基于工业CT图像的自适应三维网格模型重建  

Adaptive 3D Mesh Model Reconstruction Based on Industrial CT Images

作　　者：黎玲 金恒 刘杰[1,3] 龙超 何云勇 李中明 段黎明[1,2] Li Ling;Jin Heng;Liu Jie;Long Chao;He Yunyong;Li Zhongming;Duan Liming(ICT Research Center,Key Laboratory of Optoelectronic Technology&Systems,Ministry of Education,Chongqing University,Chongqing 400044,China;College of Mechanical and Vehicle Engineering,Chongqing University,Chongqing 400044,China;College of Optoelectronic Engineering,Chongqing University,Chongqing 400044,China)

机构地区：[1]重庆大学光电技术及系统教育部重点实验室ICT研究中心,重庆400044 [2]重庆大学机械与运载工程学院,重庆400044 [3]重庆大学光电工程学院,重庆400044

出　　处：《光学学报》2023年第3期235-244,共10页Acta Optica Sinica

基　　金：国家自然科学基金(52075057)。

摘　　要：针对X射线扫描得到的工业CT图像重建三角网格模型存在尖锐特征丢失、狭长三角形和三角面片数量多等问题,提出一种自适应三维网格模型重建算法。首先对图像进行预处理;其次采用八叉树结构确定体元;然后利用二次误差函数(QEF)构建自适应八叉树;最后剖分四边形生成三角网格。使用立方体数据和两组实际扫描的CT数据对所提算法的性能进行验证分析,实验结果表明:所提算法在简化网格的同时仍能保持物体的尖锐特征,减少了狭长三角形的数量。利用所提算法生成三角网格模型的简化率可达90%,简化后网格质量大于0.3的三角网格平均占比为99%,有效地提高了由工业CT图像重建三角网格模型的质量。Objective As a typical numerical representation of geometric models,the triangular mesh is widely used in additive manufacturing,inverse design,and finite element analysis.The triangular mesh model is directly reconstructed based on industrial CT images,which allows for the reconstruction of 3D representations of parts with complicated internal cavity structures.However,current algorithms for reconstructing triangular mesh models based on industrial CT images,for example,marching cube(MC)algorithm,have problems such as loss of sharp features,many longnarrow triangles,and a large number of triangular surfaces.In this paper,we propose an adaptive 3D mesh model reconstruction method to simultaneously address these issues while improving the quality of the reconstructed triangular mesh model from industrial CT images.Methods First,a bilateral filter and an OTSU algorithm are utilized to preprocess industrial CT images,so as to denoise and determine the value of the isosurface.Second,an octree structure is used to confirm the voxels;the octree is created topdown recursively,while nonboundary voxels are deleted to save storage space.The quadratic error function(QEF)is then applied to each boundary voxel of the octree to produce a feature point,and the octree is simplified by merging the feature points from the bottom up.Third,a quadrilateral formed by four adjacent feature points is divided into two triangular meshes.In order to validate the performance of the proposed algorithm,experiments are performed using a cubic dataset and two groups of real industrial CT images.Results and Discussions To begin with,a cubic dataset with no noise is utilized and reconstructed using the MC algorithm and the approach proposed in this study,as shown in Fig.7.Sharp features including angles are lost by the MC algorithm[Fig.7(a)].The approach in this article not only generates the cube's edges but also a smaller triangular mesh to represent sharper features such as angles[Fig.7(b)].Next,in order to demonstrate the algorithm's simplifi

关 键 词：X射线光学 工业CT图像 三维重建 三角网格 自适应八叉树 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]