基于手写字符信息调制的NFT数字艺术图像生成算法的研究

Research on NFT Digital Art Image Generation Algorithm Based on Handwritten Character Information Modulation

在知识产权大保护的主流价值观下,本研究提出了一种基于手写字符信息调制的NFT数字艺术图像生成算法,为数字作品或实物的价值量化、所有权归属等问题提供了解决方案。首先,运用彩色梯度算法进行高频和边缘轮廓的图像分割;其次,使用加权质心Voronoi算法将分割后的背景图像生成点画图像;然后,以点画图像的点集坐标为基准,生成的唯一识别号为约束,放置手写字符,绘制出具有手写字体纹理的调制图像;最后,利用局部空间不变性,实现轮廓图像和背景调制图像的融合。实验表明,本研究算法所生成的NFT图像具有高效的语义契约,在保证唯一性、可溯性、安全性的同时,还具有海量信息容量空间的保障,不仅可用作艺术收藏,还可用作实物或数字作品的防伪鉴权及其增值服务。

Under the mainstream value of intellectual property protection,an NFT digital art image generation method based on handwritten character information modulation was proposed which provides solutions for the problems such as the quantification of value and ownership of digital or real works.Firstly,the color gradient algorithm was used to segment high-frequency and edge contour images.Secondly,the weighted centroid Voronoi algorithm was applied to generate stipple image from segmented background image.Then,handwritten characters were placed to draw a modulated image with handwritten font texture,based on the coordinate of point set of the stipple image as the reference and the unique identification number as the constraint.Finally,the fusion of contour image and background modulation image was realized by using local space invariance.The results showed that the NFT image invented by this algorithm had efficient semantic contract,which guarantees uniqueness,traceability and security,and also had the guarantee of mass information capacity space.The NFT digital art images can not only be used as art collections,but also as anti-counterfeiting authentication and value-added services for real or digital works.