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作 者:王莹[1,2] 刘鹏欢 陈雅鑫 王旭粲 李巍 周强[3] 罗宏杰[4] WANG Ying;LIU Penghuan;CHEN Yaxin;WANG Xucan;LI Wei;ZHOU Qiang;LUO Hongjie(School of Materials Science and Engineering(School of Conservation Science&Technology for Cultural Heritage),Shaanxi University of Science&Technology,Xi’an 710021,China;Key Laboratory of Materials&Technology for Underground Cultural Heritage Conservation,Ministry of Education,Shaanxi University of Science&Technology,Xi’an 710021,China;School of Electrical and Control Engineering,Shaanxi University of Science&Technology,Xi’an 710021,China;Key Laboratory of Silicate Cultural Relics Conservation,Ministry of Education,Shanghai University,Shanghai 200444,China)
机构地区:[1]陕西科技大学材料科学与工程学院(文物保护材料与技术学院),陕西西安710021 [2]陕西科技大学地下文物保护材料与技术教育部重点实验室,陕西西安710021 [3]陕西科技大学电气与控制工程学院,陕西西安710021 [4]上海大学硅酸盐质文物保护教育部重点实验室,上海200444
出 处:《西北大学学报(自然科学版)》2025年第1期118-128,共11页Journal of Northwest University(Natural Science Edition)
基 金:国家自然科学基金(201012279);硅酸盐质文物保护教育部重点实验室(上海大学)开放课题(SCRC2024KF04TS);陕西省地下文物保护利用协同创新中心项目(22JY008)。
摘 要:古陶瓷碎片轮廓线特征作为文物数字化修复的主要依据之一,能够直接影响文物原真性复原的质量和效率。针对古陶瓷碎片胎体较薄、形状不规则且点云数据量大而导致轮廓线提取的精度低、耗时长等问题,提出了一种基于邻域点集稠密度的古陶瓷碎片轮廓线提取算法。首先,采用有向包围盒(OBB)中心平面平行切平面方式,将碎片进行切片处理,实现对点云的分层处理和数据简化;其次,根据轮廓点和非轮廓点处邻域点集稠密度不同这个规律,将邻域点集稠密度特征与随机采样一致性(RANSAC)算法相结合,实现对碎片轮廓线的精确和快速提取;最后,构造空间分类平面,并依据空间位置的约束关系,实现对碎片断裂面和非断裂面轮廓线的分类。实验结果表明,在百万级数据规模的古陶瓷碎片轮廓线提取方面,算法运行时间可控制在15~25 s,并且轮廓线提取的准确性可达78.3%,具有较高的准确性和完整性,能够为古陶瓷文物数字化修复提供技术依据。The contour features of ancient ceramic fragments can directly affect the quality and efficiency of the restoration of cultural relics.In order to solve the problems of low precision and time-consuming in contour extraction due to the thin body,irregular shape and large amount of point cloud data of ancient ceramic fragments,a contour extraction algorithm of ancient ceramic fragments based on the density of neighborhood point set is proposed.Firstly,the Oriented Bounding Box(OBB)center plane parallel cutting plane is used to slice the fragments for realizing the layered processing and data simplification of the point cloud.Secondly,according to the law that the density of neighborhood points at contour points and non-contour points is different,the density feature of neighborhood point set is combined with the Random Sampling Consensus(RANSAC)algorithm to achieve accurate and fast extraction of fragment contours.Finally,construct the space classification plane and classify the fracture surface and non-fracture surface contours based on spatial positional constraints.The experimental results show that the running time of the algorithm can be controlled within 15~25 seconds,and the accuracy of contour extraction can reach 78.3%,with high accuracy and integrity,which can provide technical basis for digital restoration of ancient ceramic cultural relics.
关 键 词:古陶瓷碎片轮廓线 点云切片 邻域点集稠密度 随机采样一致性算法
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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