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Computer-Aided Virtual Restoration of Frescoes Based on Intelligent Generation of Line Drawings

Author

Listed:
  • Chao Jiang
  • Zhen Jiang
  • Daijiao Shi
  • Wen-Tsao Pan

Abstract

Dunhuang frescoes are one of China’s precious historical and cultural heritages, but this treasure trove of human art has become very fragile due to natural weathering damage and the threat of major natural disasters. Therefore, the preservation of Dunhuang murals has become an urgent task. Digital fresco conservation and restoration work can preserve fresco information permanently, and can use computers to virtually repair frescoes, assist in fresco conservation, assist in fresco copying, virtually evolve the fresco disease process, and virtually display fresco realism. Digital fresco conservation and restoration provides sufficient scientific basis and testing environment for the physical conservation and restoration process of frescoes, and minimizes the danger of conservation work. This paper presents a new approach to digital conservation and virtual restoration of frescoes. Based on research by Dunhuang artists on the mural restoration process, research on pigment composition, knowledge accumulated by the artists’ experience, and some of the better-preserved murals, digital image processing, computer graphics, artificial intelligence, and other technologies are synthesized to achieve the virtual restoration of murals. Aiming at the current situation of Dunhuang mural restoration, combined with the actual painting process, this paper puts forward a set of computer-aided mural restoration solution based on intelligent generation of line graph. It can be well applied to the actual restoration work. It is a new attempt of computer-aided restoration of ancient paintings.

Suggested Citation

  • Chao Jiang & Zhen Jiang & Daijiao Shi & Wen-Tsao Pan, 2022. "Computer-Aided Virtual Restoration of Frescoes Based on Intelligent Generation of Line Drawings," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, June.
  • Handle: RePEc:hin:jnlmpe:9092765
    DOI: 10.1155/2022/9092765
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