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<p>Archeological line drawings are essential in archeological research, providing visual representations of artifact morphology and precise geometric measurements. Traditionally, these drawings were meticulously created by hand, a process that is time-consuming and labor-intensive. To overcome these limitations, this paper presents an algorithm for extracting feature lines from sculpture point cloud, enabling the automated generation of archeological line drawings. The method introduces a weighted centroid-based geometric metric to identify surface feature points and classify them based on their concavity or convexity. An iterative refinement process is then applied to ensure that feature points align correctly along the feature lines, and boundary points are extracted using an angular criterion. Finally, an enhanced curve-growing algorithm connects the feature and boundary points, producing a 3D line drawing. Experiments conducted on various stone sculptures demonstrate the practicality and accuracy of the proposed approach, with results showing significant improvements over existing methods.</p>

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Automated generation of archeological line drawings from sculpture point cloud based on weighted centroid projection

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月13日

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  • Jian Li,
  • Juntao Yang,
  • Guohe Han,
  • Hao Wu,
  • Jin Zhu,
  • Hao Cui

摘要

Archeological line drawings are essential in archeological research, providing visual representations of artifact morphology and precise geometric measurements. Traditionally, these drawings were meticulously created by hand, a process that is time-consuming and labor-intensive. To overcome these limitations, this paper presents an algorithm for extracting feature lines from sculpture point cloud, enabling the automated generation of archeological line drawings. The method introduces a weighted centroid-based geometric metric to identify surface feature points and classify them based on their concavity or convexity. An iterative refinement process is then applied to ensure that feature points align correctly along the feature lines, and boundary points are extracted using an angular criterion. Finally, an enhanced curve-growing algorithm connects the feature and boundary points, producing a 3D line drawing. Experiments conducted on various stone sculptures demonstrate the practicality and accuracy of the proposed approach, with results showing significant improvements over existing methods.