Huang Qizheng, Zhu Jiayi, Xian Yuanjie, Peng Jiyou
Shanghai Jincai South Seconday School, Shanghai, China.
School of Mechanical Engineering, Hefei University of Technology, Hefei, Anhui, China.
PLoS One. 2025 Aug 25;20(8):e0323447. doi: 10.1371/journal.pone.0323447. eCollection 2025.
Due to the rapid growth of the digital music industry, music copyrights have become valuable intangible assets for businesses, offering exclusivity and profitability. This article takes music copyrights as an example and designs a copyright protection method for music score digital images. The zero-watermarking algorithm offers an effective and lossless means of copyright protection. Owing to their geometric invariance, orthogonal moments exhibit superior robustness, positioning them as one of the mainstream methods in the research of zero-watermarking algorithms. The current zero-watermarking algorithms based on orthogonal moments face a trade-off between robustness and discriminability. In this paper, we propose a mixed low-order moments method based on quaternion-type fractional-order moments (QTFM), which balances the global information and texture details of color image contained in QTFM. Experimental results show that the mixed low-order moments method based on QTFM exhibits superior performance in terms of robustness. In the context of using mixed low-order moment features for image analysis, Franklin moments achieve higher average structural similarity (SSIM) values than other QTFMs.
由于数字音乐产业的快速发展,音乐版权已成为企业宝贵的无形资产,具有排他性和盈利能力。本文以音乐版权为例,设计了一种针对乐谱数字图像的版权保护方法。零水印算法提供了一种有效且无损的版权保护手段。由于其几何不变性,正交矩具有卓越的鲁棒性,使其成为零水印算法研究中的主流方法之一。当前基于正交矩的零水印算法在鲁棒性和可区分性之间面临权衡。本文提出了一种基于四元数型分数阶矩(QTFM)的混合低阶矩方法,该方法平衡了QTFM中包含的彩色图像的全局信息和纹理细节。实验结果表明,基于QTFM的混合低阶矩方法在鲁棒性方面表现出卓越的性能。在使用混合低阶矩特征进行图像分析的背景下,富兰克林矩比其他QTFM获得更高的平均结构相似性(SSIM)值。