Abstract
Virtual color restoration is an important work to protect or exhibit decorative paintings on ancient architecture. This paper proposes a novel method of colorful pattern segmentation and color restoration for ancient architecture based on improve color transfer algorithm. First, a color image and a shape image are converted from the RGB to \(l\alpha \beta\) color space. Second, the color and shape images are segmented using the improved clustering algorithm of density-based GMM (Gauss mixture model). Third, the relations between the color and shape image regions are determined using the nearest region-matching algorithm to avoid the problem in which multiple areas are matched to the same region. Finally, color is transferred to the corresponding region in the shape image, and a merged image is obtained. Contrastive experimental results demonstrate that the proposed method can restore paintings of ancient architecture effectively more accurately and efficiently.
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Zhang, Z. (2023). Virtual Color Restoration for Ancient Architecture by Color Transfer. In: You, P., Li, H., Chen, Z. (eds) Proceedings of International Conference on Image, Vision and Intelligent Systems 2022 (ICIVIS 2022). ICIVIS 2022. Lecture Notes in Electrical Engineering, vol 1019. Springer, Singapore. https://doi.org/10.1007/978-981-99-0923-0_24
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DOI: https://doi.org/10.1007/978-981-99-0923-0_24
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