An integrated implementation for product design

This paper represent an integrated implementation to shorten the product development cycle. The developed system uses machine vision techniques to automate the creation of CAD models for existing parts of prototypes. It extracts the manufacturing features based on the created CAD database and the tolerances that are to be added to the created CAD dabatase for CAD/CAM practice and concurrent analysis. The geometric features are organized in a database which can be imported to an automated process planning and cost estimation system. This integrated implementation is capable of providing manufacturing feedback during the product development stage. This paper outlines the development of the vision system, the creation of the CAD model, and the design of the database.     

A neural network approach for defect identification and classification on leather fabric

In this paper, an automated vision system is presented to detect and classify surface defects on leather fabric. Visual defects in a gray-level image are located through thresholding and morphological processing, and their geometric information is immediately reported. Three input feature sets are proposed and tested to find the best set to characterize five types of defects: lines, holes, stains, wears, and knots. Two multilayered perceptron models with one and two hidden layers are tested for the classification of defects. If multiple line defects are identified on a given image as a result of classification, a line combination test is conducted to check if they are parts of larger line defects. Experimental results on 140 defect samples show that two-layered perceptrons are better than three-layered perceptrons for this problem. The classification results of this neural network approach are compared with those of a decision tree approach. The comparison shows that the neural network classifier provides better classification accuracy despite longer training times.     

西林瓶缺陷自动视觉检测方法与系统研究

与传统的西林瓶缺陷人工检测方法相比,在线视觉自动检测具有巨大优越性。设计了一套西林瓶缺陷自动视觉在线检测系统,研究了系统的机械与电气结构,并设计了针对西林瓶的视觉成像与图像获取装置;根据西林瓶各部位的形状特殊性,针对性地提出了具体的检测方法。选取各类缺陷样品100瓶进行测试,结果表明该系统检测准确度较高,能满足实际生产的需求。     

A CAD Model Based System for Object Recognition

3D object recognition is a difficult and yet an important problem in computer vision. A 3D object recognition system has two major components, namely: an object modeller and a system that performs the matching of stored representations to those derived from the sensed image. The performance of systems wherein the construction of object models is done by training from one or more images of the objects, has not been very satisfactory. Although objects used in a robotic workcell or in assembly processes have been designed using a CAD system, the vision systems used for recognition of these objects are independent of the CAD database. This paper proposes a scheme for interfacing the CAD database of objects and the computer vision processes used for recognising these objects. CAD models of objects are processed to generate vision oriented features that appear in the different views of the object and the same features are extracted from images of the object to identify the object and its pose.     

Modeling by Drawing with Shadow Guidance

Modeling 3D objects is difficult, especially for the user who lacks the knowledge on 3D geometry or even on 2D sketching. In this paper, we present a novel sketch‐based modeling system which allows novice users to create 3D custom models by assembling parts based on a database of pre‐segmented 3D models. Different from previous systems, our system supports the user with visualized and meaningful shadow guidance under his strokes dynamically to guide the user to convey his design concept easily and quickly. Our system interprets the user's strokes as similarity queries into database to generate the shadow image for guiding the user's further drawing and returns the 3D candidate parts for modeling simultaneously. Moreover, our system preserves the high‐level structure in generated models based on prior knowledge pre‐analyzed from the database, and allows the user to create custom parts with geometric variations. We demonstrate the applicability and effectiveness of our modeling system with human subjects and present various models designed using our system.     

Object oriented concepts and mechanisms for feature-based computer integrated inspection

Computer vision can provide fast, accurate and reliable inspection. In this paper is described a knowledge-based vision inspection planning system for manufactured components based on their CAD design models. An object oriented methodology is developed to capture the knowledge such as the geometric entities, their relationships, sensors and plans. Reasoning mechanisms are developed to automatically determine various attributes of the different features of an object to be inspected, and to generate the alternative strategies for inspection of each attribute. Mechanisms for automated generation of sensor settings and optimization of the inspection plan are also developed. Sensor constraints are considered in determining the camera parameters. This inspection methodology is flexible, and it is easily integrated with the design and process planning aspects of an integrated manufacturing system.     

Automatic inspection of mechanical parts using geometric models and laser range finder data

This paper addresses the problems associated in processing arrays of depth data in order to achieve the goal of automatic inspection of mechanical parts, i. e. developing general model-based inspection strategies that can be applied to a range of objects. The main problems in processing this data are segmenting out reliable primitives from the data and matching these primitives to those in a stored geometric model of an object. The ability of a 3D vision system to provide depth data accurate enough to perform automatic inspection tasks was until recently only possible at a short range from an object, typically a few centimetres. However it is now possible to produce dense data from a vision system situated further from the object, typically half a metre to a metre. Such a system is outlined. Some current model-based matching techniques are assessed for their suitability for employment in inspection type tasks. One approach is adopted and modifications that improve the efficiency and accuracy of the method for inspection purposes are presented. Finally, an inspection strategy is outlined and its performance assessed. Results are presented on both artificial and real depth data.     

CAD off-line programming for industrial machine vision

CAD/CAM tools are essential components of the computer-integrated factory. Up to now, they have been used for tasks such as the simulation and path programming of numerically controlled machine tools, and sometimes industrial robots. The CAD-vision interconnection described here enables us to program parts learning on the workstation, to download piece features in the vision system for inspection on the production line, to simulate the recognition process on a set of parts stored in the computer, and to update vision files after modifications in the CAD system database.     

基于DWL的合成视景系统数据库的完整性

合成视景系统（SVS）是解决可控飞行撞地(CFIT)事故的有效途径,近年来,国家实施的重点基础研究发展计划已经把SVS的相关研究纳入了计划研究的一部分。SVS数据库的完整性研究是SVS研究中比较重要的部分。基于现阶段大部分飞机上都配备GPS、雷达测高仪等设备,本文主要基于下视传感器（DWL）对SVS数据库的完整性进行研究。基于DWL对SVS数据库进行实时监控可以有效保证数据库垂直方向数据的完整性,但是对于飞机数据库水平方向数据的完整性保证能力还略显不足。     

一种基于关系型数据库的工作流管理系统

本文提出了一种基于关系型数据库的工作流管理系统。该方案将业务分为基础业务与拓展业务,然后通过一个简单的工作流模型表示基础业务逻辑,并使用关系型数据库处理拓展业务。此外,该方案将业务逻辑与业务的设计相结合,形成了一个通过配置即可开发信息管理系统的平台。该系统的实际应用表明该方案实现简单,能够处理大部分其他工作流模型无法表示的工作流模式,并且该系统易于业务人员操作,能够达到快速开发的目的。     

In-Place Augmented Reality

In this paper, we present a vision-based approach for transmitting virtual models for Augmented Reality, which we name In-Place Augmented Reality (IPAR). A two-dimensional representation of the virtual models is embedded in a printed image. We apply computer vision techniques to interpret the printed image and extract the virtual models, which are then overlaid on the printed image. The main advantages of our approach are: (1) the image of the embedded virtual models and their behaviors are understandable to a human without using an AR system and (2) no database or network communication is required to retrieve the models. To demonstrate the technology and test its usability, we implemented several applications and performed a user evaluation. We discuss how the proposed technique can be used for the development of applications in different domains such as education, advertisement, and gaming.     

基于半监督聚类的3维肢体分割算法

行为分析已经成为计算机视觉研究领域的热点,行为主体的肢体部件分割是行为分析中很重要的一部分同时也是一个难点问题,为了对3维肢体进行有效分割,提出了一种基于半监督聚类的肢体分割算法。该算法首先利用前一帧姿势估计反馈的时域信息来对3维主体进行初始的肢体部件分割;然后根据人体结构信息进一步确定行为主体上各个点与肢体部件之间的关系来得到半监督聚类的初始值;之后基于各个肢体部件的形状信息进行半监督聚类,迭代求解肢体部件分割的最优解;最后利用分割后的各个肢体部件进行行为主体的姿势参数估计。通过对IXMAS数据库中6种行为下的6个行为主体进行的肢体部件的分割实验结果证明,该新算法具有主体适应性、视角适应性以及行为适应性。     

Stereo Image Processing and Virtual Reality in an Intelligent Robot Control System

This paper can be divided into two main parts. Both of them describe one of those parts of an intelligent robot control system, which makes the system capable to interact with its environment via visual information. The two parts can be handled as complementary parts of each other. The first part shows the solution of the data extraction from the visual information. This is a well known machine vision problem, in this case, the applied method is a passive stereo type. The second part explains the method of visual representation of the data. This is a visualization problem, in this case, a virtual reality system is used. With the use of the detailed graphic models of VR, efficient off-line robot programming and simulation is available.     

Database security—System architectures

Database security is a rapidly growing research area, spawning work in several different subareas proceeding independently in many directions. In surveying the subject this paper draws together some of this diverse work and attempts to indicate relationships among the parts. A theme of the paper is to recommend a system architecture approach to database security. Such a view is more likely to bring modularity, simplicity, isolatability and flexibility to overall system solutions than will ad hoc attempts to tune-up individual parts.Systems requirements are stated and the relation to operating system security is discussed. Security kernels, their history as well as their advantages and problems, are described. Security requirements found in databases, but not in operating systems, are introduced. Some models and experimental systems are reviewed, representing non-architectural and architectural approaches to non-secure and secure database systems. Some conclusions and trends for the furure are discussed.     

基于光学三角几何关系的三维表面重建方法

工业图像处理作为图像处理技术的工业应用,是自动化技术的发展方向之一.传统的二维图像处理已经在视觉检测系统中广泛应用.目前利用光学方法的三维数字化具有越来越重要的意义.在工业生产中,多种获取三维数据的途径得到应用.其中最重要的方法有立体视觉,条形光相位平移法和条形光格雷编码法.本文重点介绍这三种方法在视觉检测系统中的运用.所开发的系统实现了被测工件可视化,而且更容易地将三维图像集成到生产线中.     

A model-based vision system for industrial parts using a small computer

A model-based vision system has been successfully implemented in a small computer environment. This approach uses a basic solid modeling system to develop three-dimensional models of mechanical parts. From those models, two-dimensional projections are taken for every stable state of the object, with many orientations around the object's vertical axis for each stable state. These two-dimensional projections are treated as synthetic binary images, from which a variety of features may be measured and extracted. A similar procedure is used for a binary image of an object from a real scene, and features are also extracted for that image. A simple matching procedures uses the model-based feature sets to determine the real object's stable state position and orientation. This paper describes the system in detail and shows examples of its use.     

On-line evolving image classifiers and their application to surface inspection

In this paper, we present image classifiers which are able to adapt and evolve themselves at an on-line machine vision system. These classifiers are initially trained on some pre-labelled training data and further updated based on newly recorded samples, for instance during a production process. The evolution and adaptation mechanism is necessary in order to guarantee a process-save on-line system as usually the pre-labelled data does not cover all possible operating conditions, system states or image classes. It is also recommended for a refinement of the classifiers during the on-line mode in order to boost predictive performance with more loaded samples. We will present two types of on-line evolving image classifiers: The first one is a clustering-based classification approach, which exploits conventional vector quantization, forming an incremental evolving variant around it and extending it to the supervised classification case. The second one is an evolving fuzzy classifier approach which comes with two model architectures, classical single model and a novel multi-model architecture, the later exploiting indicator matrices/vectors for training. The approaches are evaluated in three different on-line surface inspection systems dealing with CD imprint inspection, egg inspection and inspection of metal rotor parts. The evaluation will show the impact of on-line evolved versus ‘static’ classifiers kept fixed during the whole on-line process.