Proceedings of the 4th International Conference on Information Technology and Management Innovation 2015
DOI: 10.2991/icitmi-15.2015.205
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A Survey on Thangka Image Inpainting Method Based on Structure-borne

Abstract: Abstract. The ancient Tangka image with reflecting Tibet art has been broken by the nature and human with different degrees.The part-shed Tangka image is researched as a type of special breaking. After discussing digital image inpainting, the digital image restoration based on the structure, and Thangka image inpainting method, we give some direction of the development of Tangka image restoration based on structure-borne.

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Cited by 5 publications
(2 citation statements)
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“…This method solved the problem of extracting and expressing the features of the Thangka Buddha headdress. Liu L et al [32] proposed a method to repair the damaged images by using similar blocks adjacent to the damaged area of the image. Hu et al [33] proposed a reference-free quality assessment method, which addresses the quality assessment problem of rendered Thangka images.…”
Section: Artificial Intelligence Educationmentioning
confidence: 99%
“…This method solved the problem of extracting and expressing the features of the Thangka Buddha headdress. Liu L et al [32] proposed a method to repair the damaged images by using similar blocks adjacent to the damaged area of the image. Hu et al [33] proposed a reference-free quality assessment method, which addresses the quality assessment problem of rendered Thangka images.…”
Section: Artificial Intelligence Educationmentioning
confidence: 99%
“…Some researchers have investigated Thangka cleaning methods, summarizing dry cleaning and wet cleaning methods [34]. Additionally, some scholars have utilized computer image processing techniques to simulate the restoration of Thangka images, providing new approaches for Thangka preservation [35]. A notable study has delved into the use of virtual reality (VR) technology to preserve traditional Thangka techniques.…”
Section: Introductionmentioning
confidence: 99%