A complete system for the intelligent interpretation of engineering drawings

Converting paper-based engineering drawings into CAD model files is a tedious process. Therefore, automating the conversion of such drawings represents tremendous time and labor savings. We present a complete system which interprets such 2D paper-based engineering drawings, and outputs 3D models that can be displayed as wireframes. The system performs the detection of dimension sets, the extraction of object lines, and the assembly of 3D objects from the extracted object lines. A knowledge-based method is used to remove dimension sets and text from ANSI engineering drawings, a graphics recognition procedure is used to extract complete object lines, and an evidential rule-based method is utilized to identify view relationships. While these methods are the subject of several of our previous papers, this paper focuses on the 3D interpretation of the object. This is accomplished using a technique based on evidential reasoning and a wide range of rules and heuristics. The system is limited to the interpretation of objects composed of planar, spherical, and cylindrical surfaces. Experimental results are presented. Received December 2, 1998 / Revised June 18, 1999     

基于设计环境的图纸BOM 管理系统

随着无纸化生产模式的普及,大量工程图和BOM 数据的管理成了一个重 要的研究领域。论文介绍一种基于设计环境的图纸BOM 管理系统,该系统以整个产品或者 是整个部件的图纸为划分,基于数据库技术,直接集成于CAD 环境中,免去了PDM、PLM 等管理软件繁琐的流程管理,更接近设计人员的使用习惯,系统以工程图纸为数据基础,可 以生成多种格式的BOM 报表,通过在企业的实际应用中证明了该系统的可靠和高效。     

Syntactic interpretation approaches for innovative engineering drawings conversion support system

By integrating human intelligence and enabling geometric modeling and knowledge based systems technologies, a realistic and plausible solution for two critical activities in a legacy data conversion cycle of engineering drawings (LDC): vector drawing editing and high level symbol interpretation was investigated. A prototype system called LEDCONS was implemented to illustrate the concepts and demonstrate the feasibility of the architecture and methodologies proposed. In this paper, the concepts and methods used by LEDCONS to perform syntactic level drawing interpretations are presented. The LEDCONS system modules at this level are designed based on the strategy that drawing interpretation could be embedded within the process of human editing in an interactive fashion. Two fundamental approaches, the automatic search-and-match approach and the manual select-and-recognize approach, used for recognizing drawing constructs at this level are proposed. With syntactically related drawing constructs, such as text blocks, hatch patterns, dimension sets, FCF/datum constructs, and geometry entities are extracted. Hence, the reusability and reliability of the drawing data can be significantly increased.     

A technique for encoding lines and regions in engineering drawings

An improvement to a method of extracting line and region information from technical drawings is presented. A scheme for compressing this information as it is being found is also given. The encoding scheme is based on a combination of run-length codes, direction chain codes, and Huffman codes. It is efficient, requires minimal storage, and achieves favorable compression ratios. Experimental results from four typical line drawings are presented.     

面向内容的工程图识别与理解综述

对工程图识别与理解研究现状进行深入和系统的综述。工程图识别与理解 的核心在于利用知识表示、图形匹配、符号识别、几何推理、语义提取等技术,自动获取工 程图中各种显式描述（如几何图元、工程符号、工程对象等）及隐式信息（如设计语义等）。 分别对工程图矢量化、工程符号识别及工程对象识别进行了系统分析。在此基础上对工程图 识别性能评测、基准库等进行总结。最后对现有研究的难点及进一步研究方向进行了展望。     

The ergonomic study of engineering drawings

This article describes an investigation of engineering-drawing comprehension. A variety of subjects was used so that results would have a wider application.     

Automated restoration of engineering drawings into a CAD data base

With the increasing use of computers in the area of design and manufacture, a major problem being faced by the industry today is that of getting existing product information in the form of paper drawings into a suitable computer data base. This paper presents techniques for preprocessing and vectorizing scan digitized images of engineering drawings for automatically transferring the resulting data to commercially available CAD/CAM systems. The preprocessing steps include noise removal, void filling, image segmentation, line thinning and contour extraction. Algorithms for raster-to-vector conversion capable of recognizing and fitting straight-line segments, circles, arcs, and conic sections are presented along with results obtained from actual machine drawings.     

An object-oriented progressive-simplification-based vectorization system for engineering drawings: model, algorithm, and performance

Existing vectorization systems for engineering drawings usually take a two-phase workflow: convert a raster image to raw vectors and recognize graphic objects from the raw vectors. The first phase usually separates aground truth graphic object that intersects or touches other graphic objects into several parts, thus, the second phase faces the difficulty of searching for and merging raw vectors belonging to the same object. These operations slow down vectorization and degrade the recognition quality. Imitating the way humans read engineering drawings, we propose an efficient one-phase object-oriented vectorization model that recognizes each class of graphic objects from their natural characteristics. Each ground truth graphic object is recognized directly in its entirety at the pixel level. The raster image is progressively simplified by erasing recognized graphic objects to eliminate their interference with subsequent recognition. To evaluate the performance of the proposed model, we present experimental results on real-life drawings and quantitative analysis using third party protocols. The evaluation results show significant improvement in speed and recognition rate.     

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.     

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.     

Detection of dimension sets in engineering drawings

This correspondence presents a system for detecting dimension sets in engineering drawings that are drawn to ANSI drafting standards. A new rule-based text/graphics separation algorithm and a model-based procedure for detecting arrowheads in any orientation have been developed. Arrowhead tracking and search methods are used to extract leaders, tails, and witness lines from segmented images containing only graphics. Text blocks and feature control frames extracted from the segmented images are than associated with their corresponding leaders to obtain complete dimension sets. Experimental results are presented     

特征造型软件环境下图样表达方法研究

结合已经实行的“数字化产品数据定义通则”系列国家标准,对比二维图样 表达方法的优缺点,分析三维特征造型软件环境下的图样表达方式,研究了三维表达的基本 形式,指出基于特征造型软件环境开展工程制图教学,应在手工绘图条件下的各种二维表达 方式的基础上,充分发挥产品数字化数据定义的优势,采用最新国家标准,开展多种形式的 三维图样表达的教学。     

A model-based computer vision system for recognizing handwritten ZIP codes

This paper describes a recognition system for handwritten ZIP Codes currently under development at the Environmental Research Institute of Michigan (ERIM). Included within this system are techniques for preprocessing address block images, locating ZIP Codes, splitting touching characters, and identifying handwritten numerals. These techniques rely on mathematical morphology-based image processing and on hierarchical matching of object models to symbolic image representations. The image processing uses adaptive filtering, thresholding, and skeletonizing to create binary and state-labeled images. The matching process uses these images and extensively developed handwritten digit models to identify ZIP Codes. The end-to-end system has been tested on 500 randomly selected address block images. The system correctly recognized a large portion of the ZIP Codes in the test images (45.0%), and incorrectly classified a very low percentage of isolated handwritten digits (0.9%). Overall performance continues to be improved through incremental digit model refinement.This work was funded by the Office of Advanced Technology, United States Postal Service under contract 104230-86-H-0042.     

New trends on digitisation of complex engineering drawings

Neural Computing and Applications - Engineering drawings are commonly used across different industries such as oil and gas, mechanical engineering and others. Digitising these drawings is becoming...