A single solution method for converting 2D assembly drawings to 3D part drawings

Although solid models play a central role in modern CAD systems, 2D CAD systems are still commonly used for designing products without complex curved faces. Therefore, an important task is to convert 2D drawings to solid models, and this is usually carried out manually even in present CAD systems. Many methods have been proposed to automatically convert orthographic part drawings of solid objects to solid models. Unfortunately, products are usually drawn as 2D assembly drawings, and therefore, these methods cannot be applied. A further problem is the difficult and time-consuming task of decomposing 2D assembly drawings into 2D part drawings. In previous work, the authors proposed a method to automatically decompose 2D assembly drawings into 3D part drawings, from which 2D part drawings can be easily generated. However, one problem with the proposed method was that the number of solutions could easily explode if the 2D assembly drawings became complex. Building on this work, here we describe a new method to automatically convert 2D assembly drawings to 3D part drawings, generating a unique solution for designers regardless of the complexity of the original 2D assembly drawings. The only requirement for the approach is that the assembly drawings consist of standard parts such as bars and plates. In 2D assembly drawings, the dimensions, part numbers and parts lists are usually drawn, and the proposed method utilizes these to obtain a unique solution.     

Solid model reconstruction from engineering paper drawings using Genetic Algorithms

The wide applications of CAD/CAM technologies have promoted the development and application of many advanced technologies, such as digital manufacturing, rapid prototyping, enterprise resources planning, computer integrated manufacturing, concurrent engineering, virtual reality, and mass customization. These advanced technologies all need to be supported by three-dimensional (3D) solid models of products. Most enterprises, however, still organize their production using 2D paper drawings, which makes difficulties for the application of these advanced technologies. It is needed to convert engineering paper drawings into 3D solid models for applications. Based on holo-extraction of information from paper drawings, this paper develops a systematic 3D reconstruction method, which simulates an experienced human designer's thinking mode in transforming inaccurate outlines with inaccurate projection relationships in 2D drawings into 3D image, with the aid of Genetic Algorithms.     

Reconstruction of curved solids from engineering drawings

This paper presents a new approach for reconstructing solids with planar, quadric and toroidal surfaces from three-view engineering drawings. By applying geometric theory to 3-D reconstruction, our method is able to remove restrictions placed on the axes of curved surfaces by existing methods. The main feature of our algorithm is that it combines the geometric properties of conics with affine properties to recover a wider range of 3-D edges. First, the algorithm determines the type of each 3-D candidate conic edge based on its projections in three orthographic views, and then generates that candidate edge using the conjugate diameter method. This step produces a wire-frame model that contains all candidate vertices and candidate edges. Next, a maximum turning angle method is developed to find all the candidate faces in the wire-frame model. Finally, a general and efficient searching technique is proposed for finding valid solids from the candidate faces; the technique greatly reduces the searching space and the backtracking incidents. Several examples are given to demonstrate the efficiency and capability of the proposed algorithm.     

Solid reconstruction using recognition of quadric surfaces from orthographic views

The reconstruction of 3D objects from 2D orthographic views is crucial for maintaining and further developing existing product designs. A B-rep oriented method for reconstructing curved objects from three orthographic views is presented by employing a hybrid wire-frame in place of an intermediate wire-frame. The Link-Relation Graph (LRG) is introduced as a multi-graph representation of orthographic views, and quadric surface features (QSFs) are defined by special basic patterns of LRG as well as aggregation rules. By hint-based pattern matching in the LRGs of three orthographic views in an order of priority, the corresponding QSFs are recognized, and the geometry and topology of quadric surfaces are recovered simultaneously. This method can handle objects with interacting quadric surfaces and avoids the combinatorial search for tracing all the quadric surfaces in an intermediate wire-frame by the existing methods. Several examples are provided.     

Holo-extraction of information from paper drawings for 3D reconstruction

The research on the conversion from 2D paper drawings to 3D computer feature models has been stuck in low-level coding. One of the reasons for it is that the three phases of understanding process has been isolated and people have been doing their research on only one of the phases since the whole conversion is very complicated and more difficult. For instance, the vectorization methods for the first phase were developed only for getting straight lines, arcs, circles, etc. so that much information contained in the drawing has been lost after the vectorization. This paper develops a holo-extraction method of information from paper drawings, the networks of single closed regions (SCRs), which can not only provide a unified base for recognizing both the annotations and the outlines of projections of parts, but also build the holo-relationships among SCRs so that it is convenient to extract lexical, syntactic and semantic information in the subsequent phases for 3D reconstruction.     

Sparse-pixel recognition of primitives in engineering drawings

Recognition of primitives in technical drawings is the first stage in their higher level interpretation. It calls for processing of voluminous scanned raster files. This is a difficult task if each pixel must be addressed at least once, as required by Hough transform or thinning-based methods. This work presents a set of algorithms that recognize drawing primitives by examining the raster file sparsely. Bars (straight line segments), arcs, and arrowheads are identified by the orthogonal zig-zag, perpendicular Bisector tracing, and self-supervised arrowhead recognition algorithms, respectively. The common feature of these algorithms is that rather than applying massive pixel addressing, they recognize the sought primitives by screening a carefully selected sample of the image and focusing attention on identified key areas. The sparse-pixel-based algorithms yield high quality recognition, as demonstrated on a sample of engineering drawings.     

The extraction of line-structured data from engineering drawings

The aim of this research is to allow automatic conversion of an engineering drawing into a form similar to that produced by a computer-aided draughting system. Progress towards generating a representation of the drawing as a set of line segments and interpreted characters is described, within an overall strategy for planning the sampling of the image and the application of analysis algorithms. Examples of results so far achieved on a real drawing are shown.     

Reconstruction of 3D interacting solids of revolution from 2D orthographic views

3D CAD is replacing 2D CAD to improve efficiency of product design and manufacturing. Therefore, converting legacy 2D drawings into 3D solid models is required. CSG based approaches reconstruct solid models from orthographic views more efficiently than traditional B-rep based approaches. A major limitation of CSG based approaches has been the limited domain of objects that can be handled. This paper aims at extending the capabilities of CSG based approaches by proposing a hint-based recognition of interacting solids of revolution. This approach can handle interacting solids of revolution as well as isolated solids of revolution.     

Sensitivity analysis of structural response uncertainty propagation using evidence theory

Sensitivity analysis for the quantified uncertainty in evidence theory is developed. In reliability quantification, classical probabilistic analysis has been a popular approach in many engineering disciplines. However, when we cannot obtain sufficient data to construct probability distributions in a large-complex system, the classical probability methodology may not be appropriate to quantify the uncertainty. Evidence theory, also called Dempster–Shafer Theory, has the potential to quantify aleatory (random) and epistemic (subjective) uncertainties because it can directly handle insufficient data and incomplete knowledge situations. In this paper, interval information is assumed for the best representation of imprecise information, and the sensitivity analysis of plausibility in evidence theory is analytically derived with respect to expert opinions and structural parameters. The results from the sensitivity analysis are expected to be very useful in finding the major contributors for quantified uncertainty and also in redesigning the structural system for risk minimization.     

Reconstruction of intersecting curved solids from 2D orthographic views

This paper presents a new approach to reconstruct curved solids composed of elementary volumes intersecting with one another from three-view engineering drawings. Intersection curves arising from two intersecting curved surfaces are mostly higher order spatial curves, which cannot be described exactly by 2D orthographic projections and normally represented as smooth curves passing through several key points or even simplified as arcs or lines. Approximated sketches of higher order intersection curves in 2D views result in the invalidation of existing methods that need the exact projection information as input. Based on some heuristic hints, our method is able to recover the complete and correct half-profiles of the intersecting elementary volumes using the least traces left by them, which ensure the correctness of solution solids constructed finally. Several examples are provided to show the validation of the described method.     

Recognition of digital curves scanned from paper drawings using genetic algorithms

After analyzing the existing methods, based on holo-extraction method of information, this paper develops a recognition method of digital curves scanned from paper drawings for subsequent pattern recognition and 3D reconstruction. This method is first to construct the networks of single closed region (SCRs) of black pixels with all the information about both segments and their linking points, to classify all the digital contours represented by SCRs into three types: straight-line segments, circular arcs, and combined lines, and then to decompose the combined lines into least basic sub-lines or segments (straight-line segments or circular arcs) with least fitting errors using genetic algorithms with adaptive probabilities of crossover and mutation and to determine their relationships (intersecting or being tangential to each other). It is verified that the recognition method based on the networks of SCRs and the genetic algorithm is feasible and efficient. This method and its software prototype can be used as a base for further work on subsequent engineering drawing understanding and 3D reconstruction.     

Minimizing neighborhood evidential decision error for feature evaluation and selection based on evidence theory

Feature selection is an important preprocessing step in pattern recognition and machine learning, and feature evaluation arises as key issues in the construction of feature selection algorithms. In this study, we introduce a new concept of neighborhood evidential decision error to evaluate the quality of candidate features and construct a greedy forward algorithm for feature selection. This technique considers both the Bayes error rate of classification and spatial information of samples in the decision boundary regions.Within the decision boundary regions, each sample x_i in the neighborhood of x provides a piece of evidence reflecting the decision of x so as to separate the decision boundary regions into two subsets: recognizable and misclassified regions. The percentage of misclassified samples is viewed as the Bayes error rate of classification in the corresponding feature subspaces. By minimizing the neighborhood evidential decision error (i.e., Bayes error rate), the optimal feature subsets of raw data set can be selected. Some numerical experiments were conducted to validate the proposed technique by using nine UCI classification datasets. The experimental results showed that this technique is effective in most of the cases, and is insensitive to the size of neighborhood comparing with other feature evaluation functions such as the neighborhood dependency.     

基于独立环路组合的多面体视图三维重建

提出了一种基于平面独立环路组合的多面体视图三维重建完整算法，即先把三视图中的每个视图分解成一个个独立的不可再分的平面独立环路，然后从三面视图的三个环路组中逐个取出可能的环路组合按构造实心体几何方法（CSG）构成局部实心体模型，最后将局部实心体模型组合成整体实心体模型。已按上述算法编制出了能在Auto CAD图形系统中使用的实用软件。     

基于D-S证据理论的邮件筛选方法

针对目前色情邮件筛选中只针对邮件的文本内容进行过滤的不足，考虑邮件的文本和附件中所携带的图片信息，提出了一种基于证据理论的色情邮件的筛选方法。新方法分别使用一个色情图片检测器和一个文本分类器分别对邮件的附件及其内容进行初判别，然后将两个检测器的判别结果作为证据，使用D-S理论融合两个检测器的输出得到最后的判别结果。实验表明，该方法能有效地提高色情邮件的识别率。     

Frontal geometry from sketches of engineering objects: is line labelling necessary?

A tool which can quickly interpret line drawings (with hidden lines removed) of engineering objects as boundary representation CAD models would be of significant benefit in the process of engineering design. Inflation of the drawing to produce a frontal geometry, a geometric realisation of that part of the object visible in the drawing, is an important stage of this process.Previous methods of producing frontal geometries have relied on the technique of line labelling (labelling edges as convex, concave or occluding). Although restricted subsets of the line-labelling problem have known solutions, reliable methods have not been found for the general line-labelling problem, and traditional methods, when adapted to drawings with non-trihedral junctions, are unacceptably slow.Many other papers assume that line labelling is an essential step. Here, we show this is not necessarily true, and that comparable results can be obtained by a novel alternative approach. Firstly, we consider what outputs from line labelling are essential to the production of frontal geometry. Secondly, we investigate by what other means these outputs can be produced.Our work indicates that the only essential output from line labelling for frontal geometry is the determination of which T-junctions in a drawing are occluding and which are non-occluding. This information is required for inflation, and also for detection of symmetry and for constructing hidden topology.Thus, we propose and analyse a new method which, in the absence of line labels, simultaneously inflates a drawing to produce the frontal geometry and attempts to determine whether each T-junction is occluding or not. For drawings of objects with holes or pockets, and for cases where line labelling is particularly unreliable, our new method can provide a better alternative.     

基于D-S证据理论的多源图像分割算法

针对多源图像分割问题,提出了一种可靠的分割算法.采用被污染的高斯分布描述待分割图像,MRF模型描述分割图像的先验分布,并利用D-S证据理论融合多源数据的不确定性,依据置信度最大的原则,确定多源图像数据的分割标记类别.用仿真图像和多源遥感图像的分割结果,证明了该算法提供了更准确、可靠的分割结果.     

Research on intelligence recognition and reconstruction of engineering graph

In the paper, the authors put forward a regulation-based expert system which is used in auto-recognition and reconstruction of engineering graph. It consists of four parts-dynamic fact library, static regulation h'brary,inference control and 3D reconstruction. it discribles the knowledge and regulations to reeongnize engineering graph with regulation- expressing method, and sets up the inference mechanism according to its recognition thoughts. At last, it introduces recognition results of 3D reconstruction with AutoCAD.     

Reconstruction of 3D Object Models from Vectorised Engineering Drawings

In this paper, the problem of 3D-object model reconstruction from engineering drawing projections is analysed, and its main stages are shown. Image vectorisation and entity recognition is mentioned briefly, the main focus being editing or the parameterisation of vectorised drawings and 3D object model reconstruction from vectorised ED projections. Vectorised drawing, as a rule, do not exactly correspond to sizes and other features (touching, parallelity, perpendicularly, symmetry, collinearity, etc.) being available on the initial drawing, and this ED vector model is not suitable for direct use in CAD systems. That is why the parameterisation stage is introduced and considered in detail. An algorithm for 3D-object reconstruction from the vectorised and parameterised drawing is proposed. The algorithm is based on the detection of volumetric solid-state object components (primitives), and performing theoretic-set operations with the components. Practical experience in realising these stages is shown. Received: 23 April 1999, Received in revised form: 29 November 2000, Accepted: 07 December 2000     

基于模糊证据理论的水质环境状态估计

从信息融合的角度，将湖泊水质环境多因子综合评价过程看成是一个多源数据融合处理与状态估计过程，提出基于相似度的模糊证据理论，评估湖泊水体富营养状况．通过引入模糊集合的相似度，一方面，确定模糊焦元的权值，并修改证据模型；另一方面，确定模糊焦元对类别焦元的信任函数的贡献因子，并建立状态估计与评价模型，使其能够处理湖泊水体富营养状况的突发性带来的某些焦点元素的显著变化问题．对太湖水体富营养状况的评估做了实证分析，并与营养状态指数评价方法进行比较，结果一致，说明基于相似度的模糊证据理论的估计方法可行．     

一种有效的基于证据理论的离线签名识别方法

提出了一种有效的基于证据理论的离线签名识别方法。从签名图像的3种信息载体中提取出4种特征,利用所提取的4种特征分别构造基于证据理论的k-NN分类器对签名图像进行初步识别,将各k-NN分类器的输出作为证据,用改进的证据理论合成公式融合不同分类器的输出得到最终识别结果。结果表明：该识别方法能有效地提高离线签名的识别率。