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Precision control of scale using in Industrial Close-Range Photogrammetry


发布时间:2010年8月17日 7时11分

Abstract: This paper research the effection of scale using in reconstruction of industry close-range photogrammetry. The two major factor of scale using, deviation of scale reconstruction and calibration, are analyzed. Based on the analysis, the equation of deviation in scale using is obtained and verificated by the experiment. According to this equation, some requsts of scale using to improve the reconstruction accuracy are studied, and a new scale using method, close scale model, is proposed. Using close scale model, it can be reduced the effection of scale using deviation in reconstruction,
the accuracy of industrial close-range photogrammetry is improved.

Introduce
In industry, there is a strongly need for accurately measuring the 3-D shapes of objects to speed up and ensure product development and manufacturing quality. A variety of applications of 3-D shape measurement include coordination with the reverse engineering, dimension measurement for die development, stamping panel geometry checking and accurate stress/strain measurement. Moreover, automatic on line inspection and recognition issues can be converted to the 3-D shape measurement of an object under inspection, for example, body panel paint defect and dent inspection. Recently, with the evolution in computer technologies, coupled with the development of digital imaging devices, electro-optical components, especially the development of CCD, laser and other light sources, 3-D shape measurement is now at
the point that some techniques have been successfully commercialized[1].
Typical photogrammetry employs the stereo technique to measure 3-D shape,although other methods such as defocus, shading and scaling can also be used. Photogrammetry is mainly used for feature type 3-D dimension measurement. It must usually have some bright markers such as retroreflective painted dots on the surface  of a measured object. In general, photogrammetric 3-D reconstruction is established on the bundle adjustment principle in which the geometric model of the central perspective and the orientation of the bundles of light rays in a photogrammetric relationship is developed analytically and implemented by a least squares procedure.
Extensive research has been done to improve the accuracy of photogrammetry. Recent advances make it achieve high accuracy as one part in 100,000 or even one part in 1,000,000[1].
Photogrammetry encompasses methods of image measurement and interpretation in order to derive the shape and location of an object from one or more photographs of that object[2].Photogrammetry is a technique for determining the three-dimensional geometry (location, size, and shape) of physical objects by measuring and analyzing their two-dimensional photographs[3]. Close-range photogrammetry became a viable tool for high-precision 3D measurement in industrial manufacturing and large-scale engineering with the development in the early 1980s of specialised cameras, film
comparators and PC-based data processing systems for both network design and multi-image triangulation[4].

Photogrammetry derives three-dimensional location of an object primaryly from one or more photographs of the object. Industrial close-range photogrammetry derive reconstruction data by processing the photographs of the targets, which are installed around the object. Through Industrial close-range photogrammetry, it can obtain more precision location data of targets. It is widely used in the detection of the workpiece,
especially the large scale workpiece, or used co-ordinately with optical scan systems to obtain the surface shap data of the object. In the process of it used, as Fig. 1 shows, at first, process the photographs of targets to get the center location of targets in each photograph; then calculate control points(coded targets) by several photographs; after control points calculated, optimal the whole control points to decrease the deviation;

then according to the relationship of locations of all points and calculated position of cammera in photographs, calcuate the location of other points(as uncoded points and feature points); then optimal the whole points reconstructed. After this step, the relative location of the whole points is obtained, but the distances between each point are very small, because the distances are estimated by the distances between the pixels in photographs at this time. So it must set the scale of the project in measurement to obtain the actual location of reconstruction. In measurement, it set one or more sets of points as scales. According to the distance of initial points location and the length of scale to be used, calculate the rate to magnify the measurement data. In actual measurement, the length of scale is calculated before measurement by some more precision measure methods(as three-dimensional measuring machine and etc), but the deviation of the length to be used and the actual length is not zero. So how the deviation to affect the finial result of measurement and how to reduce the effection of the deviation will be researched in this paper.

Fig. 3 Experiment of reconstruction by using different length of scale

Fig. 5 Calculation of close scale model


 

 
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