Robot Vision System for Coordinate Measurement of Feature Points on Large Scale Automobile Part

In this paper,we present a robot vision based system for coordinate measurement of feature points on large scale automobile parts.Our system consists of an industrial 6-DOF robot mounted with a CCD camera and a PC.The system controls the robot into the area of feature points.The images of measuring feature points are acquired by the camera mounted on the robot.3D positions of the feature points are obtained from a model based pose estimation that applies to the images.The measured positions of all feature points are then transformed to the reference coordinate of feature points whose positions are obtained from the coordinate measuring machine（CMM）.Finally,the point-to-point distances between the measured feature points and the reference feature points are calculated and reported.The results show that the root mean square error（RMSE） of measure values obtained by our system is less than 0.5 mm.Our system is adequate for automobile assembly and can perform faster than conventional methods.

Principle of Coordinates Acquisition Based on Single Camera

The principle and accuracy of 3-D coordinates acquisition using one single camera and the Aided Measuring Probe(AMP) are discussed in this paper. Using one single camera and one AMP which has several embedded targets and one tip with known coordinates, the single camera′s orientation and location can be calculated. After orientation, the global coordinate system is obtained. During measurement, the camera is fixed firstly, then the AMP is held and the feature point is touched.The camera is triggered lastly. The position and orientation of the AMP are therefore calculated from the size and position of its image on the sensor. Since the tip point of AMP has known relation with the embedded targets, the feature point can be measured. Tests show that the accuracy of length measurement is 0.2 mm and accuracy for flatness measurement in XSY-plane is 0.1 mm.

基于靶标的三目视觉3维坐标测量系统

为了解决复杂环境中大视场、高精度、非接触3维测量问题,采用三目摄像机结构,通过靶标成像来测量被测点3维坐标的测量系统。测量时摄像机采集测量靶标的图像,计算机通过图像处理的方法获取测量靶标上标志点的3维坐标,并提出基于被测点与标志点间距离方程与直线约束的被测点求解优化方法。测量系统通过高精度光栅位移平台带动测量靶标移动来完成测试。结果表明,测量系统在视场范围、测量精度、使用灵活性等方面有较大的改进,能够测量视场深度从2m～5m范围内的视场,测量精度优于0.2mm。

工件特征点三维坐标视觉测量方法综述

针对工件上特征点的三维坐标视觉测量方法进行了综述 ,其中包括结构光方法、激光自动聚焦法、双目视觉方法、三目视觉方法、单目视觉方法等。对每种方法的特点及其测量精度进行了详细的分析 。

Quality measure of color images based on properties ofvision psychology and color distortion in MPEG-21

In this article, a new way to evaluate the quality of color images is proposed, in which the properties of human vision psychology, objective fidelity, edge information, and color distortion will be combined through utilizing 3-D matrix transform. There exists color redundancy and structural similarity between three different frames of a color image, the definition of vision properties will be measured by 3-D submatrix integration transform （SIT）, in which three color components are integrated into one model and color redundancy can be exploited fully. The simulation results show that the measure index is very effective and objective in accord with vision properties.

激光跟踪测距三维坐标视觉测量系统建模

提出了一种激光跟踪测距视觉坐标测量系统,主要由摄像机、激光测距仪、计算机和光笔组成。测量时摄像机测量光笔上各光反射点的方向,激光测距仪跟踪捕捉并测量出某一光反射点到激光测距仪的距离,由测得的方向和距离计算出光笔笔尖接触点的三维坐标。根据n点透视问题(PnP)原理建立了系统的数学模型,激光测距仪测得的距离参数的引入,使得该数学模型可以线性求解,而且解具有唯一性。依据冗余技术给出了被测点三维坐标的求解方程组及其解法。和单摄像机视觉坐标测量系统的比对实验结果表明:在Z、Y和X轴方向上的测量稳定性精度可分别提高0.366、0.031和0.011 mm。