples and do not constitute a limitation on the application scenarios of the technical solutions provided by the embodiments of the present application. The technical solutions provided by the embodiments of the present application can also be applied to other scenarios. For example, as known by those skilled in the art, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0052] Based on the above description, the embodiments of the present application provide a data processing method. The method can be executed by the data recognition device mentioned above, such as a smart phone, a tablet computer, a personal computer PC, a smart wearable device, and some servers, and the like. Please refer to Figure 2 , Figure 2 The flowchart of the data processing method provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the flow of the data processing method provided by the embodiments of the present application can include the following steps. Figure 2

[0053] ​S201: Obtain target digital collectible data from a digital collectible request, and obtain collectible attribute information of the target digital collectible data. The target digital collectible data can be data of any multimedia type, such as an image, a video, or text, and the like. The target digital collectible data can be data in any multimedia format, such as an image in a JPEG (Joint Photographic Experts Group) format or a GIF (Graphics Interchange Format) format, and the like. The specific type and format of the target digital collectible data are not limited herein. The digital collectible request is based on a digital collectible block protocol. The digital collectible request is used to indicate that the target digital collectible data is to be chained. The digital collectible block protocol can be any block protocol published in a smart contract on a blockchain for digital collectibles. The block protocol defines the related data required for a digital collectible to be chained, the required fields (such as data storage fields), and the storage format, and the like.

[0054] In some embodiments, the collectible attribute information can be copyright information and ownership information of the target digital collectible data, such as generation time, source, identity information of the owner, blockchain address of the owner, and the like. The collectible attribute information is not limited herein.

[0055] S202: Determine the feature extraction algorithm for the target digital collectible data, and perform feature extraction on the target digital collectible data according to the determined feature extraction algorithm to obtain the reference features of the target digital collectible data. The data recognition device can determine the algorithm for feature extraction on the target digital collectible data, and obtain the reference features of the target digital collectible data according to the algorithm. The feature extraction algorithm can have one or more, and the corresponding reference features also have one or more. The determination of the feature extraction algorithm for the target digital collectible data can be to determine the data type of the target digital collectible data, and to select a feature extraction algorithm for the target digital collectible data according to the determined data type. Different data types use different feature extraction algorithms, and the feature extraction algorithm is adapted to the corresponding data type. The data type can be classified according to the multimedia type of the target digital collectible data, for example, when the target digital collectible data is an image type, a feature extraction algorithm for extracting image features is selected for the target digital collectible data; when it is a video type, a feature extraction algorithm for extracting video features is selected for the target digital collectible data. The data type can also be classified according to the characteristics of the target digital collectible data, for example, the target digital collectible data is an image that recognizes the object and the background, the selected feature extraction algorithm can be an algorithm suitable for recognizing the key area and enhancing the local feature extraction, such as HOG (Histogram of Oriented Gradient, Histogram of Oriented Gradient) algorithm, etc.; for example, the target digital collectible data is an image that has been rotated, the selected feature extraction algorithm can be an algorithm suitable for rotating the image, such as SIFT algorithm, etc.; for example, the target digital collectible data is a video that recognizes the object running track, the selected feature extraction algorithm can be an algorithm suitable for capturing and grabbing the object running frame, such as DT algorithm, etc. The data type can also have other definitions, and the feature extraction algorithm can also have other selection methods, which can be set by relevant business personnel according to the actual scene.

[0056] It can be understood that the digital collectible data that has been chained on the blockchain is determined by the above-mentioned method to determine the feature extraction algorithm, and the corresponding reference features are obtained by feature extraction. At this time, the digital collectible data that has been chained on the blockchain can be referred to as reference digital collectible data. Each reference digital collectible data is associated with a block (which can be referred to as a reference block) on the blockchain.

[0057] S203: Record the reference features into the metadata field to obtain the metadata text of the target digital collectible data. The metadata field is a data storage field defined in the data collectible block protocol used by the target digital collectible data.

[0058] In a possible implementation, the data recognition device can record the reference features as field values into a metadata field (which can be referred to as a meta field) to obtain metadata text. The metadata text can be a file in a json format (a lightweight data exchange format), or a file in an XML (Extensible Markup Language) format, or the like.

[0059] In some embodiments, when the reference features are recorded into the metadata field, the feature extraction algorithms corresponding to the reference features can also be recorded into the metadata field, and in the obtained metadata text, the reference features and the feature extraction algorithms have a one-to-one mapping relationship.

[0060] In some embodiments, the data recognition device can also obtain the on-chain information of the target digital collectible data, and add the on-chain information to the metadata field to obtain the metadata text of the target digital collectible data. The feature extraction algorithm and the on-chain information can be different metadata fields. The on-chain information can include any one or more of a collectible identifier of the target digital collectible data, a collectible name, collectible description information, and a data pulling address of the target digital collectible data.

[0061] In some embodiments, the collectible description information can be determined based on specific display forms and specific display contents in the target digital collectible data. For example, the target digital collectible data is an image, and the collectible description information can be what the target object in the image is. The data pulling address can be an address for obtaining the target digital collectible data. For example, the data pulling address can be an opening link of the target digital collectible data, or the target digital collectible data can be stored in an IPFS (Inter Planetary File System, a distributed file storage system), and the storage link can be used as the data pulling address of the target digital collectible data.

[0062] In some embodiments, the collectible identifier of the target digital collectible data can be obtained by performing feature processing on the target digital collectible data using a specified feature processing algorithm. The specified feature processing algorithm can be a hash algorithm. The hash algorithm means that a data is converted into a binary stream, and a hash value is obtained by performing hash calculation on the binary stream. The hash value changes greatly when the data changes slightly (for example, the data is an image, and the image is stretched or watermarked). Therefore, the collectible identifier obtained by the hash algorithm can be referred to as a reference verification identifier of the target digital collectible data, and the reference verification identifier can uniquely represent the target digital collectible data.

[0063] In some embodiments, the collection identifier of the target digital collectible data can also be determined according to the selected blockchain, and can be determined according to the block height of the selected blockchain, for example, if the block height of the reference block generated most recently is 100, then the collection identifier of the target digital collectible data is 101.

[0064] In some embodiments, the collection identifier of the target digital collectible data can be associated with the block data corresponding to the target digital collectible data, and the block data corresponding to the target digital collectible data can be found through a relevant standard, and then the contents recorded in the block data such as the on-chain information, the reference features, the collection attribute information, and the like can be obtained. The collection identifier is directly found or found through a smart contract based on the collection identifier.

[0065] For example, assuming that the target digital collectible data is an image, and the metadata text is in json format, the required data can be recorded in the metadata text, such as the reference features, the on-chain information, the used feature extraction algorithm, and even the collection attribute information of the target digital collectible data. The on-chain information includes the "name" content corresponding to the collection name in the metadata text, for example, the name of the target digital collectible data is recorded as "ABC"; includes the "image" content corresponding to the data pulling address in the metadata text, for example, the acquisition link of the target digital collectible data is recorded as "https: / / XXXX.com / XXXXX / / 1.png"; includes the "characteristic" content corresponding to the feature information in the metadata text, and records that the reference feature "value1" corresponds to the feature extraction algorithm "pHash" and the reference feature "value2" corresponds to the feature extraction algorithm "DT"; includes the "attributes" content corresponding to the collection description information in the metadata text, for example, the target digital collectible data depicts a strong tiger, and the description information can be expressed as: the target object contained in the target digital collectible data is a tiger, and the target object is strong in body type, the target object is red in color, and the like. The collection description information can be used to verify the data identified on the blockchain again, and the process of the verification again can be referred to the relevant description of the following embodiments.

[0066] S204: Generate block data and perform on-chain processing on the block data. The collection attribute information and the metadata text are recorded in the block data.

[0067] In some embodiments, the data identification device can generate block data of the target digital collectible data, record the collectible attribute information and the metadata text in the block data, and perform on-chain processing of the block data on the blockchain, that is, the block data can be stored in a block (or can be referred to as a reference block) associated with the target digital collectible data on the blockchain. The data identification device can search the collectible attribute information and the metadata text stored on the corresponding reference block through the block height of the associated reference block and / or the collectible identifier.

[0068] In some embodiments, the data identification device can directly record the above-mentioned metadata text in the block data, that is, the format recorded in the block data at this time is: [collectible identifier, collectible attribute information, metadata text]; or the metadata text can be recorded in a linked manner, that is, the associated link of the metadata text is recorded in the block data, and the metadata text can be stored in a third-party storage point (such as a database), or can be stored on different blockchains from the block data, and the corresponding metadata text is obtained through the associated link. At this time, the format recorded in the block data is: [collectible identifier, collectible attribute information, associated link].

[0069] In some embodiments, after storing the block data of the target digital collectible data on the blockchain, the target digital collectible data can be referred to as reference digital collectible data associated with the reference block on the blockchain. Subsequently, data identification on the blockchain can be implemented based on the reference features recorded by each reference block on the blockchain. The specific identification process can be referred to the related description of the following embodiments.

[0070] In the embodiments of the present application, reference features can be added to the block data of the target digital collectible data to improve the richness of the block data on the blockchain, which can better meet some subsequent use requirements to a certain extent. For example, the requirements can be to implement matching in the blockchain through the reference features, to quickly and accurately search the digital collectible related data stored on the blockchain, to improve the data identification efficiency of the blockchain, and to meet the user's demand for automatic and intelligent search of related data such as copyright.

[0071] Please refer to Figure 3a , Figure 3a A flowchart of a data processing method provided in the embodiments of the present application is shown. The method can be executed by the above-mentioned data identification device, for example, a smart phone, a tablet computer, a personal computer (PC), a smart wearable device, and some servers, etc. As shown in Figure 3a The flowchart of the data processing method in the embodiments of the present application can include the following steps:

[0072] S301: Obtain a data identification request. In one possible implementation, the data identification request can also be generated and sent by the electronic device based on the digital collectible block protocol described in the foregoing embodiments.

[0073] The data identification request can carry to-be-detected digital collectible data. The to-be-detected digital collectible data can be described as described above with respect to the target digital collectible data.

[0074] S302: According to the determined feature extraction rule, the to-be-detected digital collectible data is subjected to feature extraction to obtain verification features corresponding to the to-be-detected digital collectible data.

[0075] In one possible implementation, there can be multiple reference blocks on the blockchain for data identification, and each reference block is associated with a reference digital collectible data. The associated reference digital collectible data can be data of any multimedia type and format. Each reference block can record block data of the reference digital collectible data associated with the reference block. The metadata text recorded by the block data can include a feature extraction algorithm of the reference digital collectible data associated with the reference block. One reference block can record one or more feature extraction algorithms, and the feature extraction algorithms recorded by different reference blocks can be the same or different. Therefore, the feature extraction rule can be to extract features from the to-be-detected digital collectible data according to the feature extraction algorithms recorded in the foregoing reference blocks, thereby obtaining the verification features corresponding to the to-be-detected digital collectible data.

[0076] In some embodiments, according to the feature extraction algorithms recorded in the foregoing reference blocks, the to-be-detected digital collectible data can be subjected to feature extraction to obtain verification features. This can be that each time a feature extraction algorithm recorded in a reference block is obtained, the to-be-detected digital collectible data is subjected to feature extraction to obtain verification features for the current reference block. If the currently obtained feature extraction algorithm has been obtained before, the feature extraction algorithm recorded in the next reference block is directly obtained, and the verification features obtained before are taken as the verification features for the current reference block. Alternatively, one or more feature extraction algorithms recorded in all reference blocks can be obtained first, and the to-be-detected digital collectible data is subjected to feature extraction using the one or more feature extraction algorithms in sequence to obtain one or more verification features (denoted as a verification feature set), and the verification features for the reference blocks are determined from the verification feature set according to the feature extraction algorithms recorded in the reference blocks.

[0077] The reference block can refer to all blocks in the blockchain or part of the blocks. The part of the blocks can refer to blocks with a preset time period (e.g., 10 years) of on-chain time or blocks associated with the reference digital collectible data. Optionally, the associated reference digital collectible data can refer to all digital collectible data that has been chained or digital collectible data of the same multimedia type as the digital collectible data to be detected, such as digital collectible data to be detected being of an image type, and the associated reference digital collectible data being all digital collectible data that has been chained and is of an image type. The determination of the reference block is not limited herein.

[0078] In one possible implementation, the feature extraction rule can further include determining a data type of the digital collectible data to be detected, obtaining a feature extraction algorithm matched with the data type of the digital collectible data to be detected, the matched feature extraction algorithm can be one or more, and performing feature extraction on the digital collectible data to be detected according to the matched feature extraction algorithm. The data type can refer to a multimedia type of the digital collectible data to be detected. For example, the digital collectible data to be detected is of an image type, and the matched feature extraction algorithm can be an algorithm for extracting image features, such as a perceptual hash (pHash) algorithm; the digital collectible data to be detected is of a video type, and the matched feature extraction algorithm can be an algorithm for extracting video features, such as a dense trajectory (DT) algorithm; and the like.

[0079] It can be understood that the matched feature extraction algorithm is a feature extraction algorithm predetermined according to the data type. If each reference block on the blockchain records a reference feature of the associated reference digital collectible data, the reference feature can be obtained in the same way as the verification feature, that is, a feature extraction algorithm matched with the reference digital collectible data is determined according to the data type of the reference digital collectible data, and the reference digital collectible data is then subjected to feature extraction based on the feature extraction algorithm to obtain the corresponding verification feature.

[0080] The metadata text recorded by the block data and the feature extraction algorithm have a one-to-one mapping relationship, that is, one feature extraction algorithm corresponds to one verification feature. When there are multiple feature extraction algorithms, the verification feature corresponding to the digital collectible data to be detected corresponds to multiple features obtained based on the multiple feature extraction algorithms.

[0081] S303: determining a target reference block from the multiple reference blocks of the blockchain based on the verification feature.

[0082] It should be noted that the reference block of the blockchain can refer to all blocks in the blockchain, or can refer to part of special blocks in the blockchain. Through the reference block, the reference feature and the corresponding collection attribute information can be obtained. The reference feature is used to verify and compare the verification feature to be verified and compared, and the collection attribute information includes copyright information of the reference digital collection data associated with the reference block, ownership information of the reference digital collection data, and the like, such as generation time, source, and owner of the reference digital collection data.

[0083] The target reference feature associated with the reference digital collection data of the target reference block matches the verification feature, the target reference feature can represent the feature that is most similar to the verification feature in the plurality of reference features recorded in the plurality of reference blocks, and the reference digital collection data associated with the target reference block matches the to-be-detected digital collection data.

[0084] In some embodiments, the data recognition device determines the target reference block from the plurality of reference blocks of the blockchain based on the verification feature. Specifically, the feature similarity between the to-be-detected digital collection data and the reference digital collection data associated with each reference block is determined according to the verification feature and the reference feature recorded in each reference block, and the target reference block is determined from each reference block according to the feature similarity. Optionally, the data recognition device can determine the feature similarity between the to-be-detected digital collection data and the reference digital collection data associated with each reference block after determining the verification feature for each reference block, or can determine the feature similarity after determining the verification feature for all reference blocks.

[0085] In some embodiments, the target reference block is determined from each reference block according to the feature similarity can be that the reference feature corresponding to the maximum feature similarity is taken as the target reference feature, and the reference block recording the target reference feature is taken as the target reference block. The maximum feature similarity indicates that the reference digital collection data associated with the target reference block is the most similar data to the to-be-detected digital collection data.

[0086] In some embodiments, the process and principle of determining the feature similarity of the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block are the same. Taking any one of the reference blocks of the block chain as an example, which is denoted as a transition reference block. The feature similarity of the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block can be determined according to the verification feature and the reference feature recorded in each reference block. According to the verification feature and the transition reference feature recorded in the transition reference block, the feature similarity of the to-be-detected digital collectible data and the reference digital collectible data associated with the transition reference block can be determined according to a preset determination manner. Wherein, the distance between the verification feature and the reference feature is calculated according to the preset determination manner, and the feature similarity is obtained according to the distance. The distance between the verification feature and the reference feature can be the Euclidean distance or Chebyshev distance between the verification feature and the reference feature, and the determination manner of the distance is not limited here. And the feature similarity can be obtained according to the distance, which can be the distance as the feature similarity, or the distance is mapped to a specified numerical range (such as 0-1), and the mapping result is taken as the feature similarity, and so on, which is not limited here. Alternatively, the preset determination manner can also have other ways, which is not limited here. It can be understood that whether it is a transition reference block or a target reference block, it belongs to a reference block, and it is a differentiated naming for convenience of description. The transition reference block is used to describe the reference block that can be verified and compared with the verification feature, and the reference feature in most of the transition reference blocks does not match the verification feature, and the named target reference block refers to the reference block whose reference feature matches the verification feature.

[0087] Alternatively, when there are multiple verification features for the transition reference block, there are also multiple transition reference features recorded in the transition reference block. When determining the above feature similarity, the similarity between the multiple verification features and the corresponding same feature extraction algorithm features in the multiple transition reference features can be calculated to obtain multiple initial similarities, and the multiple initial similarities are weighted and summed to obtain the final feature similarity. The weighting coefficient can be set by relevant business personnel according to experience value. The determination of the initial similarity can refer to the above description of the determination of the feature similarity.

[0088] For example, the feature extraction algorithm of the transition reference block record includes algorithm 1 and reference feature 1 based on algorithm 1, algorithm 2 and reference feature 2 based on algorithm 2, the verification feature of the transition reference block includes verification feature 1 and verification feature 2, verification feature 1 is based on algorithm 1, and verification feature 2 is based on algorithm 2, so the similarity between reference feature 1 and verification feature 1 is calculated to obtain initial similarity 1, the similarity between reference feature 2 and verification feature 2 is calculated to obtain initial similarity 2, and the weighted sum of initial similarity 1 and initial similarity 2 is obtained. The feature similarity between the reference digital collectible data associated with the transition reference block and the digital collectible data to be detected.

[0089] S304: Obtain the property information of the digital collectible recorded in the target reference block, and return the property information to the electronic device initiating the data identification request.

[0090] The property information of the digital collectible can include the ownership, the issuer, the generation time, or the unique code of the reference digital collectible data associated with the target reference block, and the like. The specific content of the property information of the digital collectible is not limited herein.

[0091] In some embodiments, the data identification device can perform blockchain data identification on the digital collectible data to be detected sent by the electronic device initiating the data identification request to obtain an identification result and return it to the electronic device. The identification result can include the property information of the digital collectible recorded in the target reference block and / or the reference digital collectible data associated with the target reference block and / or part of the data in the metadata text (such as the name of the digital collectible). The electronic device can display part or all of the data in the received property information of the digital collectible, such as displaying only the ownership, and the rest of the data can be displayed after the user of the electronic device queries; and / or the electronic device can display the reference digital collectible data (or display after querying) so that the identification party can view the relevant attributes or judge whether the reference digital collectible data is the digital collectible data to be detected. This can realize the copyright protection and right confirmation of the digital collectible on the chain (i.e. the reference digital collectible data), can prevent third parties from infringing the use of the digital collectible protected by copyright after fine-tuning, or can enable the identification party to locate the actual ownership of the digital collectible on the chain to buy and sell data assets.

[0092] In the embodiments of the present application, a data recognition request can be obtained, feature extraction is performed on the to-be-detected digital collectible data according to the determined feature extraction rule, verification features corresponding to the to-be-detected digital collectible data are obtained, a target reference block is determined from the plurality of reference blocks of the blockchain based on the verification features, collectible attribute information recorded in the target reference block is obtained, and the collectible attribute information is returned to the electronic device that initiates the data recognition request. Through the above method, the most matching target reference block can be quickly determined from the blockchain by using the verification features, the reference digital collectible data that is most likely related to the to-be-detected digital collectible data can be accurately identified on the blockchain, and attribute data such as the author of the digital collectible data is returned, which can improve the data recognition efficiency of the blockchain and meet the user's demand for automatic and intelligent search of related data such as copyright.

[0093] Please refer to Figure 3b , Figure 3b A flowchart of a data processing method provided in the embodiments of the present application is shown in the figure. The method can be executed by the data recognition device mentioned above, for example, a smart phone, a tablet computer, a personal computer (PC), a smart wearable device, a server, and the like. As shown in Figure 3b The flow of the data processing method in the embodiments of the present application can include the following steps:

[0094] S401: Obtain a data recognition request. The specific implementation of step S401 can be referred to the related description of the above embodiments, which will not be repeated here.

[0095] S402: Call a hash algorithm to determine the verification identification feature of the to-be-detected digital collectible data.

[0096] In some embodiments, since the hash algorithm will produce a large change in the case of slight data change. Therefore, the hash algorithm can be called to extract the features of the to-be-detected digital collectible data to obtain the verification identification feature, which can uniquely represent the to-be-detected digital collectible data. Let the collectible identification recorded in the reference block be the reference identification feature of the reference digital collectible data associated with each reference block. If the same feature as the verification identification feature is determined from the reference identification features recorded in the plurality of reference blocks, it indicates that the reference digital collectible data corresponding to the same reference identification feature is the to-be-detected digital collectible data. Therefore, the blockchain data recognition can be performed through the verification identification feature first, and then the recognition can be performed based on the verification features of the to-be-detected digital collectible data when no recognition is performed.

[0097] S403: If the target reference block is determined from the plurality of reference blocks of the blockchain based on the verification identification feature, the collectible attribute information is obtained from the target reference block and returned to the electronic device that initiates the data recognition request.

[0098] In some embodiments, the collection identifier recorded by the block data recorded by each reference block on the blockchain is a reference identifier feature for uniquely representing the reference digital collection data associated with each reference block, and the reference identifier feature is obtained based on feature extraction of the reference digital collection data by calling a hash algorithm.

[0099] Therefore, the data recognition device can determine whether there is a target reference identifier feature identical to the verification identifier feature in the reference identifier feature recorded by each reference block record. If there is, the reference block recording the target reference identifier feature is taken as the target reference block, so as to determine the target reference block from the plurality of reference blocks of the blockchain based on the verification identifier feature, and obtain the recorded collection attribute information from the target reference block, and return to the electronic device.

[0100] S404: If the target reference block is not determined based on the verification identifier feature, the feature extraction of the to-be-detected digital collection data is performed according to the determined feature extraction rule to obtain the verification feature corresponding to the to-be-detected digital collection data.

[0101] In some embodiments, if the reference identifier feature recorded by each reference block record is different from the verification identifier feature, it indicates that there is no data identical to the to-be-detected digital collection data in the reference digital collection data associated with each reference block. Therefore, the step of performing feature extraction of the to-be-detected digital collection data according to the determined feature extraction rule to obtain the verification feature corresponding to the to-be-detected digital collection data can be performed.

[0102] In one possible implementation, the reference block can record the feature extraction algorithm of the reference digital collection data associated with each reference block; and the data recognition device can perform feature extraction of the to-be-detected digital collection data according to the determined feature extraction rule to obtain the verification feature corresponding to the to-be-detected digital collection data. Specifically, the to-be-detected digital collection data can be extracted according to the feature extraction algorithm recorded by each reference block to obtain the verification feature of the to-be-detected digital collection data for each reference block.

[0103] Optionally, the feature extraction algorithms recorded by each reference block record can be the same or different, and the corresponding obtained verification features for each reference block can be the same or different; and the feature extraction algorithms recorded by each reference block record can be one or more, and the corresponding obtained verification features for each reference block can be one or more.

[0104] In some embodiments, the metadata recorded in the transition reference block of the reference blocks of the blockchain includes the first feature extraction algorithm and the second feature extraction algorithm, so that the feature extraction of the to-be-detected digital collectible data is performed according to the feature extraction algorithm recorded in each reference block, and the verification features of the to-be-detected digital collectible data for each reference block can be specifically obtained by performing feature extraction on the to-be-detected digital collectible data according to the first feature extraction algorithm to obtain first verification features, performing feature extraction on the to-be-detected digital collectible data according to the second feature extraction algorithm to obtain second verification features, and determining the verification features of the to-be-detected digital collectible data for the transition reference block according to the first verification features and the second verification features.

[0105] According to the first verification features and the second verification features, the verification features of the to-be-detected digital collectible data for the transition reference block can be directly used as the verification features of the to-be-detected digital collectible data for the transition reference block, or the first verification features and the second verification features can be preprocessed, and the preprocessing results can be used as the verification features of the to-be-detected digital collectible data for the transition reference block. The feature processing can be merging the first verification features and the second verification features, such as feature addition or feature fusion. The feature processing can be set by relevant business personnel according to the actual application scene, which is not limited herein. It can be understood that if the first feature extraction algorithm or the second feature extraction algorithm has been called to perform feature extraction, the feature extraction step can not be performed at this time, and the first verification features or the second verification features obtained previously can be directly used.

[0106] S405: Determine the target reference block from the plurality of reference blocks of the blockchain based on the verification features.

[0107] The target reference features of the reference digital collectible data associated with the target reference block match the verification features, and the associated reference digital collectible data is the most similar data to the to-be-detected digital collectible data.

[0108] In a possible implementation, the reference feature of the reference digital collectible data associated with each reference block can be recorded in the reference block; the data identification device can determine the target reference block from the plurality of reference blocks of the blockchain based on the verification feature, specifically, determine the feature similarity of the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block according to the verification feature of each reference block and the reference feature recorded in each reference block, determine the target reference feature from the reference feature recorded in each reference block according to the feature similarity, and determine the reference block recording the target reference feature as the target reference block. The target reference feature can be determined from the reference feature recorded in each reference block according to the feature similarity, that is, the reference feature corresponding to the maximum feature similarity can be taken as the target reference feature.

[0109] In some embodiments, when the reference feature of the reference digital collectible data associated with the reference block is multiple, and the verification feature of the to-be-detected digital collectible data for the reference block is multiple, a plurality of initial similarities can be determined through the plurality of reference features and the plurality of verification features, and the feature similarity can be determined according to the plurality of initial similarities. Therefore, the feature information recorded in the transition reference block in the blockchain further includes a first reference feature and a second reference feature, the first reference feature is obtained by performing feature extraction on the reference digital collectible data associated with the transition reference block based on the first feature extraction algorithm, and the second reference feature is obtained by performing feature extraction on the reference digital collectible data associated with the transition reference block based on the second feature extraction algorithm, and the verification feature of the to-be-detected digital collectible data for the transition reference block is obtained according to the first verification feature and the second verification feature; assuming that the first verification feature and the second verification feature are both taken as the verification feature of the to-be-detected digital collectible data for the transition reference block, the feature similarity of the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block can be determined according to the verification feature of the to-be-detected digital collectible data for each reference block and the reference feature recorded in each reference block, that is, the first initial similarity can be determined according to the first reference feature and the first verification feature, the second initial similarity can be determined according to the second reference feature and the second verification feature, the first initial similarity and the second initial similarity are weighted and summed to obtain the feature similarity of the to-be-detected digital collectible data and the reference digital collectible data associated with the transition reference block; the weighting coefficient can be set by relevant business personnel according to experience value. The specific process of determining the initial similarity can be referred to the related description of the above embodiments.

[0110] In some embodiments, the first feature processing result of the first verification feature and the second verification feature after feature processing is taken as the verification feature of the to-be-detected digital collectible data for the transition reference block. According to the verification features of the to-be-detected digital collectible data for each reference block and the reference features recorded by each reference block, the feature similarity of the reference digital collectible data associated with each reference block by the to-be-detected digital collectible data can be that the reference features recorded by the transition reference block are feature-processed to obtain a second feature processing result, and the similarity between the first feature processing result and the second feature processing result is calculated to obtain the feature similarity of the reference digital collectible data associated with the transition reference block by the to-be-detected digital collectible data. The specific process of calculating the similarity between the first feature processing result and the second feature processing result can be the same as the specific process of determining the initial similarity.

[0111] In some embodiments, one data recognition request can carry one or more to-be-detected digital collectible data, and the one or more to-be-detected digital collectible data are used for data recognition once. The reference digital collectible data associated with the reference block can be one or more. When the to-be-detected digital collectible data is one data and the reference digital collectible data associated with the reference block is one data, the specific process of performing feature similarity calculation and obtaining the target reference block to realize blockchain data recognition can refer to the related description of the above process.

[0112] When the to-be-detected digital collectible data is multiple and the reference digital collectible data associated with the transition reference block is one, the feature extraction algorithm recorded by the transition reference block can be used to extract features from the multiple to-be-detected digital collectible data respectively to obtain the verification feature corresponding to each to-be-detected digital collectible data respectively. According to the verification feature corresponding to each to-be-detected digital collectible data respectively and the reference feature of the associated reference digital collectible data recorded by the transition reference block, the feature similarity of each to-be-detected digital collectible data and the associated reference digital collectible data is determined respectively, and the multiple feature similarities are weighted and summed to obtain the total feature similarity of the multiple to-be-detected digital collectible data and the associated reference digital collectible data.

[0113] When there is one digital collectible data to be detected and multiple reference digital collectible data associated with the transition reference block, the feature extraction algorithm recorded in the transition reference block includes an algorithm for each reference digital collectible data and recorded reference features including the features of each reference digital collectible data. It can be that the digital collectible data to be detected is extracted according to the algorithm for each reference digital collectible data separately to obtain the verification features of the digital collectible data to be detected relative to each reference digital collectible data. Based on the verification features of the digital collectible data to be detected relative to each reference digital collectible data and the features of each reference digital collectible data, the feature similarity between the digital collectible data to be detected and each reference digital collectible data is determined. The multiple feature similarities are then weighted and summed to obtain the total feature similarity between the digital collectible data to be detected and the multiple reference digital collectible data as a whole.

[0114] When there are multiple digital artifact data sets to be detected, and multiple reference digital artifact data sets are associated with the transitional reference block, the feature similarity between each digital artifact data set to be detected and the collective reference digital artifact data sets can be determined separately. Then, a weighted sum of these feature similarities can be performed to obtain the overall feature similarity between the collective digital artifact data sets to be detected and the collective reference digital artifact data sets. The weighting coefficients used can be set by relevant personnel based on experience.

[0115] For example, such as Figure 4a - Figure 4c As shown, Figure 4a - Figure 4c This application provides a schematic diagram of a scenario for determining feature similarity; wherein:

[0116] like Figure 4a Let the digital artifact data to be detected include images A and B, and the reference digital artifact data associated with the transition reference block be image C. The reference features recorded in the transition reference block include feature 1 and feature 2, and the feature extraction algorithms include algorithm 1 and algorithm 2. Feature 1 corresponds to algorithm 1, and feature 2 corresponds to algorithm 2. Algorithm 1 is called to extract features from image A to obtain feature 3, and algorithm 2 is called to extract features from image A to obtain feature 4. Algorithm 1 is called to extract features from image B to obtain feature 5, and algorithm 2 is called to extract features from image B to obtain feature 6. Therefore, the similarity 1 between feature 3 and feature 1, and the similarity 2 between feature 4 and feature 2 are determined. Based on similarity 1 and similarity 2, the similarity ① between image A and image C is determined, as well as the similarity 3 between feature 5 and feature 1, and the similarity 4 between feature 6 and feature 2 are determined. Based on similarity 3 and similarity 4, the similarity ② between image B and image C is determined. The feature similarity between the digital artifact data to be detected and the reference digital artifact data is obtained by weighted summation of similarity ① and similarity ②.

[0117] For example, such asFigure 4b Let the digital artifact data to be detected include image A, and the reference digital artifact data associated with the transition reference block be images B and C. The reference features recorded in the transition reference block include features 1 and 2 corresponding to image B, and features 3 and 4 corresponding to image C. The recorded feature extraction algorithms include algorithm 1, algorithm 2, and algorithm 3. Features 1 and 3 correspond to algorithm 1, features 2 correspond to algorithm 2, and features 4 correspond to algorithm 3. Algorithm 1 is called to extract features from image A to obtain feature 5, algorithm 2 is called to extract features from image A to obtain feature 6, and algorithm 3 is called to extract features from image A to obtain feature 7. Therefore, the similarity 1 between feature 5 and feature 1, and the similarity 2 between feature 6 and feature 2 are determined. Based on similarity 1 and similarity 2, the similarity ① between image A and image B is determined, as well as the similarity 3 between feature 5 and feature 3, and the similarity 4 between feature 7 and feature 4 are determined. Based on similarity 3 and similarity 4, the similarity ② between image A and image C is determined. The feature similarity between the digital artifact data to be detected and the reference digital artifact data is obtained by weighted summation of similarity ① and similarity ②.

[0118] For example, such as Figure 4c, the reference digital collectible data associated with the transition reference block is image C and image D, the recorded reference features of the transition reference block include feature 1 and feature 2 corresponding to image C, feature 3 and feature 4 corresponding to image D, the recorded feature extraction algorithm includes algorithm 1, algorithm 2 and algorithm 3, feature 1 and feature 3 correspond to algorithm 1, feature 2 corresponds to algorithm 2, and feature 4 corresponds to algorithm 3, and feature 5 is obtained by calling algorithm 1 to perform feature extraction on image A, feature 6 is obtained by calling algorithm 2 to perform feature extraction on image A, feature 7 is obtained by calling algorithm 3 to perform feature extraction on image A, feature 8 is obtained by calling algorithm 1 to perform feature extraction on image B, feature 9 is obtained by calling algorithm 2 to perform feature extraction on image B, and feature 10 is obtained by calling algorithm 3 to perform feature extraction on image B; therefore, the similarity 1 of feature 5 and feature 1 is determined, the similarity 2 of feature 6 and feature 2 is determined, the similarity ① of image A and image C is determined according to the similarity 1 and the similarity 2, the similarity 3 of feature 5 and feature 3 is determined, the similarity 4 of feature 7 and feature 4 is determined, and the similarity ② of image A and image D is determined according to the similarity 3 and the similarity 4, the similarity ③ of image A and the reference digital collectible data is obtained by weighted summation of the similarity ① and the similarity ②, the similarity 5 of feature 8 and feature 1 is determined, the similarity 6 of feature 9 and feature 2 is determined, the similarity ④ of image B and image C is determined according to the similarity 5 and the similarity 6, the similarity 7 of feature 8 and feature 3 is determined, the similarity 8 of feature 10 and feature 4 is determined, and the similarity ⑤ of image B and image D is determined according to the similarity 7 and the similarity 8, the similarity ⑥ of image B and the reference digital collectible data is obtained by weighted summation of the similarity ④ and the similarity ⑤, and the feature similarity of the to-be-detected digital collectible data and the reference digital collectible data is obtained by weighted summation of the similarity ③ and the similarity ⑥.

[0119] Optionally, in one possible implementation, due to the large amount of data on the blockchain, the data workload of finding the relevant reference block is large and time-consuming, therefore, before determining the target reference block from the multiple reference blocks on the blockchain based on the verification data features, the metadata text recorded by each reference block (or the text containing the reference features and feature extraction algorithm part in the metadata text; or it can also include the recorded collection attribute information) and the block height of each reference block in the blockchain can be associated and stored in a target database, which can be located in the data recognition device or a third-party storage device, and the feature information includes the reference features and feature extraction algorithm of the reference digital collection data associated with each reference block; and in response to the data device request, the target reference features matching the verification features are found in the target database, if the target reference features are queried, the collection attribute information corresponding to the target reference features is obtained, which can include the collection attribute information corresponding to the target reference features recorded in the target database, or the collection attribute information recorded in the corresponding target reference block is obtained according to the block height associated with the target reference features on the blockchain; if the target reference features are not queried, the step of determining the target reference block from the multiple reference blocks on the blockchain based on the verification data features is triggered; the data on the chain can be associated with the block height as the dimension, and the relationship between the reference features and the data on the chain can be associated.

[0120] In some embodiments, the electronic device can determine the feature similarity between the reference features recorded by each reference block stored in the target database and the verification features, and take the reference feature corresponding to the maximum similarity among the obtained multiple similarities as the target reference feature, i.e., indicating that the target reference feature is obtained from the target database; or can be, if the multiple feature similarities exist a similarity greater than a preset threshold, the reference feature corresponding to the maximum similarity is taken as the target reference feature, i.e., indicating that the target reference feature is obtained from the target database; or can be if the multiple feature similarities are all less than the preset threshold, it indicates that the target reference feature is not obtained in the target database; or can be, determine whether there is a newly added and unassociated stored reference block on the blockchain, if not, it can be executed according to the above situation, if there is, it can indicate that the target reference feature is not obtained in the target database, and the target reference feature can be further queried based on the multiple reference blocks of the blockchain; wherein, it can be specifically executed according to the above related process description to determine the target reference block from the multiple reference blocks of the blockchain based on the verification data features; or can be, determine the feature similarity between the reference digital collectible data recorded by the unassociated stored reference block on the blockchain and the to-be-detected digital collectible data, and determine the target reference block from the multiple reference blocks of the blockchain based on the feature similarity determined by the unassociated stored reference block and the feature similarity obtained based on the previously determined associated stored reference block, to achieve the step of determining the target reference block from the multiple reference blocks of the blockchain based on the verification data features.

[0121] In one possible implementation, if the feature similarity between the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block is less than the similarity threshold, it indicates that there is no data similar to the to-be-detected digital collectible data in the reference digital collectible data associated with each reference block, i.e., it can be indicated that the data that may be the to-be-detected digital collectible data is not identified in the blockchain, therefore, the data on-chain prompt information can be generated and sent to the electronic device to instruct the electronic device to perform on-chain processing on the to-be-detected digital collectible data. If the data identification device receives the data on-chain request generated by the electronic device according to the data on-chain prompt information, the block data of the to-be-detected digital collectible data is generated, and the blockchain on-chain processing is performed on the block data. The data on-chain request can be represented as a data collectible request.

[0122] In some embodiments, the manner of generating the block data of the digital collectible data to be detected can be the same as that of generating the block data of the target digital collectible, specifically, obtaining to-be-chained data associated with the digital collectible data to be detected, obtaining a feature extraction algorithm of the to-be-chained data, performing feature extraction on the to-be-chained data according to the feature extraction algorithm of the to-be-chained data, obtaining reference features of the to-be-chained data, obtaining metadata text of the to-be-chained data according to the reference features of the to-be-chained data and the feature extraction algorithm of the to-be-chained data, obtaining collectible attribute information of the to-be-chained data and a collectible identifier of the to-be-chained data, and determining the block data of the digital collectible data to be detected according to the metadata text of the to-be-chained data, the collectible attribute information of the to-be-chained data, and the collectible identifier of the to-be-chained data. The descriptions of the collectible attribute information and the collectible identifier of the to-be-chained data can refer to the descriptions of the collectible attribute information and the collectible identifier of the target digital collectible described above. Part or all of the data can be obtained and sent by the electronic device or obtained by the data recognition device through relevant processing.

[0123] The to-be-chained data can be the digital collectible data to be detected or complete digital collectible data associated with the digital collectible data to be detected, for example, the digital collectible data to be detected is a front image of a target object, and the to-be-chained data is the front image and a side image of the target object, and the like. The block data can further include other data related to the chain of the blockchain, which can be determined according to the actual chain scenario. The block data is subjected to the chain of the blockchain to obtain a reference block recording the block data in the blockchain. The reference block is associated with the to-be-chained data, and the to-be-chained data can be regarded as reference digital collectible data associated with the reference block.

[0124] In addition, the feature extraction algorithm of the to-be-chained data can be determined by determining the data type of the to-be-chained data and selecting a feature extraction algorithm for the to-be-chained data according to the determined data type. Different data types use different feature extraction algorithms. The specific manner of selecting the feature extraction algorithm according to the data type of the to-be-chained data can be the same as the manner of determining the feature extraction algorithm of the target digital collectible described in the above embodiments.

[0125] In a possible implementation, after obtaining the target reference block, the matched reference digital collection data can be further verified by the collection description information recorded in the target reference block, that is, the matched reference digital collection data and the to-be-detected digital collection data can be compared based on the collection description information, and if the description information does not meet the condition (for example, it can mean that more than a preset proportion does not meet the condition, for example, if there are more than 3 mismatches in a total of 10 description information, it means that they are not similar), it means that the matched reference digital collection data and the to-be-detected digital collection data are still not similar, and data chaining prompt information can be generated. For example, the description information of the matched reference digital collection data is that the target object is a tiger, the tiger is strong, the color of the tiger is red, and the like; and the description information obtained by detecting the to-be-detected digital collection data is that the target object is a cat, the cat is small, the color of the cat is white, and the like; at this time, the description information of the reference digital collection data and the description information of the to-be-detected digital collection data do not meet the condition.

[0126] In addition, the data chaining prompt information can be generated when both the description information does not meet the condition and the similarity is less than the similarity threshold; or the data chaining prompt information can be generated when either the description information does not meet the condition or the similarity is less than the similarity threshold.

[0127] S406: Obtain the collection attribute information recorded in the target reference block, and return the collection attribute information to the electronic device that initiates the data recognition request.

[0128] In some embodiments, the reference digital collection data associated with the reference block (denoted as target reference digital collection data) can be directly chained in the reference block, or can be stored in a third-party storage area (for example, a database or the like) in an external chain manner to reduce the storage overhead on the blockchain, for example, it can be stored by IPFS, and the storage information (that is, the data pulling address) corresponding to the target reference digital collection data is chained in the metadata text recorded in the reference block. The data recognition device can obtain the target reference digital collection data from the target reference block when obtaining the collection attribute information, and return the collection attribute information and the target reference digital collection data to the electronic device for display; or the data recognition device can obtain the target reference digital collection data according to the storage information recorded in the collection attribute information, and return the collection attribute information and the target reference digital collection data to the electronic device; or the data recognition device obtains the storage information from the metadata text, and returns the storage information and the collection attribute information to the electronic device, and the electronic device obtains the target reference digital collection data according to the storage information and displays it.

[0129] Based on the above description, the technical solution provided in this application can achieve the following when processing reference digital collectible data on the blockchain: the reference features of the reference digital collectible data are acquired and uploaded to the blockchain simultaneously. Subsequently, the identification function provided by the blockchain explorer can be used to obtain the digital collectible data to be detected, such as an image to be detected. The blockchain explorer then performs blockchain data identification based on the verification features of the image to be detected, determining whether similar images already uploaded to the blockchain exist, and obtaining the data recorded in the corresponding blocks of similar images already uploaded to the blockchain. Furthermore, since the blockchain explorer has a weak dependence on on-chain data, it can be associated with multiple underlying blockchains, enabling data search and identification across multiple blockchains. During the search, the name, unique code, block height, issuer, etc., of the uploaded data can be searched.

[0130] In some embodiments, when a data recognition device uploads data to the blockchain, it may do so according to the relevant defined format of the blockchain. Specifically, it may determine the on-chain data corresponding to the block data of the reference digital collectible data according to a specified defined format, and generate a reference block on the blockchain indicating the on-chain data. Subsequently, when an electronic device displays the recognition result, it can do so based on this on-chain data. This on-chain data includes field data corresponding to various fields, and the feature information of the reference digital collectible data can be added as field values ​​in the metadata text of the on-chain data.

[0131] For example, such as Figure 5 As shown, Figure 5 This application provides a schematic diagram of a scenario for uploading reference digital collectible data to the blockchain. The reference digital collectible data is denoted as image A. The pHash and SIFT algorithms are used to extract features from image A, resulting in reference feature 1 (value1) and reference feature 2 (value2). The on-chain data of image A is obtained according to a specified format, added to the associated reference block, and issued by the blockchain. This on-chain data indicates the collectible identifier, collectible attribute information, and metadata text. The collectible attribute information may include the name, issuer, and owner of image A. The metadata text may include reference features and feature extraction algorithms in the meta field. The metadata text indicates the mapping relationship between the pHash algorithm and value1, and the mapping relationship between the SIFT algorithm and value2.

[0132] For example, such as Figure 6 As shown, Figure 6 This application provides a schematic diagram of a scenario for identifying digital artifact data to be detected; wherein, the digital artifact data to be detected uploaded through an image recognition tool is image B, and image B is... Figure 5The reduced image (or slightly deformed / modified similar image) of the image A is compared by the data recognition device through the blockchain browser according to the verification features of the image B and the reference features recorded in each reference block record to determine the target reference block associated with the image A from the blockchain, and the data recorded in the target reference block record is obtained to obtain the recognition result, and the recognition result and the image A are displayed by the electronic device; in addition, when the features are compared, the verification features of the image B and the reference features of the image A can be the same or approximately the same, when the image B is a reduced image of the image A, the verification features and the reference features can be the same, when the image B is an adjusted image B, the verification features and the reference features can be approximately the same, so when the data with slight adjustment is identified, the original data can be accurately identified from the blockchain.

[0133] In the embodiments of the present application, a data recognition request can be obtained, a hash algorithm is called to determine the verification identification features of the to-be-detected digital collection data, if the target reference block is determined from the plurality of reference blocks of the blockchain based on the verification identification features, the collection attribute information is obtained from the target reference block, and returned to the electronic device initiating the data recognition request, if the target reference block is not determined based on the verification identification features, the feature extraction rule is determined, the feature extraction is performed on the to-be-detected digital collection data, the verification features corresponding to the to-be-detected digital collection data are obtained, the target reference block is determined from the plurality of reference blocks of the blockchain based on the verification features, the collection attribute information recorded in the target reference block is obtained, and the collection attribute information is returned to the electronic device initiating the data recognition request. Through the above method, the same reference digital collection data as the to-be-detected digital collection data can be quickly determined by the obtained verification identification features, and the identification flexibility is improved, when the verification identification features fail to determine, the most matched target reference block is determined from the blockchain by using the verification features, the target reference features recorded in the target reference block are most similar to the verification features, the reference digital collection data most possibly related to the to-be-detected digital collection data can be accurately identified on the blockchain, the data recognition efficiency for the blockchain can be improved, and the automatic and intelligent search demand of the user for related data such as copyright is met.

[0134] Please refer to Figure 7 , Figure 7 The flowchart of the data acquisition method provided by the embodiments of the present application can be executed by the electronic device mentioned above, for example, a smart phone, a tablet computer, a personal computer PC, a smart wearable device, and some servers, etc. As shown in Figure 7 The flowchart of the data acquisition method provided by the embodiments of the present application can include the following steps:

[0135] S701: receiving the recognition result of the data recognition of the to-be-detected digital collection data.

[0136] In some embodiments, after the data identification device performs data identification on the to-be-detected digital collectible data on the blockchain, the identification result is returned, and the electronic device can determine the to-be-displayed data according to the identification result when receiving the identification result, and display the to-be-displayed data. The to-be-displayed data can include to-be-displayed collectible attribute information and reference digital collectible data matched with the to-be-detected digital collectible data. The reference digital collectible data can be sent together with the collectible attribute information by the data identification device, or the data identification device can obtain a data pulling address from the metadata text and send the collectible attribute information to the electronic device according to the data pulling address.

[0137] S702: Display the object data in the object display area of the display interface and display the identification result in the attribute display area of the display interface.

[0138] In some embodiments, the electronic device can display through a display interface, which can include an object display area and an attribute display area. The object display area is used to display object data, which can include to-be-detected digital collectible data and / or matched reference digital collectible data. The attribute display area is used to display the identification result, which can include collectible attribute information obtained for the to-be-detected digital collectible data. The display interface can be an interface in a recognition client for the blockchain, which can be an application client, a browser client, or a mini-program client, etc.

[0139] In some embodiments, the electronic device may, in response to an identification request operation, acquire first digital collectible data uploaded by the user, generate a data identification request based on the first digital collectible data, and send it to a data identification device. The data identification device then performs blockchain data identification based on the first digital collectible data to obtain an identification result. The first digital collectible data can be the aforementioned digital collectible data to be detected. After the electronic device displays the relevant information on the display interface, if the user determines that the identification is inaccurate, a re-identification can be performed. That is, the electronic device may, in response to a re-identification operation received through the display interface, acquire second digital collectible data and send a data identification request to the data identification device based on the second digital collectible data to receive the identification result based on the second digital collectible data again. The first and second digital collectible data can be the same or different, and are loaded and acquired during the detection data entry operation. In other words, during re-identification, the user can choose to still use the uploaded first digital collectible data for data identification, or re-upload the second digital collectible data (e.g., image data that is clearer than the first digital collectible data) for data identification. In addition, the first digital collectible data can be data that has been adjusted from reference digital collectible data that has been put on the blockchain, or it can be data obtained by taking pictures or other means. The first digital collectible data can be obtained by scanning the target object with a scanning and recognition tool provided by an electronic device, or by the user taking pictures, recording videos, copying relevant links or uploading files.

[0140] In some embodiments, when the electronic device receives a data uploading prompt from the data recognition device during a related display, it can respond to the user's data uploading operation to obtain the data to be uploaded to the blockchain, generate a data uploading request based on the data to be uploaded to the blockchain, and send it to the data recognition device for blockchain uploading processing. Alternatively, it can respond to a re-recognition operation and perform blockchain data recognition again. The re-recognition operation can be a user trigger operation on a relevant control or a voice instruction operation, etc.

[0141] For example, such as Figure 8 As shown, Figure 8This is a schematic diagram of a display interface provided in an embodiment of this application. The display interface may include an object display area and an attribute display area. The object display area can be used to display the digital collectible data to be detected and the matching reference digital collectible data, and the attribute display area can be used to display collectible attribute information, such as unique code, issuer, etc. In addition, when the display interface is displayed, it will also output a "re-identify" control. The electronic device can obtain the digital collectible data for re-identification and generate a data identification request by responding to the trigger behavior of the control. If the display interface displays a data uploading prompt, it will output a "data uploading" control. The electronic device can obtain the data to be uploaded to the blockchain and generate a data uploading request by responding to the trigger behavior of the control.

[0142] In this embodiment, the system can receive the identification results of the digital collectible data to be detected, display the object data in the object display area of ​​the display interface, and display the identification results in the attribute display area of ​​the display interface. Through this method, rapid and accurate identification of data in the blockchain can be achieved, and the system can display copyright-related attribute data such as the author of the digital collectible data for intuitive viewing.

[0143] The methods of the embodiments of this application have been described in detail above. In order to facilitate better implementation of the above solutions of the embodiments of this application, the apparatus of the embodiments of this application is provided below.

[0144] Please see Figure 9 , Figure 9 This application provides a schematic diagram of the structure of a data processing device; this data processing device can be used as a computer program (including program code) running in a data recognition device, for example, the data processing device can be an application program (such as a program capable of data processing) in the data recognition device. It should be noted that... Figure 9 The data processing apparatus shown is used to execute this application. Figure 2 , Figure 3a and Figure 3b Some or all of the steps in the method of the illustrated embodiment. The data processing apparatus 900 may include: an acquisition module 901 and a processing module 902. Wherein:

[0145] The acquisition module 901 is used to obtain target digital collectible data from the digital collectible request and to obtain the collectible attribute information of the target digital collectible data; the digital collectible request is generated based on the digital collectible block protocol;

[0146] The processing module 902 is used to determine the feature extraction algorithm for the target digital collection data, and to extract features from the target digital collection data according to the determined feature extraction algorithm to obtain the reference features of the target digital collection data.

[0147] The processing module 902 is further configured to record the reference features into a metadata field to obtain the metadata text of the target digital collectible data; the metadata field is a data storage field defined in a digital collectible block protocol;

[0148] The processing module 902 is further configured to generate block data and perform a chain processing on the block data; wherein the collectible attribute information and the metadata text are recorded in the block data.

[0149] In some embodiments, the processing module 902 is further configured to:

[0150] obtain the chain information of the target digital collectible data;

[0151] add the chain information into the metadata field to obtain the metadata text of the target digital collectible data;

[0152] The chain information includes any one or more of the collectible identifier, the collectible name, the collectible description information, and the data pulling address of the target digital collectible data.

[0153] In some embodiments, the processing module 902 is further configured to, after performing the chain processing on the block data:

[0154] obtain a data identification request; the data identification request carries the digital collectible data to be detected;

[0155] extract features from the digital collectible data to be detected according to the determined feature extraction rule to obtain verification features corresponding to the digital collectible data to be detected;

[0156] determine a target reference block from a plurality of reference blocks of the block chain based on the verification features; wherein the target reference block includes target reference features recorded in the metadata text, and the target reference features match the verification features;

[0157] obtain the collectible attribute information recorded in the target reference block, and return the collectible attribute information to the electronic device initiating the data identification request.

[0158] In some embodiments, the reference block of the block chain records the block data of the reference digital collectible data associated with each reference block, and the metadata text recorded in the block data includes the feature extraction algorithm of the reference digital collectible data associated with each reference block.

[0159] The processing module 902 is configured to, when extracting features from the digital collectible data to be detected according to the determined feature extraction rule to obtain verification features corresponding to the digital collectible data to be detected:

[0160] According to the feature extraction algorithm recorded by each reference block, the feature of the to-be-detected digital collectible data is extracted to obtain the verification feature of the to-be-detected digital collectible data for each reference block.

[0161] In some embodiments, the reference features recorded in the metadata text recorded by the block data and the feature extraction algorithm are in one-to-one mapping relationship.

[0162] The processing module 902 is specifically configured to:

[0163] According to the verification feature of the to-be-detected digital collectible data for each reference block and the reference feature recorded by each reference block, the feature similarity of the reference digital collectible data associated with each reference block by the to-be-detected digital collectible data is determined.

[0164] According to the feature similarity, the target reference feature is determined from the reference features recorded by each reference block.

[0165] The reference block recording the target reference feature is determined as the target reference block.

[0166] In some embodiments, the metadata text recorded by the transition reference block in each reference block of the block chain includes: a first feature extraction algorithm and a first reference feature, the first reference feature is obtained by performing feature extraction on the reference digital collectible data associated with the transition reference block based on the first feature extraction algorithm, a second feature extraction algorithm and a second reference feature, the second reference feature is obtained by performing feature extraction on the reference multi-media data associated with the transition reference block based on the second feature extraction algorithm.

[0167] The processing module 902 is specifically configured to:

[0168] According to the first feature extraction algorithm, the feature of the to-be-detected digital collectible data is extracted to obtain the first verification feature;

[0169] According to the second feature extraction algorithm, the feature of the to-be-detected digital collectible data is extracted to obtain the second verification feature;

[0170] According to the first verification feature and the second verification feature, the verification feature of the to-be-detected digital collectible data for the transition reference block is determined.

[0171] In some embodiments, the first verification feature and the second verification feature are both used as the verification feature of the to-be-detected digital collectible data for the transition reference block.

[0172] The processing module 902 is specifically configured to:

[0173] determine a first initial similarity according to the first reference feature and the first verification feature, and determine a second initial similarity according to the second reference feature and the second verification feature;

[0174] perform weighted summation on the first initial similarity and the second initial similarity to obtain the feature similarity between the to-be-detected digital collectible data and the reference digital collectible data associated with the transition reference block.

[0175] In some embodiments, the processing module 902 is further configured to:

[0176] generate a data chaining prompt information if the feature similarity between the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block is less than the similarity threshold;

[0177] send the data chaining prompt information to the electronic device;

[0178] generate block data of the to-be-detected digital collectible data and perform blockchain chaining processing on the block data if a data chaining request generated by the electronic device according to the data chaining prompt information is received.

[0179] In some embodiments, the processing module 902 is specifically configured to:

[0180] obtain to-be-chained data associated with the to-be-detected digital collectible data, and obtain a feature extraction algorithm of the to-be-chained data;

[0181] extract features of the to-be-chained data according to the feature extraction algorithm of the to-be-chained data to obtain reference features of the to-be-chained data;

[0182] obtain metadata text of the to-be-chained data according to the reference features of the to-be-chained data and the feature extraction algorithm of the to-be-chained data;

[0183] obtain collectible attribute information of the to-be-chained data and a collectible identifier of the to-be-chained data;

[0184] determine the block data of the to-be-detected digital collectible data according to the metadata text of the to-be-chained data, the collectible attribute information of the to-be-chained data, and the collectible identifier of the to-be-chained data.

[0185] In some embodiments, the processing module 902 is specifically configured to:

[0186] determining a data type of the data to be uploaded;

[0187] selecting a feature extraction algorithm for the data to be uploaded according to the determined data type;

[0188] wherein the feature extraction algorithms used by different data types are different.

[0189] In some embodiments, the processing module 902 is further configured to, before determining the target reference block from the plurality of reference blocks of the blockchain based on the verification data feature:

[0190] respectively store the metadata text recorded by each reference block and the block height of each reference block in the blockchain in the target database;

[0191] In response to the data identification request, searching for the target reference feature matching the verification feature in the target database;

[0192] If the target reference feature is found, obtaining the collection attribute information corresponding to the target reference feature; the collection attribute information includes: the collection attribute information corresponding to the target reference feature recorded in the target database, or the collection attribute information recorded in the corresponding target reference block according to the block height associated with the target reference feature in the blockchain;

[0193] If the target reference feature is not found, triggering the determination of the target reference block from the plurality of reference blocks of the blockchain based on the verification data feature.

[0194] In some embodiments, the collection identifier recorded by each reference block of the blockchain is a reference identifier feature used to uniquely represent the reference digital collection data associated with each reference block, and the reference identifier feature is obtained based on a hash algorithm;

[0195] Before the processing module 902 is configured to extract features from the digital collection data to be detected according to the determined feature extraction rule, it is further configured to:

[0196] determine the verification identifier feature of the digital collection data to be detected by calling a hash algorithm;

[0197] If there is a target reference identifier feature identical to the verification identifier feature in the reference identifier features recorded by each reference block, the reference block recording the target reference identifier feature is taken as the target reference block;

[0198] If the reference identifier features recorded by each reference block are all different from the verification identifier feature, the feature extraction from the digital collection data to be detected according to the determined feature extraction rule is performed.

[0199] According to an embodiment of the present application, Figure 9Each unit in the data processing apparatus shown can be combined into one or several other units respectively or all, or some of them can be further split into a plurality of units with smaller functions to constitute, which can achieve the same operation without affecting the implementation of the technical effects of the embodiments of the present application. The above units are divided based on logical functions, and in actual application, the functions of one unit can also be implemented by multiple units, or the functions of multiple units can be implemented by one unit.

[0200] In other embodiments of the present application, the data processing apparatus can also include other units, and in actual application, these functions can also be assisted by other units, and can be implemented by multiple units. According to another embodiment of the present application, the data processing apparatus as shown in Figure 2 、 Figure 3a and Figure 3b indicated can be constructed, and the data processing method of the embodiments of the present application can be implemented by running the computer program (including program codes) capable of executing the steps involved in the corresponding method as shown in Figure 9 indicated on a general computing device such as a computer including processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), read-only memory (ROM), etc. The computer program can be recorded on, for example, a computer readable recording medium, and loaded into the above data recognition device through the computer readable recording medium, and run therein.

[0201] In the embodiments of the present application, the acquisition module acquires target digital collectible data from a digital collectible request, and acquires collectible attribute information of the target digital collectible data; the processing module determines a feature extraction algorithm for the target digital collectible data, and performs feature extraction on the target digital collectible data according to the determined feature extraction algorithm to obtain reference features of the target digital collectible data; the processing module records the reference features into a metadata field to obtain metadata text of the target digital collectible data; and the processing module generates block data and performs on-chain processing on the block data. Through the above apparatus, the reference features can be added to the block data of the target digital collectible data, and the richness of the block data on the block chain is improved, so that matching in the block chain through the reference features can be realized, and the digital collectible data stored on the block chain can be searched quickly and accurately, the data recognition efficiency for the block chain is improved, and the automatic and intelligent search demand of users for related data such as copyright is also met.

[0202] Please refer to Figure 10 , Figure 10A structural schematic diagram of a data acquisition device provided in the present application; the data acquisition device can be used in a computer program (including program code) running in an electronic device, for example, the data acquisition device can be an application program (such as a program that can acquire data) in the electronic device. It should be noted that, Figure 10 The data acquisition device shown is used to execute the method of the embodiment of the present application Figure 7 Some or all steps in the method of the embodiment shown. The data acquisition device 1000 can include: a receiving module 1001, a display module 1002. Wherein:

[0203] The receiving module 1001 is configured to receive an identification result of data identification on the to-be-detected digital collectible data;

[0204] The display module 1002 is configured to display object data in an object display area of a display interface, the object data including the to-be-detected digital collectible data and / or reference digital collectible data matched with the to-be-detected digital collectible data;

[0205] The display module 1002 is further configured to display the identification result in a property display area of the display interface, the identification result including collectible property information obtained for the to-be-detected digital collectible data.

[0206] In some embodiments, the display module 1002 is further configured to:

[0207] In response to an identification request operation, obtain first digital collectible data and send a data identification request according to the first digital collectible data;

[0208] In response to a re-identification operation received through the display interface, obtain second digital collectible data and send a data identification request according to the second digital collectible data;

[0209] The first digital collectible data and the second digital collectible data are the same or different, and the first digital collectible data and the second digital collectible data are loaded and obtained when the data detection entry operation is performed.

[0210] According to one embodiment of the present application, Figure 10 The various units in the data acquisition device shown can be combined into one or several other units respectively or all, or some of the units can be further split into a plurality of units with smaller functions to constitute, which can realize the same operation without affecting the realization of the technical effects of the embodiments of the present application. The above units are divided based on logical functions, and in actual application, the functions of one unit can also be realized by multiple units, or the functions of multiple units are realized by one unit.

[0211] In other embodiments of the present application, the data acquisition apparatus can also include other units, and in actual applications, these functions can also be assisted by other units, and can be realized by cooperation of multiple units. According to another embodiment of the present application, the data acquisition apparatus as shown in Figure 7 the data acquisition apparatus as shown in Figure 10 and the data acquisition method of the embodiments of the present application can be constructed by running a computer program (including program codes) capable of executing the steps involved in the corresponding method as shown in

[0212] In the embodiments of the present application, the receiving module receives an identification result of data identification on the to-be-detected digital collectible data; the display module displays object data in an object display area of the display interface, the object data including the to-be-detected digital collectible data and / or reference digital collectible data matched with the to-be-detected digital collectible data; and the display module displays the identification result in an attribute display area of the display interface, the identification result including collectible attribute information obtained for the to-be-detected digital collectible data. Through the above apparatus, the identification of the blockchain data can be realized, and the corresponding identification result can be displayed for intuitive viewing by the identifier.

[0213] The functional modules in each of the embodiments of the present application can be integrated in one module, or each module can exist physically, or two or more modules can be integrated in one module. The integrated module can be realized in the form of hardware, or in the form of a software functional module, and the present application is not limited.

[0214] Please refer to Figure 11 , Figure 11 for a structural schematic diagram of a data identification device provided by the embodiments of the present application. As shown in Figure 11 , the data identification device 1100 includes at least one processor 1101, a memory 1102. In one possible implementation, the data identification device can also include a network interface. Among them, the processor 1101, the memory 1102 and the network interface can interact with each other, the network interface is controlled by the processor 1101 to receive and send messages, the memory 1102 is used to store computer programs, the computer programs include program instructions, and the processor 1101 is used to execute the program instructions stored in the memory 1102. Among them, the processor 1101 is configured to call the program instructions to execute the above method.

[0215] The memory 1102 can include a volatile memory, such as a random-access memory (RAM), and / or a non-volatile memory, such as a flash memory, a solid-state drive (SSD), etc. The memory 1102 can also include a combination of the above-mentioned types of memories.

[0216] The processor 1101 can be a central processing unit (CPU). In an embodiment, the processor 1101 can also be a graphics processing unit (GPU). The processor 1101 can also be a combination of a CPU and a GPU.

[0217] In some embodiments, the memory 1102 is configured to store program instructions, and the processor 1101 is configured to invoke the program instructions to perform the following steps:

[0218] Obtain target digital collectible data from a digital collectible request, and obtain collectible attribute information of the target digital collectible data; the digital collectible request is generated based on a digital collectible block protocol;

[0219] Determine a feature extraction algorithm for the target digital collectible data, and perform feature extraction on the target digital collectible data according to the determined feature extraction algorithm to obtain reference features of the target digital collectible data;

[0220] Record the reference features in a metadata field of the target digital collectible data to obtain metadata text of the target digital collectible data; the metadata field is a data storage field defined in the digital collectible block protocol;

[0221] Generate block data, and perform a chain processing on the block data; wherein the collectible attribute information and the metadata text are recorded in the block data.

[0222] In some embodiments, the processor 1101 is further configured to:

[0223] Obtain the chain information of the target digital collectible data;

[0224] Add the chain information to the metadata field to obtain the metadata text of the target digital collectible data;

[0225] The chain information includes any one or more of a collectible identifier, a collectible name, collectible description information of the target digital collectible data, and a data pulling address of the target digital collectible data.

[0226] In some embodiments, the processor 1101 is further configured to, after performing the on-chain processing on the block data:

[0227] obtain a data identification request, the data identification request carrying to-be-detected digital collectible data;

[0228] perform feature extraction on the to-be-detected digital collectible data according to the determined feature extraction rule to obtain verification features corresponding to the to-be-detected digital collectible data;

[0229] determine a target reference block from the plurality of reference blocks of the blockchain based on the verification features; wherein the target reference block includes target reference features recorded in metadata text that match the verification features;

[0230] obtain collectible attribute information recorded in the target reference block, and return the collectible attribute information to an electronic device that initiates the data identification request.

[0231] In some embodiments, the reference block of the blockchain records block data of reference digital collectible data associated with each reference block, and the metadata text recorded in the block data includes: a feature extraction algorithm of the reference digital collectible data associated with each reference block.

[0232] When the processor 1101 is configured to perform feature extraction on the to-be-detected digital collectible data according to the determined feature extraction rule to obtain verification features corresponding to the to-be-detected digital collectible data, the processor 1101 is specifically configured to:

[0233] perform feature extraction on the to-be-detected digital collectible data according to the feature extraction algorithm recorded in each reference block to obtain verification features of the to-be-detected digital collectible data for each reference block.

[0234] In some embodiments, the reference features and the feature extraction algorithm recorded in the metadata text of the block data are in one-to-one mapping relationship.

[0235] When the processor 1101 is configured to determine a target reference block from the plurality of reference blocks of the blockchain based on the verification features, the processor 1101 is specifically configured to:

[0236] determine feature similarities between the to-be-detected digital collectible data and reference digital collectible data associated with each reference block, respectively, according to the verification features of the to-be-detected digital collectible data for each reference block and the reference features recorded in each reference block;

[0237] determine the target reference features from the reference features recorded in each reference block according to the feature similarities;

[0238] determine the reference block recording the target reference features as the target reference block.

[0239] In some embodiments, the metadata text recorded in the transition reference block of each reference block of the blockchain includes: a first feature extraction algorithm and a first reference feature, the first reference feature being obtained by performing feature extraction on reference digital collectible data associated with the transition reference block based on the first feature extraction algorithm; and a second feature extraction algorithm and a second reference feature, the second reference feature being obtained by performing feature extraction on reference multimedia data associated with the transition reference block based on the second feature extraction algorithm.

[0240] The processor 1101 is specifically configured to:

[0241] perform feature extraction on the to-be-detected digital collectible data according to the first feature extraction algorithm to obtain first verification features;

[0242] perform feature extraction on the to-be-detected digital collectible data according to the second feature extraction algorithm to obtain second verification features;

[0243] determine the verification features of the to-be-detected digital collectible data for the transition reference block according to the first verification features and the second verification features.

[0244] In some embodiments, the first verification features and the second verification features are both used as the verification features of the to-be-detected digital collectible data for the transition reference block.

[0245] The processor 1101 is specifically configured to:

[0246] determine a first initial similarity according to the first reference features and the first verification features, and determine a second initial similarity according to the second reference features and the second verification features;

[0247] perform weighted summation on the first initial similarity and the second initial similarity to obtain the feature similarity between the to-be-detected digital collectible data and the reference digital collectible data associated with the transition reference block.

[0248] In some embodiments, the processor 1101 is further configured to:

[0249] if the feature similarities between the to-be-detected digital collectible data and the reference digital collectible data associated with each reference block are all less than a similarity threshold, generate data chaining prompt information;

[0250] send the data chaining prompt information to the electronic device;

[0251] If the data on-chain request generated by the electronic device according to the data on-chain prompt information is received, block data of the digital collectible data to be detected is generated, and the block data is processed on the block chain.

[0252] In some embodiments, the processor 1101, when generating the block data of the digital collectible data to be detected, specifically for:

[0253] Obtain the to-be-chained data associated with the digital collectible data to be detected, and obtain the feature extraction algorithm of the to-be-chained data;

[0254] According to the feature extraction algorithm of the to-be-chained data, the reference features of the to-be-chained data are extracted;

[0255] According to the reference features of the to-be-chained data and the feature extraction algorithm of the to-be-chained data, the metadata text of the to-be-chained data is obtained;

[0256] Obtain the collectible attribute information of the to-be-chained data and the collectible identifier of the to-be-chained data;

[0257] According to the metadata text of the to-be-chained data, the collectible attribute information of the to-be-chained data, and the collectible identifier of the to-be-chained data, the block data of the digital collectible data to be detected is determined.

[0258] In some embodiments, the processor 1101, when obtaining the feature extraction algorithm of the to-be-chained data, specifically for:

[0259] Determine the data type of the to-be-chained data;

[0260] According to the determined data type, select a feature extraction algorithm for the to-be-chained data;

[0261] Wherein, the feature extraction algorithms used by different data types are different.

[0262] In some embodiments, before the processor 1101 determines the target reference block from the plurality of reference blocks of the block chain based on the verification data features, it is further used for:

[0263] Respectively store the metadata text recorded by each reference block and the block height of each reference block in the block chain in the target database;

[0264] In response to the data identification request, find the target reference features matching the verification features in the target database;

[0265] If the target reference feature is queried, the collection attribute information corresponding to the target reference feature is obtained; the collection attribute information includes: the collection attribute information recorded in the target database corresponding to the target reference feature, or the collection attribute information recorded in the corresponding target reference block according to the block height associated with the target reference feature in the blockchain;

[0266] If the target reference feature is not queried, triggering execution of determining the target reference block from the plurality of reference blocks of the blockchain based on the verification data feature.

[0267] In some embodiments, the collection identifier recorded in the block data recorded in each reference block of the blockchain is a reference identifier feature for uniquely representing the reference digital collection data associated with each reference block, and the reference identifier feature is obtained based on a hash algorithm;

[0268] The processor 1101 is further configured to, before performing feature extraction on the to-be-detected digital collection data according to the determined feature extraction rule:

[0269] determine the verification identifier feature of the to-be-detected digital collection data by calling a hash algorithm;

[0270] If the target reference identifier feature same as the verification identifier feature exists in the reference identifier features recorded in each reference block, the reference block recording the target reference identifier feature is taken as the target reference block;

[0271] If the reference identifier features recorded in each reference block are all different from the verification identifier feature, performing feature extraction on the to-be-detected digital collection data according to the determined feature extraction rule.

[0272] In some embodiments, the memory 1102 is configured to store program instructions, and the processor 1101 can call the program instructions to perform the following steps:

[0273] receiving an identification result of data identification on the to-be-detected digital collection data;

[0274] displaying object data in the object display area of the display interface, the object data including the to-be-detected digital collection data, and / or the reference digital collection data matched with the to-be-detected digital collection data;

[0275] displaying the identification result in the attribute display area of the display interface, the identification result including the collection attribute information obtained for the to-be-detected digital collection data.

[0276] In some embodiments, the processor 1101 is further configured to:

[0277] in response to the identification request operation, obtaining the first digital collection data, and sending a data identification request according to the first digital collection data;

[0278] In response to the re-identification operation received through the display interface, the second digital collectible data is acquired, and a data identification request is sent according to the second digital collectible data;

[0279] The first digital collectible data and the second digital collectible data are the same or different, and the first digital collectible data and the second digital collectible data are loaded and acquired when the data entry operation is detected.

[0280] In specific implementations, the data processing apparatus, the processor, the memory, and the like described above can perform the implementation manners described in the above method embodiments, and can also perform the implementation manners described in the embodiments of the present application, which will not be described here.

[0281] In the embodiments of the present application, a computer (readable) storage medium is also provided, which stores a computer program. The computer program includes program instructions, which, when executed by a processor, enable the processor to perform some or all of the steps performed by the method embodiments described above. In one possible implementation, the computer storage medium can be volatile or non-volatile. The computer readable storage medium can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required by a function, and the like; the data storage area can store data created according to the use of the blockchain node, and the like.

[0282] The embodiments of the present application also provide a computer program product, which includes computer instructions that, when executed by a processor, can implement some or all of the steps in the above method.

[0283] In this document, "multiple" refers to two or more. "And / or" describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone. The character " / " generally represents that the associated objects before and after it are in an "or" relationship.

[0284] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware. The aforementioned program can be stored in a computer storage medium, which can be a computer readable storage medium. The program, when executed, can include the processes of the above-mentioned embodiments of the method. The aforementioned storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), and the like.

[0285] The above disclosure is only some embodiments of the present application, of course, cannot be limited by this, those skilled in the art can understand that the implementation of all or part of the above processes, and the equivalent changes made by the claims of the present application, still belong to the scope covered by the present application.

Claims

1. A data processing method, characterized in that, include: Obtain target digital collectible data from the digital collectible request, and obtain the collectible attribute information of the target digital collectible data; The digital collection request is generated based on the digital collection block protocol; A feature extraction algorithm for the target digital collectible data is determined, and features are extracted from the target digital collectible data according to the determined feature extraction algorithm to obtain reference features of the target digital collectible data; The reference features and feature extraction algorithm are recorded in the metadata field to obtain the metadata text of the target digital collectible data; the metadata field is the data storage field defined in the digital collectible block protocol; The feature extraction algorithm includes multiple algorithms. The reference features recorded in the metadata text of the block data and the feature extraction algorithm have a one-to-one mapping relationship. Each feature extraction algorithm is selected and determined according to the data type of the digital collection data. Generate block data and perform on-chain processing on the block data; wherein, the collection attribute information and the metadata text are recorded in the block data; A data identification request is obtained; the data identification request carries the digital artifact data to be detected. Based on the feature extraction algorithm of each reference block record, feature extraction is performed on the digital collection data to be detected to obtain the verification features of the digital collection data to be detected for each reference block; Based on the verification features for each reference block, a target reference block is determined from multiple reference blocks in the blockchain; wherein the target reference features recorded in the metadata text of the target reference block match the verification features. Specifically, for each record obtained in the current reference block, the feature extraction algorithm performs feature extraction on the digital collectible data to be detected, obtaining verification features for the current reference block. Multiple initial similarities are obtained by calculating the similarity between the multiple verification features for the current reference block and the reference features extracted by the same feature extraction algorithm in the metadata text of the current reference block. These initial similarities are then weighted and summed to obtain the feature similarity between the digital collectible data corresponding to the current reference block and the digital collectible data to be detected, thus determining whether the current reference block is a target reference block. When there are multiple digital collectible data to be detected, and the reference block is associated with one or more reference digital collectible data, the feature similarity between each digital collectible data to be detected and the entire set of one or more reference digital collectible data is determined according to the feature extraction algorithm corresponding to each reference digital collectible data associated with the reference block, thus determining the target reference block.

2. The method as described in claim 1, characterized in that, The method further includes: Obtain the on-chain information of the target digital collection data; Add the on-chain information to the metadata field to obtain the metadata text of the target digital collection data; The on-chain information includes any one or more of the following: the collection identifier, collection name, collection description information, and the data retrieval address of the target digital collection data.

3. The method as described in claim 1, characterized in that, After determining the target reference block from multiple reference blocks of the blockchain based on the verification features, the method further includes: Obtain the collection attribute information recorded in the target reference block, and return the collection attribute information to the electronic device that initiated the data identification request.

4. The method as described in claim 3, characterized in that, The reference blocks of the blockchain record block data of the reference digital collectible data associated with each reference block. The metadata text recorded in the block data includes: the feature extraction algorithm of the reference digital collectible data associated with each reference block.

5. The method as described in claim 4, characterized in that, The step of determining the target reference block from multiple reference blocks in the blockchain based on the verification features includes: Based on the verification features of the digital collectibles data to be detected for each reference block and the reference features recorded in each reference block, the feature similarity between the digital collectibles data to be detected and the reference digital collectibles data associated with each reference block is determined. The target reference feature is determined from the reference features recorded in each reference block based on the feature similarity. The reference block that records the target reference features is determined as the target reference block.

6. The method as described in claim 5, characterized in that, The metadata text recorded in the transitional reference blocks in each reference block of the blockchain includes: a first feature extraction algorithm and a first reference feature, wherein the first reference feature is obtained by extracting features from the reference digital collection data associated with the transitional reference block based on the first feature extraction algorithm; a second feature extraction algorithm and a second reference feature, wherein the second reference feature is obtained by extracting features from the reference multimedia data associated with the transitional reference block based on the second feature extraction algorithm. The feature extraction algorithm based on each reference block record is used to extract features from the digital collectible data to be detected, obtaining the verification features of the digital collectible data to be detected for each reference block, including: The first feature extraction algorithm is used to extract features from the digital collection data to be detected, thereby obtaining the first verification feature; The second feature extraction algorithm is used to extract features from the digital collection data to be detected, and a second verification feature is obtained. Based on the first verification feature and the second verification feature, the verification features of the digital collection data to be detected for the transition reference block are determined.

7. The method as described in claim 6, characterized in that, Both the first verification feature and the second verification feature are used as verification features of the digital collection data to be detected for the transition reference block; The step of determining the feature similarity between the digital collectible data to be detected and the reference digital collectible data associated with each reference block, based on the verification features of the digital collectible data to be detected for each reference block and the reference features recorded in each reference block, includes: A first initial similarity is determined based on the first reference feature and the first verification feature, and a second initial similarity is determined based on the second reference feature and the second verification feature; The first initial similarity and the second initial similarity are weighted and summed to obtain the feature similarity between the digital collectible data to be detected and the reference digital collectible data associated with the transition reference block.

8. The method as described in claim 5, characterized in that, The method further includes: If the feature similarity between the digital collectible data to be detected and the reference digital collectible data associated with each reference block is less than the similarity threshold, then a data on-chain prompt message will be generated. The data upload notification message is sent to the electronic device; If a data upload request is received from the electronic device based on the data upload prompt information, then block data of the digital collectible data to be detected is generated, and the block data is processed for blockchain upload.

9. The method as described in claim 8, characterized in that, The block data used to generate the digital collectible data to be detected includes: Obtain the data to be uploaded to the blockchain associated with the digital collectible data to be detected, and obtain the feature extraction algorithm for the data to be uploaded to the blockchain; Based on the feature extraction algorithm of the data to be uploaded to the blockchain, feature extraction is performed on the data to be uploaded to the blockchain to obtain reference features of the data to be uploaded to the blockchain; The metadata text of the data to be uploaded to the blockchain is obtained based on the reference features of the data to be uploaded to the blockchain and the feature extraction algorithm of the data to be uploaded to the blockchain. Obtain the collection attribute information and the collection identifier of the data to be uploaded to the blockchain; The block data of the digital collection data to be tested is determined based on the metadata text of the data to be uploaded to the blockchain, the collection attribute information of the data to be uploaded to the blockchain, and the collection identifier of the data to be uploaded to the blockchain.

10. The method as described in claim 3, characterized in that, Before determining the target reference block from multiple reference blocks of the blockchain based on the verification features, the method further includes: The metadata text recorded by each reference block and the block height of each reference block in the blockchain are respectively stored in the target database; In response to the data identification request, a target reference feature matching the verification feature is searched in the target database; If the target reference feature is found, the collection attribute information corresponding to the target reference feature is obtained; the collection attribute information includes: the collection attribute information corresponding to the target reference feature recorded in the target database, or the collection attribute information recorded in the corresponding target reference block obtained in the blockchain according to the block height associated with the target reference feature; If the target reference feature is not found, the process of determining the target reference block from multiple reference blocks in the blockchain based on the verification feature is triggered.

11. The method as described in claim 3, characterized in that, The collection identifier recorded in the block data of each reference block of the blockchain is a reference identifier feature used to uniquely represent the reference digital collection data associated with each reference block. The reference identifier feature is obtained based on a hash algorithm. Before performing feature extraction on the digital collection data to be detected according to the determined feature extraction rules, the method further includes: A hash algorithm is invoked to determine the verification identifier features of the digital collectible data to be detected; If any of the reference identifier features recorded in each reference block contains a target reference identifier feature that is identical to the verification identifier feature, then the reference block that records the target reference identifier feature is taken as the target reference block. If the reference identifier features recorded in each reference block are not the same as the verification identifier features, then feature extraction is performed on the digital collection data to be detected according to the determined feature extraction rules.

12. A data recognition device, characterized in that, The device includes a processor and a memory, wherein the memory is used to store a computer program, the computer program including program instructions, and the processor is configured to invoke the program instructions to perform the method as described in any one of claims 1-11.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-11.

14. A computer program product, characterized in that, The computer program product includes computer instructions that, when executed by a processor, implement the method as described in any one of claims 1-11.

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