Abstract
Modern digitised approaches have dramatically changed the preservation and restoration of cultural treasures, integrating computer scientists into multidisciplinary projects with ease. Machine learning, deep learning, and computer vision techniques have revolutionised developing sectors like 3D reconstruction, picture inpainting,IoT-based methods, genetic algorithms, and image processing with the integration of computer scientists into multidisciplinary initiatives. We suggest three cutting-edge techniques in recognition of the special qualities of Indian monuments, which are famous for their architectural skill and aesthetic appeal. First is the Fractal Convolution methodology, a segmentation method based on image processing that successfully reveals subtle architectural patterns within these irreplaceable cultural buildings. The second is a revolutionary Self-Sensitive Tile Filling (SSTF) method created especially for West Bengal's mesmerising Bankura Terracotta Temples with a brand-new data augmentation method called MosaicSlice on the third. Furthermore, we delve deeper into the Super Resolution strategy to upscale the images without losing significant amount of quality. Our methods allow for the development of seamless region-filling and highly detailed tiles while maintaining authenticity using a novel data augmentation strategy within affordable costs introducing automation. By providing effective solutions that preserve the delicate balance between tradition and innovation, this study improves the subject and eventually ensures unrivalled efficiency and aesthetic excellence in cultural heritage protection. The suggested approaches advance the field into an era of unmatched efficiency and aesthetic quality while carefully upholding the delicate equilibrium between tradition and innovation.
Abstract (translated)
现代数字化方法已经极大地改变了文化遗产的保护和修复，将计算机科学家轻松地融入多学科项目中。机器学习、深度学习以及计算机视觉技术在3D重建、图像修补、基于物联网的方法、遗传算法及图像处理等领域革新了发展中的行业，尤其是在计算机科学家参与多学科合作的情况下。 我们针对印度纪念碑的独特特点提出了三种前沿技术，这些纪念碑以其建筑技艺和美学吸引力而闻名于世。第一项是分形卷积方法（Fractal Convolution methodology），这是一种基于图像处理的分割方法，能够成功揭示这些不可替代的文化建筑中的细微建筑模式。第二种是一项革命性的自适应填砖法（Self-Sensitive Tile Filling, SSTF），专门为西孟加拉邦令人着迷的班库拉陶制寺庙设计，并引入了一种全新的数据增强技术——马赛克切片（MosaicSlice）。第三，我们深入探讨了超分辨率策略，在不影响图像质量的前提下提升图像分辨率。我们的方法允许在保持真实性的同时发展无缝区域填充和高度详细的砖块，通过一种新颖的数据增强策略以经济实惠的方式实现自动化。 本研究提供有效的解决方案来维护传统与创新之间的微妙平衡，并最终确保文化遗产保护的无与伦比效率及美学卓越性。所提出的方案将该领域推进到一个前所未有的高效性和美学质量的时代，同时谨慎地保持了传统与创新之间微妙的均衡。
URL
https://arxiv.org/abs/2507.12195
