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Component Extraction on CT Volumes of Assembled Products Using Geometric Template Matching

机译:使用几何模板匹配提取装配产品CT体积上的成分

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As a method of non-destructive internal inspection, X-ray computed tomography (CT) is used not only in medical applications but also for product inspection. Some assembled products can be divided into separate components based on density, which is known to be approximately proportional to CT values. However, components whose densities are similar cannot be distinguished using the CT value driven approach. In this study, we proposed a new component extraction algorithm from the CT volume, using a set of voxels with an assigned CT value with the surface mesh as the template rather than the density. The method has two main stages: rough matching and fine matching. At the rough matching stage, the position of candidate targets is identified roughly from the CT volume, using the template of the target component. At the fine matching stage, these candidates are precisely matched with the templates, allowing the correct position of the components to be detected from the CT volume. The results of two computational experiments showed that the proposed algorithm is able to extract components with similar density within the assembled products on CT volumes.
机译:作为无损内部检查的一种方法,X射线计算机断层扫描(CT)不仅用于医疗应用,而且还用于产品检查。某些组装产品可以根据密度分为独立的组件,密度与CT值大致成正比。但是,使用CT值驱动的方法无法区分密度相似的组件。在这项研究中,我们提出了一种新的从CT体积中提取分量的算法,该算法使用一组具有指定CT值且以表面网格作为模板而不是密度的体素。该方法具有两个主要阶段:粗匹配和精匹配。在粗略匹配阶段,使用目标组件的模板从CT体中大致确定候选目标的位置。在精细匹配阶段,这些候选对象将与模板精确匹配,从而可以从CT体积中检测出组件的正确位置。两次计算实验的结果表明,所提出的算法能够在CT体积上提取组装产品中具有相似密度的成分。

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