arXiv:2411.10668cs.CVcs.DL2024-11

用多光谱图像分割死海古卷的墨迹与羊皮纸区域

Segmentation of Ink and Parchment in Dead Sea Scroll Fragments

  • 基于多光谱特征和能量最小化,精准分离墨迹与羊皮纸
  • 在20个碎片上测试,显著优于Otsu、Sauvola等传统方法
  • 适合古籍数字化、文物图像分析的研究者参考

60多年前发现的死海古卷被誉为现代最重要的考古突破之一。近期研究面临诸多计算挑战,包括碎片来源溯源、按相似度聚类及配对同一手稿的碎片,这些任务均需关注单个字母与碎片形状。本文提出一种针对多光谱图像的墨迹与羊皮纸区域分割方法。利用新构建的Qumran Segmentation Dataset(QSD,含20个碎片),通过多光谱阈值法根据其独特光谱特征分离墨迹与羊皮纸区域。为进一步提升精度,引入基于墨迹轮廓的能量最小化技术,该轮廓相比内部墨迹更易区分且噪声更少。实验表明,所提多光谱阈值与能量最小化(MTEM)方法在羊皮纸分割上显著优于Otsu、Sauvola等传统二值化方法,并能有效勾勒墨迹边界,区别于孔洞与背景区域。

原文摘要 · Abstract (English)

The discovery of the Dead Sea Scrolls over 60 years ago is widely regarded as one of the greatest archaeological breakthroughs in modern history. Recent study of the scrolls presents ongoing computational challenges, including determining the provenance of fragments, clustering fragments based on their degree of similarity, and pairing fragments that originate from the same manuscript -- all tasks that require focusing on individual letter and fragment shapes. This paper presents a computational method for segmenting ink and parchment regions in multispectral images of Dead Sea Scroll fragments. Using the newly developed Qumran Segmentation Dataset (QSD) consisting of 20 fragments, we apply multispectral thresholding to isolate ink and parchment regions based on their unique spectral signatures. To refine segmentation accuracy, we introduce an energy minimization technique that leverages ink contours, which are more distinguishable from the background and less noisy than inner ink regions. Experimental results demonstrate that this Multispectral Thresholding and Energy Minimization (MTEM) method achieves significant improvements over traditional binarization approaches like Otsu and Sauvola in parchment segmentation and is successful at delineating ink borders, in distinction from holes and background regions.

古籍图像多光谱分割文物数字化

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