Blockchain-based image copyright registration method supporting multi-dimensional data query

Blockchain technology for image copyright registration eliminates the dependence on third-party institutions, making it a current research hotspot. However, existing methods suffer from a critical bottleneck: the lack of an efficient on-chain mechanism for originality detection, as they rely on inefficient, single-mode queries. This article proposes the multi-dimensional query (MDQ) scheme, a blockchain-based image copyright registration framework designed to solve this challenge. The core of our scheme is a novel block storage structure, the Merkle-KD (MKD) tree, which synergistically combines the verifiability of Merkle trees with the efficiency of KD-trees. This structure enables fast, multi-dimensional similarity searches directly on the blockchain, allowing for robust originality checks to be performed prior to registration. At the same time, user identity is embedded within the copyright data to enable user-specific information queries. The effectiveness of our scheme is validated through simulation experiments, which demonstrate that our proposed method significantly improves the efficiency of image copyright registration and expands the on-chain copyright query modes.

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Publication Details

Journal
PeerJ Computer Science
Published
2025-10-15
DOI
https://doi.org/10.7717/peerj-cs.3284
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Blockchain-based image copyright registration method supporting multi-dimensional data query

Yuwei Sun, Chenlei Liu, Lu Chen, ZiXuan Wang et al.
PeerJ Computer Science
Brain Tumor Detection and Classification
article

Blockchain-based image copyright registration method supporting multi-dimensional data query

Yuwei Sun, Chenlei Liu, Lu Chen, ZiXuan Wang, Zhixin Sun
article en

Abstract

Blockchain technology for image copyright registration eliminates the dependence on third-party institutions, making it a current research hotspot. However, existing methods suffer from a critical bottleneck: the lack of an efficient on-chain mechanism for originality detection, as they rely on inefficient, single-mode queries. This article proposes the multi-dimensional query (MDQ) scheme, a blockchain-based image copyright registration framework designed to solve this challenge. The core of our scheme is a novel block storage structure, the Merkle-KD (MKD) tree, which synergistically combines the verifiability of Merkle trees with the efficiency of KD-trees. This structure enables fast, multi-dimensional similarity searches directly on the blockchain, allowing for robust originality checks to be performed prior to registration. At the same time, user identity is embedded within the copyright data to enable user-specific information queries. The effectiveness of our scheme is validated through simulation experiments, which demonstrate that our proposed method significantly improves the efficiency of image copyright registration and expands the on-chain copyright query modes.

PeerJ Computer ScienceVol. 11
Nanjing Institute of Technology (CN), Nanjing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 64%
Brain Tumor Detection and Classification
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