光学学报, 2019, 39 (9): 0915002, 网络出版: 2019-09-09
基于断裂面特征点匹配的文物碎片重组方法 下载: 1005次
Reassembly Method of Cultural Relics Based on Feature Point Matching of Fracture Surface
机器视觉 碎片重组 特征点提取 协方差描述符 迭代最近点 machine vision fragment reassembly feature point extraction covariance descriptor iterative closest point
摘要
在计算机辅助文物虚拟复原过程中,针对现有复原方法匹配精度低、速度慢等问题,提出一种新的基于断裂面特征点匹配的文物碎片重组方法。利用改进的内部形状签名法提取碎片断裂面潜在特征点;计算特征点邻域几何特征的协方差矩阵,从而构建特征描述符;采用对数欧氏黎曼度量方法作为相似性度量准则,通过双向最近邻法获得初始点对集合,再利用典型相关分析法消除误匹配对得到最优匹配集;使用最小二乘法估算刚体变换矩阵将碎片粗对齐,再采用迭代最近点算法实现精确对齐,最终实现碎片重组。实验结果表明,本文算法相对传统算法特征点数量少,描述符简单,且稳健性强,有效提高了碎片重组的效率和准确性。
Abstract
Existing restoration methods perform virtual restoration of computer-aided cultural relics with low accuracy and speed. To address this issue, a new reassembly method of cultural relics based on feature Point matching of fracture surface is proposed. First, the improved internal shape signature method is used to extract potential feature points of fragment fracture surfaces. Then, the covariance matrix of geometric features of adjacent feature points is calculated to construct feature descriptors. The logarithmic Euclidean Riemann method is then used as the similarity measure criterion, and the initial point pair set is obtained based on the bidirectional nearest neighbor method. The optimal matching set is obtained by eliminating mismatching pairs based on the canonical correlation analysis method. Finally, the least square method is used to calculate the rigid body transformation matrix to align the fragments and the iterative closest point algorithm is used to achieve precise alignment, thereby realizing fragment reassembly. Experimental results show that the proposed algorithm has fewer feature points compared with traditional algorithms; the descriptor is simple and robust, which effectively improves the efficiency and accuracy of fragment reassembly.
胡佳贝, 周蓬勃, 耿国华, 张勇杰, 杨稳, 陆正杰. 基于断裂面特征点匹配的文物碎片重组方法[J]. 光学学报, 2019, 39(9): 0915002. Jiabei Hu, Pengbo Zhou, Guohua Geng, Yongjie Zhang, Wen Yang, Zhengjie Lu. Reassembly Method of Cultural Relics Based on Feature Point Matching of Fracture Surface[J]. Acta Optica Sinica, 2019, 39(9): 0915002.