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基于Morse-Smale拓扑特征的文物碎片拼接算法

袁洁 周明全 耿国华 张雨禾

袁洁, 周明全, 耿国华, 张雨禾. 基于Morse-Smale拓扑特征的文物碎片拼接算法. 自动化学报, 2018, 44(8): 1486-1495. doi: 10.16383/j.aas.2017.c160778
引用本文: 袁洁, 周明全, 耿国华, 张雨禾. 基于Morse-Smale拓扑特征的文物碎片拼接算法. 自动化学报, 2018, 44(8): 1486-1495. doi: 10.16383/j.aas.2017.c160778
YUAN Jie, ZHOU Ming-Quan, GENG Guo-Hua, ZHANG Yu-He. Automatic Reassembly of Fractured Fragments Using Morse Topological Features. ACTA AUTOMATICA SINICA, 2018, 44(8): 1486-1495. doi: 10.16383/j.aas.2017.c160778
Citation: YUAN Jie, ZHOU Ming-Quan, GENG Guo-Hua, ZHANG Yu-He. Automatic Reassembly of Fractured Fragments Using Morse Topological Features. ACTA AUTOMATICA SINICA, 2018, 44(8): 1486-1495. doi: 10.16383/j.aas.2017.c160778

基于Morse-Smale拓扑特征的文物碎片拼接算法

doi: 10.16383/j.aas.2017.c160778
基金项目: 

国家自然科学基金 61673319

陕西省产业创新链项目:秦汉都城虚拟修复建模及其增强现实展示应用示范工程 2016TZC-G-3-5

国家自然科学基金 61373117

高等学校博士学科点专项科研基金 20136101110019

详细信息
    作者简介:

    袁洁  西北大学信息科学与技术学院硕士研究生.2015年获得西北大学计算机科学与技术学士学位.主要研究方向为图形几何处理, 可视化技术.E-mail:yuanjie4920@163.com

    耿国华  西北大学信息科学与技术学院教授.主要研究方向为计算机图形图像处理, 可视化技术.E-mail:ghgeng@nwu.edu.cn

    张雨禾  西北大学信息科学与技术学院博士研究生.2012年获得西北大学计算机科学与技术学士学位.主要研究方向为图形几何处理, 可视化技术及3D打印技术.E-mail:zhangyuhe0601@126.com

    通讯作者:

    周明全  北京师范大学信息科学与技术学院教授.主要研究方向为虚拟现实与可视化技术, 智能信息处理, 数据库与知识库, 图形图像处理.本文通信作者.E-mail:mqzhou@bnu.edu.cn

Automatic Reassembly of Fractured Fragments Using Morse Topological Features

Funds: 

National Natural Science Foundation of China 61673319

Qinhan Metropolis Metropolitan Virtual Repair Modeling and Its Augmented Reality Display Application Demonstration Project 2016TZC-G-3-5

National Natural Science Foundation of China 61373117

Special Research Fund for the Doctoral Program of Higher Education 20136101110019

More Information
    Author Bio:

     Master student at the School of Information Science and Technology, Northwest University. She received her bachelor degree from Northwest University in 2015. Her research interest covers graphics geometry processing, and visualization technology

     Ph. D. Professor at the School of Information Science and Technology, Northwest University. Her research interest covers graphics image processing and visualization technology

     Ph. D. candidate at the School of Information Science and Technology, Northwest University. She received her bachelor degree from Northwest University in 2012. Her research interest covers graphics geometry processing, visualization technology, and 3D printing technology

    Corresponding author: ZHOU Ming-Quan  Professor at the School of Information Science and Technology, Beijing Normal University. His research interest covers virtual reality and visualization technology, intelligent information processing, database and knowledge base, graphics and image processing. Corresponding author of this paper
  • 摘要: 针对计算机辅助文物虚拟复原中由于破损文物断裂部位边缘受损而引起的轮廓线不能充分表示断裂面几何特征的问题,提出了一种基于断裂面拓扑特征的破碎文物自动拼接算法.首先,定义碎片模型顶点显著度指标函数,提取断裂面特征点,依据Morse-Smale复形理论构建并简化断裂面的几何拓扑图;然后,通过定义基准点与0值面,从而计算目标点的对应高度差值,将拓扑图中四边形曲面构造成为能完整表示断裂面几何特征的特征描述符,并根据凹凸互补性计算初始特征四边形匹配集的误差,筛选出最优匹配集;最后,采用四元组方法计算旋转、平移矩阵,利用穷举搜索法实现碎片的精确拼接.实验结果表明,该方法针对断裂部位边缘受损的破碎文物模型可获得较满意的拼接效果.
    1)  本文责任编委 刘成林
  • 图  1  本文方法步骤

    Fig.  1  Procedures for the method proposed in the paper

    图  2  顶点邻域关系图

    Fig.  2  Diagrams of vertex neighborhoods

    图  3  环状和孤立临界点

    Fig.  3  Diagrams of cyclic and solitary critical points

    图  4  路径点位选择

    Fig.  4  Paths selected by points

    图  5  特征线构成

    Fig.  5  Feature line composition

    图  6  顶点高度差值

    Fig.  6  Vertex height difference

    图  7  断裂面拓扑图

    Fig.  7  Topological diagram of fracture surface

    图  8  匹配集优化结果

    Fig.  8  Optimization results of matching set

    图  9  G10-26号俑部分邻接碎片拼接结果

    Fig.  9  Reassembly results of some adjacent fragments of Warriors G10-26

    图  10  G10-19号俑部分邻接碎片拼接结果

    Fig.  10  Reassembly results of some adjacent fragments of Warriors G10-19

    图  11  G10-23号俑部分邻接碎片拼接结果

    Fig.  11  Reassembly results of some adjacent fragments of Warriors G10-23

    图  12  G10-18号俑部分邻接碎片拼接结果

    Fig.  12  Reassembly results of some adjacent fragments of Warriors G10-18

    图  13  G10-36号俑部分邻接碎片拼接结果

    Fig.  13  Reassembly results of some adjacent fragments of Warriors G10-36

    图  14  G10-22号俑部分邻接碎片拼接结果

    Fig.  14  Reassembly results of some adjacent fragments of Warriors G10-22

    图  15  薄壁碎片断裂面特征提取图

    Fig.  15  Feature extraction in thin fragments

    图  16  传统算法实验结果

    Fig.  16  Experimental results of traditional methods

    表  1  兵马俑碎片实验数据

    Table  1  Experimental datas of the Terracotta Army fragments

    编号碎片数量网格总数特征四边形总数匹配精度
    G10-187674 4772530.924
    G10-26238 602320.929
    G10-366591 6411910.961
    G10-225451 7501030.975
    G10-19394 276930.924
    G10-23312 147840.896
    下载: 导出CSV

    表  2  本文算法运行时间

    Table  2  Execute times of the proposed algorithm

    编号T1 (s)T2 (s)T3 (s)总时间(s)
    G10-1868.46117.4367.24693.143
    G10-3653.53416.9906.12876.652
    G10-2230.15712.6314.02146.809
    G10-267.0653.5180.98111.564
    G10-1917.9136.3492.06526.327
    G10-2319.2547.5212.73129.506
    下载: 导出CSV
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  • 收稿日期:  2016-11-21
  • 录用日期:  2017-05-22
  • 刊出日期:  2018-08-20

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