Digital restoration of cultural relics based on 3D modeling and machine vision

As technology rapidly develops, modern technological means have gradually been introduced into the area of cultural relic protection. To strengthen the accuracy and efficiency of cultural relic restoration, a fully digital restoration method is adopted, utilizing computer 3D modeling, machine vision, and Generative Adversarial Networks (GAN) technologies for image restoration. This method uses GAN for image preprocessing and selection of areas to be repaired, to digitally restore the surface decorative patterns of cultural relics. Moreover, the repaired decorative patterns is combined with a 3D structural model, further enhancing the accuracy and effectiveness of digital restoration of cultural relics by introducing conditional variables, gated convolutions, and contextual attention layers. The findings denoted that the PSNR and SSIM values of the proposed method were as high as 31.20 dB and 0.94, respectively. The initial Frechet distance value was 16.84, and the continuity of the ornamentation was as high as 0.93. In addition, the double-blind subjective evaluation findings denoted that the average score for the completeness of the decorative patterns in the research method reached 9.30. In summary, the digital restoration of cultural relics grounded on 3D modeling and machine vision has effectively strengthened the accuracy and efficiency of cultural relic restoration, providing new possibilities for the long-term preservation and display of cultural relics.