Abstract
In the traditional cultural relic image digital repair system, there are obvious color aberrations and structural deviations between the restored part and the surrounding part, which weakens the visual connectivity of the restored result. In view of this, this research designs a digital repair system of damaged cultural relics image in professional training of restoration. In the hardware of the system, an integrated fast spherical camera is designed, and the transformation between image and pixel coordinate system is expressed by homogeneous coordinate system according to its parameters. In the system software, the damaged areas of cultural relics images are segmented and marked first, and the optimization algorithm of texture synthesis and restoration based on samples is designed. The experimental test results show that the system in this paper can ensure the use of the known information of the original image to the greatest extent, and make the repair result more reasonable on the basis of the minimum modification of the original image, so as to achieve the effect of professional practical training of repair.
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References
Jiang, C., Wang, J., Yu, L.: Research on a digital restoration method for textile cultural relics. Silk 56(11), 21–25 (2019)
Yao, Y., Hu, W., Ren, Y., et al.: Detection and localization of digital video regional tampering. J. Image Graph. 23(06), 779–791 (2018)
Cui, T., Xu, K., Yan, S.: Improved criminisi algorithm based on sobel operator. Comput. Digit. Eng. 46(10), 2111–2116 (2018)
Sun, J., Cao, F., Tang, Z., et al.: Trustable image inpainting method based on image mosaics. J. Univ. Shanghai Sci. Technol. 40(02), 150–157 (2018)
Xiang, P., Wuzhen, J., Herong, Z., et al.: Combining interpolated subdivision and radial basis function for filling 3D scanning data. J. Image Graph. 23(04), 564–571 (2018)
Lulu, Z., Shaoyan, G., Feipeng, D., et al.: Hole filling algorithm of three-dimensional point cloud based on structure from motion. Acta Optica Sinica 38(06), 131–137 (2018)
Qi, Z., Suzhen, L., Jialu, B., et al.: Opening-hole repairing in point cloud based on improved curve contraction flows. Laser Optoelectron. Prog. 55(09), 125–131 (2018)
Vincenti, G., Bucciero, A., Helfert, M., Glowatz, M. (eds.): E-Learning, E-Education, and Online Training. LNICSSITE, vol. 180. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-49625-2
Fu, W., Liu, S., Srivastava, G.: Optimization of big data scheduling in social networks. Entropy 21(9), 902 (2019)
Liu, S., Li, Z., Zhang, Y., et al.: Introduction of key problems in long-distance learning and training. Mob. Netw. Appl. 24(1), 1–4 (2019)
Fan, C.Q., Ren, K., Meng, L.S., et al.: Advances in digital image inpainting algorithms based on deep learning. J. Sign. Process. 36(01), 102–109 (2020)
Chen, Q., Zhang, L.H.: Design of simulation system for authenticity reproduction of cultural relics in digital museum. Sci. Technol. Eng. 19(11), 195–200 (2019)
Zhang, Y., Geng, G. H.: Matching method of damaged cultural relic images based on scale invariant feature transform and bounded distortion mapping. J. Xiamen Univ. (Nat. Sci.) 58(03), 449–454 (2019)
Tu, D.W., Lan, H., Zhang, X.: Digital three-dimensional reconstruction technology of cultural relics. Laser Optoelectron. Prog. 56(19), 196–202 (2019)
Funding
1. 2018 Tibet University Scientific Research and Cultivation Fund Project (Growth Plan) Project Number: ZDCZJH18–15.
2. “The Education Department of Tibet Autonomous Region’Building a National Team and Key Laboratory of Computer and Tibetan Information Technology' (Zang Jiao Cai Zhi [2018] No. 81)”.
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Shen, St., Chen, Ym. (2021). Design of Digital Repair System for Damaged Cultural Relic Image in the Professional Training of Restoration. In: Fu, W., Liu, S., Dai, J. (eds) e-Learning, e-Education, and Online Training. eLEOT 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-030-84383-0_28
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DOI: https://doi.org/10.1007/978-3-030-84383-0_28
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