The Research of Data Points Quality Assessment Method in Reverse Engineering

Abstract

In the field of reverse engineering, data quality assessment is a very important work in the detection, the result of data quality assessment will directly or indirectly affect the detection and the following manufacturing process quality. Data quality assessment can be used in the camera calibration, the model and model reconstruction comparison, and so on. In this paper, on the basis of the existing method of calculating each point error, and multipurpose use of average and standard error and some other concepts of mathematical statistics, and then improve a novel and simple calculating error method. This method is applicable to many groups of one-to-one ideal data and the measured data comparison, and it can be more intuitive to reflect the error of overall data, as well as the error distribution, and it can be more efficient to determine the measured data is reasonable or not. In this paper, the data point quality which is collected in the reverse engineering is assessed, and it can see that the method which is proposed in this article has some advantages in the data point quality assessment field.

Research on Surface Reconstruction from Intersecting Curves

“…By refinement [3], after extracting the skeleton of the original image into a single row of pixels, center of the intersection of the cross laser line in the left and right images is very easy to find. Then, point detected in the left view, in order to find the corresponding matching point on the right image.…”

A systematic use of reverse engineering in evaluating the overall accuracy of the fabricated parts

“…(2002), Yau H. T. (1997), andNarayanan Namboothiri V. N., Shunmugam, M. S., (1998) describe different data accuracy and error analysis methods, such as, linear approximation techniques, least-square method, and geometric and surface shape evaluation. Cheng, J.T., Zhao, W. L., Xie, X. D., (2009) made an improvement of the method of data quality assessment, while Wu, X. M. does an error analysis and precision evaluation of reconstructed surfaces in which the accuracy of a CMM machine is evaluated (Wu, X. M., Yu, G. B., Li, G. X., Shan, D. B., 2011). The above computerized/automated system resolves the limitations of the manual systems including time consuming and human error.…”