CAD mesh model simplification with assembly features preservation

This paper aims to investigate a CAD mesh model simplification method with assembly features preservation, in order to satisfy the requirement of assembly field for the information of 3D model. The proposed method simplifies a CAD mesh model as follows. Firstly, the notion of ＂conjugation＂ is incorporated into the definition of assembly features, with the purpose of benefitting the downstream applications such as assembly features recognition and preservation. Subsequently, the attributed adjacency graphs （AAGs） of the region- level-represented parts are established. The assembly features are automatically recognized by searching for conjugated subgraphs of every two AAGs based on subgraph isomorphism algorithm. In order to improve the efficiency of assembly features recognition, the characteristics of conjugated subgraphs are adopted to initialize the mapping matrix, and the ＂verifying while matching strategy＂ is used to verify the validity of every two newly founded vertices which are correspondingly matched. Then, simplified CAD mesh model with assembly features preserved is constructed after suppressing the common form features. The method is applied successfully to simplify the CAD mesh model with assembly features well preserved. Moreover, the tradeoff between the cost of time for conjugated subgraphs matching and the complexity of the to-be-matched parts is proven to be almost linear.     

An approach to automated decomposition of volumetric mesh

Mesh decomposition is critical for analyzing, understanding, editing and reusing of mesh models. Although there are many methods for mesh decomposition, most utilize only triangular meshes. In this paper, we present an automated method for decomposing a volumetric mesh into semantic components. Our method consists of three parts. First, the outer surface mesh of the volumetric mesh is decomposed into semantic features by applying existing surface mesh segmentation and feature recognition techniques. Then, for each recognized feature, its outer boundary lines are identified, and the corresponding splitter element groups are setup accordingly. The inner volumetric elements of the feature are then obtained based on the established splitter element groups. Finally, each splitter element group is decomposed into two parts using the graph cut algorithm; each group completely belongs to one feature adjacent to the splitter element group. In our graph cut algorithm, the weights of the edges in the dual graph are calculated based on the electric field, which is generated using the vertices of the boundary lines of the features. Experiments on both tetrahedral and hexahedral meshes demonstrate the effectiveness of our method.     

空心涡轮叶片CAD模型与CT切片模型的配准研究

针对利用三维CT设备对空心涡轮叶片进行无损检测时存在的定位偏差问题,提出了一种基于三维数字样品的图像模型匹配方法,这对于充分利用有关叶片的先验知识,建立叶片无损检测专家系统具有重要的意义。该方法首先通过图像模型的一阶矩,进行灰度重心匹配;然后将叶片的图像模型与其CAD理论模型之间的残差平方和定义为优化目标函数,采用黄金分割方法搜索其极小值;同时利用叶片上预先指定的结构特征,求出空间变换的位置匹配参数和角度匹配参数,最后根据匹配参数精确地建立起从叶片CT切片模型到其CAD理论模型的空间变换。仿真结果表明:该方法不依赖于初始参数的选取,可达到满意的精度。     

基于SVD-ICP算法配准CT切片重构模型与CAD模型

利用三维CT设备对工业产品进行无损检测时,由于存在定位偏差问题,CT切片重构模型和CAD理论模型会存在微小的偏差,因此需要将这二者进行匹配。文章首先从重构模型的表面任选一部分点作为初始点集,通过SVD-ICP算法求取最近邻点集,反复迭代直至达到迭代停止条件。这样可以确定出最优旋转矩阵和平移向量,从而将两个模型匹配起来。在求取最近邻点的过程中利用线性八叉树加快速度。仿真实验表明:利用该方法匹配两个模型可以达到比较满意的效果。     

一种精度可控的CAD网格模型及轻量化算法的研究

针对现有三维CAD系统中,CAD网格模型显示精度固定,难以动态调整以及细分后网格数量过多等瓶颈问题,在原始模型基础上,结合CAD模型中边、面等几何与拓扑信息,提出了一种精度可控的三维CAD网格模型.根据该模型的结构特点,采用曲面内部插值与边界曲线插值相结合的轻量化分类细分算法来实现模型精度调整,并有效控制细分后的网格数量,可满足三维CAD系统对模型精度可控、减少网格数量的需要.     

A blind watermarking algorithm for 3D mesh models based on vertex curvature

We propose a robust blind watermarking algorithm for three-dimensional （3D） mesh models based on vertex cur-vature to maintain good robustness and improve visual masking in 3D mesh models. In the embedding process, by using the local window of vertex, the root mean square curvature is calculated for every vertex of the 3D mesh model and an ordered set of fluctuation values is obtained. According to the ordered fluctuation values, the vertices are separated into bins. In each bin the fluctuation values are normalized. Finally, the mean of the root mean square curvature fluctuation values of the vertices in each bin is modulated to embed watermark information. In watermark detection, the algorithm uses a blind watermark extraction technique to extract the watermark information. The experimental results show that the algorithm has a very good performance for visual masking of the embedded model and that it can resist a variety of common attacks such as vertex rearrangement, rotation, trans-lating, uniform scaling, noise, smoothing, quantization, and simplification.     

基于混合模型的虚拟装配关键技术研究

针对虚拟装配中采用多边形网格模型引起的组件定位困难和碰撞检测精度低等问题,提出一种采用精确几何模型及其对应的多边形网格模型的混合模型作为底层数据,支持精确装配的虚拟装配系统构造方法,并基于Parasolid和Vir-tools平台进行了实现。基于混合模型的碰撞检测能根据计算精度和时间要求自适应求解,在速度快的同时,满足高精度碰撞检测要求;基于混合模型的组件装配,采用离散采样点定义装配路径,通过装配几何约束交互式定义限制组件的运动范围,通过自由度规约、装配约束求解实现了零部件精确定位,通过四元数插值实现装配路径中零部件位姿的平滑过渡,能满足高精度的装配要求。该方法已经在开发的多个系统中得到验证和应用。     

面向模型验证的空间网格面的染色及显示技术

针对工程分析用的网格模型,以图论中的拓扑图为基础提出了一种空间网格面的染色算法.该算法对可平面图几何模型、非可平面图几何模型以及奇异几何模型均可染色.利用染色结果,给出了在AutoCAD平台上编程显示染色几何模型的方法.多项工程应用表明,该染色算法可靠、适应性强、染色效果好,可用于几何分析模型的验证.     

Automatic analysis of 3D low dose CT images for early diagnosis of lung cancer

Our long term research goal is to develop a fully automated, image-based diagnostic system for early diagnosis of pulmonary nodules that may lead to lung cancer. This paper focuses on monitoring the development of lung nodules detected in successive chest low dose (LD) CT scans of a patient. We propose a new methodology for 3D LDCT data registration which is non-rigid and involves two steps: (i) global target-to-prototype alignment of one scan to another using the learned prior appearance model followed by (ii) local alignment in order to correct for intricate relative deformations. After equalizing signals for two subsequent chest scans, visual appearance of these chest images is described using a Markov-Gibbs random field (MGRF) model with multiple pairwise interaction. An affine transformation that globally registers a target to a prototype is estimated by the gradient ascent-based maximization of a special Gibbs energy function. To get an accurate visual appearance model, we developed a new approach to automatic selection of most characteristic second-order cliques that describe pairwise interactions in the LDCT data. To handle local deformations, we displace each voxel of the target over evolving closed equi-spaced surfaces (iso-surfaces) to closely match the prototype. The evolution of the iso-surfaces is guided by a speed function in the directions that minimize distances between the corresponding voxel pairs on the iso-surfaces in both the data sets. Preliminary results on the 135 LDCT data sets from 27 patients show that the proposed accurate registration could lead to precise diagnosis and identification of the development of the detected pulmonary nodules.     

Automatic mesh generation and modification techniques for mixed quadrilateral and hexahedral element meshes of non-manifold models

A typical geometric model usually consists of both solid sections and thin-walled sections. Through using a suitable dimensional reduction algorithm, the model can be reduced to a non-manifold model consisting of solid portions and two-dimensional portions which represent the mid-surfaces of the thin-walled sections. It is desirable to mesh the solid entities using three-dimensional elements and the surface entities using two-dimensional elements. This paper proposes a robust scheme to automatically generate such a mesh of mixed two-dimensional and three-dimensional elements. It also ensures that the mesh is conforming at the interface of the non-manifold geometries. Different classes of problems are identified and their corresponding solutions are presented.     

Analysis of assembly operations’ difficulty using enhanced expert high-level colored fuzzy Petri net model

Majority of the products can be assembled in several ways that means the same final product can be realized by different sequences of assembly operations. Different degree of difficulty is associated with each sequence of assembly operation and such difficulties are caused by the different mechanical constraints forced by the different sequences of operations. In the past, few notable attempts have been made to represent and enumerate the degree of difficulty associated with an assembly sequence (in the form of triangular fuzzy number) by using the concept of assembly graph. However, such representation schemes do not possess the capabilities to model the user's reasoning and preferences. In this research, an intelligent Petri net model that combines the abilities of modelling, planning and performance evaluation for assembly operation is presented. This modelling tool can represent the issues concerning degree of difficulty associated with assembly sequences. The proposed mechanism is enhanced expert high-level colored fuzzy Petri net (EEHLCFPN) that is a hybrid of knowledge-based system and colored Petri net. An example encompassing assembly of subassemblies is considered to efficiently delineate the modelling capabilities of proposed hybrid petri net model.     

Removing local irregularities of triangular meshes with highlight line models

The highlight line model is a powerful tool in assessing the quality of a surface. It increases the flexibility of an interactive design environment. In this paper, a method to generate a highlight line model on an arbitrary triangular mesh is presented. Based on the highlight line model, a technique to remove local shape irregularities of a triangular mesh is then presented. The shape modification is done by solving a minimization problem and performing an iterative procedure. The new technique improves not only the shape quality of the mesh surface, but also the shape of the highlight line model. It provides an intuitive and yet suitable method for locally optimizing the shape of a triangular mesh. Supported by National Science Foundation of China (Grant Nos. 60533070, 60625202), National Basic Research Program of China (Grant No. 2004CB719400), National High-Tech Research & Development Program of China (Grant No. 2007AA040401), Fok Ying Tung Education Foundation (Grant No. 111070), National Science Foundation of USA (Grant Nos. DMI-0422126, DMS-0310645), and Kentucky Science & Technology Corporation (Grant No. COMM-Fund-712)     

3D模型LOD算法的研究及其OpenGL实现

3D模型LOD技术是计算机图形学的一个重要研究课题,简述了3D模型LOD技术的基本原理并分析和探讨了各类LOD算法。为了克服LOD算法在使用中的局限性,提出了一种3D模型LOD算法,并通过OpenGL编程进行了实现,运行的结果表明此3D模型LOD算法是可行和高效的。     

Comparison of ANN approach with 2D and 3D hydrodynamic models for simulating estuary water stage

Accurately predicting tidal levels, including tidal and freshwater discharge effects, is important for human activities in estuaries. The traditional harmonic analysis method and numerical modeling are usually adopted to simulate and predict estuary water stages. This study applied artificial neural networks (ANNs) as an alternative modeling approach to simulate the water stage time-series of the Danshui River estuary in northern Taiwan. We compared this approach with vertical (laterally averaged) 2D and 3D hydrodynamic models. Five ANN models were constructed to simulate the water stage time-series at the Shizi Tou, Taipei Bridge, Rukuoyan, Xinhai Bridge, and Zhongzheng Bridge locations along the Danshui River estuary. ANN models can preserve nonlinear characteristics between input and output variables and are superior to physical-based hydrodynamic models during the training phase. The simulated results reveal that the vertical 2D and 3D hydrodynamic models could not capture the observed water stages during an input of high freshwater discharge from upstream boundaries, while the ANN could match the observed water stage. However, during the testing phase, the ANN approach was slightly inferior to the 2D and 3D models at the Xinhai Bridge, Zhongzheng Bridge, and Rukouyan locations. Our results show that the ANN was able to predict the water stage time-series with reasonable accuracy, suggesting that ANNs can be a valuable tool for estuarine management.     

Hierarchical segmentation and identification of thoracic vertebra using learning-based edge detection and coarse-to-fine deformable model

Precise segmentation and identification of thoracic vertebrae is important for many medical imaging applications though it remains challenging due to the vertebra’s complex shape and varied neighboring structures. In this paper, a new method based on learned bone-structure edge detectors and a coarse-to-fine deformable surface model is proposed to segment and identify vertebrae in 3D CT thoracic images. In the training stage, a discriminative classifier for object-specific edge detection is trained using steerable features and statistical shape models for 12 thoracic vertebrae are also learned. For the run-time testing, we design a new coarse-to-fine, two-stage segmentation strategy: subregions of a vertebra first deform together as a group; then vertebra mesh vertices in a smaller neighborhood move group-wise to progressively drive the deformable model towards edge response maps by optimizing a probability cost function. In this manner, the smoothness and topology of vertebrae shapes are guaranteed. This algorithm performs successfully with reliable mean point-to-surface errors 0.95 ± 0.91 mm on 40 volumes. Consequently a vertebra identification scheme is also proposed via mean surface mesh matching. We achieve a success rate of 73.1% using a single vertebra, and over 95% for 8 or more vertebra which is comparable or slightly better than state-of-the-art [5].     

Range image segmentation using local approximation of scan lines with application to CAD model acquisition

Abstract. Automatic acquisition of CAD models from existing objects requires accurate extraction of geometric and topological information from the input data. This paper presents a range image segmentation method based on local approximation of scan lines. The method employs edge models that are capable of detecting noise pixels as well as position and orientation discontinuities of varying strengths. Region-based techniques are then used to achieve a complete segmentation. Finally, a geometric representation of the scene, in the form of a surface CAD model, is produced. Experimental results on a large number of real range images acquired by different range sensors demonstrate the efficiency and robustness of the method. Received: 1 August 2000 / Accepted: 23 January 2002 Correspondence to: I. Khalifa