Painting and calligraphy work copyright intelligent tracing system

Abstract

The invention relates to the technical field of work copyright tracing, in particular to a calligraphy and painting work copyright intelligent tracing system which comprises a tracing system and is used for tracing the calligraphy and painting work copyright. The database server is used for receiving and storing identity authentication information, work metadata and work digital images submitted by a copyright person, and generating a work feature fingerprint database through a feature extraction algorithm; the work tracing comparison unit is used for analyzing the visual features of the traced work and performing similarity matching with the feature fingerprint database; through the digital evidence storage unit, the intelligent comparison unit and the collaborative feedback unit, the copyright protection of the whole process of the painting and calligraphy works is realized; the identification accuracy is ensured by adopting high-precision scanning and a neural network technology; and an administrative, judicial and market linkage mechanism is constructed, rapid handling of infringement is realized, and a new efficient and reliable calligraphy and painting copyright protection normal form is formed.

Description

Technical Field

[0001] The present invention relates to the technical field of copyright tracing of works, and in particular to an intelligent copyright tracing system for calligraphy and painting works. Background Art

[0002] Painting and calligraphy, including Chinese calligraphy, oil painting, printmaking, embossing, sand painting, electronic painting and other graphic art works, are the most common types of artworks in our lives. However, due to the lack of copyright tracing tools for painting and calligraphy, the painting and calligraphy market is flooded with infringing works, making it difficult for copyright holders to protect their rights, which is not conducive to the healthy development of the copyright market.

[0003] According to the publication number: CN215814240U, a cultural artwork anti-counterfeiting identification and filing and tracing system is disclosed. This technology discloses "a cultural artwork anti-counterfeiting identification and filing and tracing system, including an artwork classification unit, a data acquisition unit, a feature extraction unit, a feature comparison unit, a controller, a communication module, an artwork positioning unit, a cloud and a filing unit, wherein the output end of the artwork classification unit is electrically connected to the input end of the data acquisition unit, and the output end of the data acquisition unit is electrically connected to the input end of the feature extraction unit." The system has the following technical effects: "different artworks can be classified, corresponding features can be extracted for different artworks, the extracted features can be analyzed, and based on the analysis results, the artwork can be analyzed with other works of the same era, the same author, and the same material, or with similar works, thereby providing reference opinions for the authenticity identification of the artwork."

[0004] The current copyright protection of calligraphy and painting works faces three problems: first, the process of title confirmation and tracing relies heavily on manual labor, and there is a lack of standardized digital means for the preservation of works, resulting in incomplete feature records. Infringement identification requires experts to compare brushstrokes, colors and other details one by one, which is inefficient and costly. Second, there are inherent bottlenecks in technical identification. Traditional image recognition has difficulty capturing the layers of ink rendering and the characteristics of calligraphy lines. Digital copies under different shooting conditions have problems such as color distortion and perspective deformation. There is a lack of quantitative connection between artistic expression techniques and legal standards for determining substantial similarity. Finally, the protection system lacks coordination, and data is fragmented between copyright registration, administrative law enforcement and e-commerce platforms. The inconsistent evidence standards make it difficult to accept electronic evidence, and the response to cross-platform infringement is delayed. These problems jointly lead to the current situation in the calligraphy and painting market where the cost of infringement is low and the cost of rights protection is high. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides an intelligent copyright tracing system for calligraphy and painting works. Through three major units: digital evidence storage, intelligent comparison and collaborative feedback, it realizes the full-process copyright protection of calligraphy and painting works; adopts high-precision scanning and neural network technology to ensure the accuracy of identification; and constructs an administrative, judicial and market linkage mechanism to achieve rapid handling of infringements, forming a new paradigm of efficient and reliable copyright protection for calligraphy and painting.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent tracing system for copyright of calligraphy and painting works, including a tracing system for tracing the copyright of calligraphy and painting works, the tracing system comprising:

[0007] The copyright owner evidence storage unit is used to receive and store the identity authentication information, work metadata and digital images submitted by the copyright owner, and generate a work feature fingerprint library through a feature extraction algorithm;

[0008] The work tracing and comparison unit is used to analyze the visual features of the traced work and perform similarity matching with the feature fingerprint library;

[0009] The rights status feedback unit is used to return the comparison results to the tracer and send a confirmation request to the relevant copyright owner, and generate a copyright status report of the work based on the feedback results.

[0010] Preferably, the copyright owner evidence storage unit includes:

[0011] Identity verification module, used to verify the true identity of the copyright owner;

[0012] The work information entry module is used to receive the work title, creation time, and description of the creation technique;

[0013] Image scanning module, supporting digital collection of calligraphy and painting works at least 600dpi;

[0014] The feature extraction module uses a deep convolutional network to extract the composition, color distribution, and brushstroke trajectory feature vectors of the work;

[0015] The blockchain evidence storage module stores the work information and feature vectors on the chain and generates an electronic evidence certificate containing a timestamp.

[0016] Preferably, the work tracing and comparison unit includes:

[0017] A pre-processing module for denoising, color correction and perspective correction of the traced image;

[0018] The feature encoding module uses the same deep convolutional network as the evidence storage subsystem to generate feature vectors;

[0019] The similarity calculation module calculates the similarity score between the traced work and the evidenced work using the cosine similarity algorithm;

[0020] The search and sorting module returns a list of matching results based on similarity from high to low.

[0021] Preferably, the rights status feedback unit includes:

[0022] The result presentation module displays the copyright registration information and similarity analysis charts of the matching works to the tracer;

[0023] The rights holder notification module sends a confirmation request to the copyright owner of the matching work through the preset contact information;

[0024] A status marking module that marks works as confirmed original, authorized copy, suspected infringement, or competing works based on feedback from copyright holders;

[0025] The early warning push module automatically sends infringement warning information to the market supervision platform when it is confirmed to be an infringing work.

[0026] Preferably, the traceability system also includes a data maintenance unit and is used to regularly update the training data set of the artificial intelligence model. The training data set includes a style evolution database of calligraphy and painting works, a feature library of common infringement techniques, and a historical case annotation database.

[0027] Preferably, the traceability system further includes a multi-terminal access unit and is used to provide channels for collecting work data, the collection channels including a museum-specific scanning terminal interface, a mobile APP image acquisition module, and an auction house data batch import API.

[0028] Preferably, the tracing system further includes an evidence preservation unit for automatically generating a legally effective infringement evidence package, wherein the evidence preservation unit includes:

[0029] The infringement evidence fixing module automatically generates an infringement comparison report including a timestamp;

[0030] Forensic identification docking module, with evidence export function that complies with electronic data forensic identification standards;

[0031] The rights protection process guidance module provides suggestions on localized legal remedies.

[0032] Preferably, the traceability system also includes a market supervision linkage unit and is used to achieve real-time data interaction with the supervision platform. The supervision platform includes the copyright registration system of the National Copyright Administration, the comprehensive law enforcement platform of the cultural market and the product review interface of the e-commerce platform.

[0033] The present invention provides an intelligent copyright tracing system for calligraphy and painting works. Compared with the existing technology, it has the following advantages:

[0034] 1. Through the coordinated operation of the three core units, namely the copyright holder evidence storage unit, the work tracing and comparison unit, and the rights status feedback unit, the whole process of digital management of calligraphy and painting works from creation and confirmation to infringement tracing has been realized; it has changed the traditional model of calligraphy and painting copyright protection that relies on paper certificates and expert appraisals, significantly improved the efficiency of copyright management, and at the same time ensured the reliability of appraisal results through standardized processes, providing a new technical guarantee solution for the art market.

[0035] 2. Through high-precision scanning and adaptive color correction technology, the digital copy is ensured to fully restore the artistic characteristics of the original work; a homologous dual-channel neural network architecture is adopted to maintain the consistency of the feature space of evidence storage and tracing; a judicial case annotation system is introduced to convert legal concepts into quantifiable image feature parameters; the system is enabled to accurately identify various common forms of infringement and maintain a high degree of identification accuracy for various calligraphy and painting styles, including freehand brushwork, forming a new standard for intelligent identification applicable to traditional Chinese calligraphy and painting.

[0036] 3. Through the deep integration of market supervision linkage and evidence preservation functions, a copyright protection mechanism that collaborates among administration, judiciary, and the market has been established. When infringing works are detected, the system can quickly secure evidence and trigger cross-platform warnings to enable timely disposal of infringing works. The specially designed electronic evidence chain system significantly shortens the copyright dispute resolution cycle and reduces the cost of rights protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a system block diagram of the present invention;

[0038] Figure 2 A block diagram of the copyright holder's evidence storage unit in the present invention;

[0039] Figure 3 A block diagram of a work tracing and comparison unit in the present invention;

[0040] Figure 4 is a block diagram of the rights status feedback unit in the present invention;

[0041] Figure 5 This is a block diagram of the evidence preservation unit in the present invention.

[0042] In the figure: 1. Traceability system; 11. Copyright owner evidence storage unit; 111. Identity authentication module; 112. Work information entry module; 113. Image scanning module; 114. Feature extraction module; 115. Blockchain evidence storage module; 12. Work traceability and comparison unit; 121. Preprocessing module; 122. Feature encoding module; 123. Similarity calculation module; 124. Retrieval and ranking module; 13. Rights status feedback unit; 131. Result presentation module; 132. Rights holder notification module; 133. Status marking module; 134. Warning push module; 14. Data maintenance unit; 15. Multi-terminal access unit; 16. Evidence preservation unit; 161. Infringement evidence fixation module; 162. Judicial appraisal docking module; 163. Rights protection process guidance module; 17. Market supervision linkage unit. DETAILED DESCRIPTION

[0043] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0044] See also Figure 1 - Figure 5 The present invention provides a technical solution: an intelligent tracing system for copyright of calligraphy and painting works, including a tracing system 1 and used for tracing the copyright of calligraphy and painting works, the tracing system 1 includes:

[0045] The copyright owner evidence storage unit 11 is used to receive and store the identity authentication information, work metadata and work digital images submitted by the copyright owner, and generate a work feature fingerprint library through a feature extraction algorithm;

[0046] The work tracing and comparison unit 12 is used to analyze the visual features of the traced work and perform similarity matching with the feature fingerprint library;

[0047] The rights status feedback unit 13 is used to return the comparison results to the tracer and send a confirmation request to the relevant copyright owner, and generate a work copyright status report based on the feedback results.

[0048] In this implementation plan, the intelligent copyright tracing system for calligraphy and painting works establishes a complete digital fingerprint library of works through the copyright owner's evidence storage unit 11, uses the work tracing and comparison unit 12 to achieve high-precision visual feature matching, and then completes two-way confirmation and status determination through the rights status feedback unit 13, constructing a complete copyright protection closed loop of evidence storage-comparison-right confirmation; the system innovatively combines deep learning technology with calligraphy and painting art feature analysis, solving the core pain points of traditional calligraphy and painting copyright protection such as difficulty in right confirmation, tracing, and rights protection, and realizing full-process digital management from work creation to infringement identification. Compared with traditional manual identification methods, this system improves the efficiency of copyright tracing, and at the same time greatly improves the objectivity and accuracy of identification results through standardized feature extraction and quantitative analysis.

[0049] Specifically, the copyright owner evidence storage unit 11 includes:

[0050] Identity verification module 111, used to verify the true identity of the copyright owner;

[0051] The work information input module 112 is used to receive the work title, creation time, and creation technique description text;

[0052] Image scanning module 113, supporting digital collection of calligraphy and painting works at least 600dpi;

[0053] Feature extraction module 114, which uses a deep convolutional network to extract the composition, color distribution, and brushstroke trajectory feature vectors of the work;

[0054] The blockchain evidence storage module 115 stores the work information and feature vector on the chain and generates an electronic evidence certificate containing a timestamp.

[0055] In this embodiment, the copyright holder evidence storage unit 11 ensures the authenticity of the creator's identity through the identity authentication module 111, fully records the creative background with the help of the work information entry module 112, uses the high-precision image scanning module 113 to achieve lossless digitization of the work, and deeply analyzes the artistic characteristics through the feature extraction module 114. Finally, the blockchain evidence storage module 115 realizes the permanent solidification of information. This unit constructs a full-process evidence storage system of identity verification-information collection-feature analysis-blockchain evidence storage, which not only preserves the artistic characteristics of calligraphy and painting works, but also converts them into verifiable digital fingerprints, solving the pain points of incomplete work feature records and insufficient evidence validity in traditional copyright registration. In particular, the application of blockchain technology makes the evidence information tamper-proof and legally effective, providing original evidence with judicial credibility for possible subsequent copyright disputes, greatly improving the standardization and authority of copyright protection of calligraphy and painting works.

[0056] Specifically, the work tracing and comparison unit 12 includes:

[0057] A pre-processing module 121 is used to perform denoising, color correction and perspective correction on the traced image;

[0058] Feature encoding module 122, which uses the same deep convolutional network as the evidence storage subsystem to generate feature vectors;

[0059] A similarity calculation module 123 calculates the similarity score between the traced work and the evidenced work using a cosine similarity algorithm;

[0060] The search ranking module 124 returns a list of matching results in descending order of similarity.

[0061] In this embodiment, the work tracing and comparison unit 12 ensures input image quality standardization through a preprocessing module 121, achieves high-precision feature extraction through a feature encoding module 122, completes scientific and quantitative comparison through a similarity calculation module 123, and provides ordered result output through a retrieval and ranking module 124. This unit constructs a complete comparison chain from image optimization to feature extraction to similarity analysis to result ranking. It uses a neural network derived from the same source as the evidence storage system to ensure feature space consistency and combines it with a cosine similarity algorithm to achieve objective quantitative evaluation, effectively resolving the problem of misjudgment caused by differences in shooting conditions and storage status in the comparison of calligraphy and painting works. It innovatively transforms the dimension of artistic appreciation into computable image feature parameters, achieving technical comparison while maintaining the artistic characteristics of the calligraphy and painting works. This transforms the traditional subjective identification based on expert experience into a repeatable and verifiable objective analysis, significantly improving the scientific nature and efficiency of copyright tracing and providing a reliable technical basis for copyright protection of calligraphy and painting works.

[0062] Specifically, the rights status feedback unit 13 includes:

[0063] The result presentation module 131 displays the copyright registration information and similarity analysis chart of the matching works to the tracer;

[0064] The rights holder notification module 132 sends a confirmation request to the copyright owner of the matching work through a preset contact method;

[0065] Status marking module 133, marking the work as original, authorized copy, suspected infringement, or competing work based on feedback from the copyright owner;

[0066] The early warning push module 134 automatically sends infringement warning information to the market supervision platform when it is confirmed to be an infringing work.

[0067] In this embodiment, the rights status feedback unit 13 provides a visual analysis report for the tracer through the result presentation module 131, establishes an active confirmation mechanism for the original author with the help of the rights holder notification module 132, and then realizes the intelligent classification of the legal status of the work through the status marking module 133. Finally, the early warning push module 134 completes the automatic supervision linkage of infringement behavior; this unit constructs a closed-loop feedback process of technical judgment-manual confirmation-classification disposal, which not only ensures the effective connection between technical judgment and legal recognition, but also avoids the risk of algorithmic misjudgment through the participation of rights holders in the confirmation link; when an infringing work is discovered, the system automatically triggers a cross-platform early warning mechanism, compressing the traditional manual rights protection process that takes several weeks to a real-time response. While protecting the copyright owner's right to know and the right to participate, it greatly improves the efficiency of infringement disposal, realizes the organic unity of technical identification and legal recognition, and provides a solution for the copyright protection of calligraphy and painting works that is both accurate and timely.

[0068] Specifically, the traceability system 1 also includes a data maintenance unit 14 and is used to regularly update the training data set of the artificial intelligence model. The training data set includes a style evolution database of calligraphy and painting works, a feature database of common infringement methods, and a historical case annotation database.

[0069] In this embodiment, by adopting incremental learning technology, it is possible to continuously absorb new characteristics of calligraphy and painting creation styles and changes in infringement patterns without affecting the performance of the existing model, so that the system's recognition capabilities keep pace with the times. By integrating historical judicial case data, the unit can also convert legal recognition standards into machine-recognizable feature parameters, significantly improving the system's accuracy in judging legal concepts such as substantial similarity; this continuously evolving data maintenance mechanism effectively solves the recognition blind spot problem caused by data aging in traditional copyright protection systems, ensuring that the system can still maintain high-precision identification capabilities when facing new creative techniques and infringement methods, providing long-term and reliable technical support for the protection of copyrights of calligraphy and painting works.

[0070] Specifically, the tracing system 1 further includes a multi-terminal access unit 15 and is used to provide channels for collecting work data. The collection channels include a museum-specific scanning terminal interface, a mobile APP image acquisition module, and an auction house data batch import API.

[0071] In this embodiment, by adopting adaptive processing technology, the digitization efficiency of different types of calligraphy and painting works is significantly improved while ensuring the true restoration of the colors and details of the works; the museum interface supports high-precision professional-level acquisition, the mobile application provides a convenient daily acquisition solution, and the auction house interface realizes efficient processing of large quantities of data. The collaborative work of the three breaks the traditional calligraphy and painting digitization's dependence on professional equipment and venues, and establishes a standardized data input channel covering various application scenarios for the copyright traceability system, so that calligraphy and painting works from different sources can obtain the same copyright protection services, greatly expanding the applicability and popularity of the system.

[0072] Specifically, the tracing system 1 further includes an evidence preservation unit 16 for automatically generating a legally binding infringement evidence package. The evidence preservation unit 16 includes:

[0073] The infringement evidence fixing module 161 automatically generates an infringement comparison report including a timestamp;

[0074] Forensic authentication docking module 162, which has an evidence export function that complies with electronic data forensic authentication standards;

[0075] The rights protection process guidance module 163 provides suggestions on local legal remedies.

[0076] In this embodiment, the infringement evidence fixing module 161 automatically generates an infringement comparison report containing a blockchain timestamp to ensure the integrity and non-tamperability of electronic evidence; the judicial appraisal docking module 162 strictly follows the "Electronic Data Judicial Appraisal Specifications" standard to achieve standardized packaging and one-click export of evidence materials to meet the evidence collection requirements of judicial organs; the rights protection process guidance module 163 intelligently matches localized rights protection plans based on the place where the infringement occurred and the type of work, and provides optimal rights protection path recommendations including administrative complaints and civil litigation; this unit realizes the full process of electronic processing from infringement evidence collection and fixation to judicial application, and optimizes the time-consuming and costly evidence preservation link in the traditional calligraphy and painting rights protection into an automated and standardized process, significantly lowering the copyright owner's rights protection threshold. At the same time, it greatly improves the rights protection success rate through the evidence solidification method that meets judicial standards, providing strong technical support and legal protection for combating infringement of calligraphy and painting works.

[0077] Specifically, the traceability system 1 also includes a market supervision linkage unit 17 and is used to achieve real-time data interaction with the supervision platform. The supervision platform includes the copyright registration system of the National Copyright Administration, the comprehensive law enforcement platform of the cultural market and the product review interface of the e-commerce platform.

[0078] This embodiment enables real-time cross-platform sharing and collaborative handling of infringement information, establishing a comprehensive regulatory mechanism encompassing intelligent identification, automatic early warning, and coordinated handling. When the system identifies an infringing work, it automatically transmits evidence of infringement to the National Copyright Administration to prevent its registration. This evidence is then pushed to the Cultural Law Enforcement Platform in real time to initiate administrative enforcement procedures. It also triggers the e-commerce platform's product review interface to rapidly remove infringing products from shelves. This multi-department collaborative regulatory model significantly improves the efficiency of infringement handling, shortening the traditional rights protection cycle from several months to real-time response. It effectively addresses industry pain points such as the difficulty in identifying and handling infringements of calligraphy and painting works, slow handling, and cross-platform accountability.

[0079] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "includes," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0080] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent copyright tracing system for calligraphy and painting works, characterized by: The invention comprises a tracing system (1) and is used for tracing the copyright of calligraphy and painting works. The tracing system (1) comprises: The copyright owner evidence storage unit (11) is used to receive and store the identity authentication information, work metadata and work digital image submitted by the copyright owner, and generate a work feature fingerprint library through a feature extraction algorithm; A work tracing and comparison unit (12) is used to analyze the visual features of the work being traced and perform similarity matching with a feature fingerprint library; The rights status feedback unit (13) is used to return the comparison results to the tracer and send a confirmation request to the relevant copyright owner, and generate a work copyright status report based on the feedback results.

2. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The copyright owner evidence storage unit (11) includes: An identity verification module (111) is used to verify the true identity of the copyright owner; The work information entry module (112) is used to receive the work title, creation time, and creation technique description text; Image scanning module (113), supporting digital collection of calligraphy and painting works at least 600dpi; A feature extraction module (114) uses a deep convolutional network to extract the composition, color distribution, and brushstroke trajectory feature vectors of the work; The blockchain evidence storage module (115) stores the work information and feature vectors on the chain and generates an electronic evidence certificate containing a timestamp.

3. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The work tracing and comparison unit (12) includes: A pre-processing module (121) for performing denoising, color correction and perspective correction on the traced image; The feature encoding module (122) generates feature vectors using a deep convolutional network that is the same as the evidence storage subsystem; A similarity calculation module (123) calculates the similarity score between the traced work and the evidenced work using a cosine similarity algorithm; The search ranking module (124) returns a list of matching results according to the similarity from high to low.

4. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The rights status feedback unit (13) comprises: A result presentation module (131) displays the copyright registration information and similarity analysis chart of the matching works to the tracer; The rights holder notification module (132) sends a confirmation request to the copyright owner of the matching work through a preset contact method; Status marking module (133), which marks the work as original, authorized copy, suspected infringement or competing work based on the copyright owner's feedback; The early warning push module (134) automatically sends infringement warning information to the market supervision platform when it is confirmed to be an infringing work.

5. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The tracing system (1) further includes a data maintenance unit (14) for regularly updating a training data set of an artificial intelligence model, wherein the training data set includes a calligraphy and painting style evolution database, a common infringement method feature database, and a historical case annotation database.

6. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The tracing system (1) further comprises a multi-terminal access unit (15) for providing a work data collection channel, wherein the collection channel comprises a museum-specific scanning terminal interface, a mobile APP image collection module and an auction house data batch import API.

7. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The tracing system (1) further includes an evidence preservation unit (16) for automatically generating a legally effective infringement evidence package, wherein the evidence preservation unit (16) includes: Infringement evidence fixing module (161), automatically generates infringement comparison report including timestamp; Forensic identification docking module (162), which has the function of exporting evidence in accordance with the electronic data forensic identification standards; The rights protection process guidance module (163) provides suggestions on local legal remedies.

8. The intelligent copyright tracing system for calligraphy and painting works according to claim 1 is characterized by: The traceability system (1) further includes a market supervision linkage unit (17) for realizing real-time data interaction with a supervision platform, wherein the supervision platform includes a copyright registration system of the National Copyright Administration, a comprehensive law enforcement platform for the cultural market, and a commodity review interface of an e-commerce platform.

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