基于特征区域划分的文物碎片自动匹配算法

赵夫群; 耿国华

doi:10.12263/DZXB.20201236

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基于特征区域划分的文物碎片自动匹配算法

学术论文 | 更新时间：2025-12-08

- 基于特征区域划分的文物碎片自动匹配算法
- Automatic Matching Algorithm of Cultural Relic Fragments Based on Feature Region Division
- 电子学报 2022年50卷第6期页码：1436-1443
- 作者机构：
  
  1.西安财经大学信息学院，陕西西安 710100
  2.西北大学信息科学与技术学院，陕西西安 710127
- 作者简介：
  
  [ "赵夫群女，1982年生，山东临沂人.博士，现为西安财经大学信息学院副教授.主要研究方向为图形图像处理，三维重建.E-mail: fuqunzhao@126.com" ]
  [ "耿国华女，1955年生，山东莱西人.现为西北大学信息科学与技术学院教授，博士生导师.主要研究方向为计算机辅助文物数字化复原.E-mail: ghgeng@nwu.edu.cn" ]
- 基金信息：
  
  国家重点自然科学基金(61731015);陕西省自然科学基础研究计划(2021JQ-765);陕西省哲学社会科学重大理论与现实问题研究项目(2021ND0141);西安财经大学科研计划(20FCJH002)
- DOI：10.12263/DZXB.20201236
  中图分类号： TP391;
- 收稿：2020-11-02，
  
  修回：2021-02-28，
  
  纸质出版：2022-06-25
- 稿件说明：
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赵夫群,耿国华.基于特征区域划分的文物碎片自动匹配算法[J].电子学报,2022,50(06):1436-1443.

ZHAO Fu-qun,GENG Guo-hua.Automatic Matching Algorithm of Cultural Relic Fragments Based on Feature Region Division[J].ACTA ELECTRONICA SINICA,2022,50(06):1436-1443.
赵夫群,耿国华.基于特征区域划分的文物碎片自动匹配算法[J].电子学报,2022,50(06):1436-1443. DOI： 10.12263/DZXB.20201236.

ZHAO Fu-qun,GENG Guo-hua.Automatic Matching Algorithm of Cultural Relic Fragments Based on Feature Region Division[J].ACTA ELECTRONICA SINICA,2022,50(06):1436-1443. DOI： 10.12263/DZXB.20201236.

摘要

在破损文物虚拟复原过程中，碎片匹配是重要研究内容之一，而传统几何驱动匹配算法对断裂面重叠率较低碎片的匹配误差较大，因此针对具有一定厚度的文物，本文提出一种基于特征区域划分的文物碎片自动匹配拼接算法.首先提取文物碎片的断裂面，并在断裂面上点的局部区域内构造法向量特征，计算断裂面的特征点和特征点集；然后将特征点集划分为多个小规模的点云区域，并通过区域匹配将碎片断裂面初步对齐；最后利用基于阈值约束的迭代最近点（Iterative Closest Point，ICP）算法对特征点进行精确对齐，从而实现碎片的最终匹配.实验结果表明，该基于特征区域划分的文物碎片匹配算法的时间效率和匹配精度，比多数已有算法至少可以分别提高10%和20%，适用于低重叠断裂面的文物碎片匹配.

Abstract

In the process of virtual restoration of damaged cultural relics

fragments matching is one of the important research contents. The traditional geometric driven matching algorithms have large matching error for fracture surfaces with low overlapping rate

thus aiming at cultural relics with certain thickness

an automatic matching and splicing algorithm of cultural relics fragments based on feature region division is proposed. Firstly

the fracture surfaces of fragments are extracted

normal vector features are constructed in the local region of the points on the fracture surface to obtain the feature points and feature point sets of the fracture surfaces; secondly

each feature point set is divided into several small-scale point cloud regions

and the fragment fracture surfaces are aligned by region matching; finally

the iterative closest point (ICP) algorithm based on threshold constraint is used to further accurately align the fracture surfaces

so as to achieve the final matching of cultural relic fragments. The experimental results show that the time efficiency and matching accuracy of the proposed algorithm are at least 10% and 20% higher than those of many existing algorithms

respectively

and it is suitable for the matching of cultural relic fragments with low overlapping fracture surfaces.

关键词

Keywords

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