Image Segmentation in Shape Synthesis, Shape Optimization, And Reverse Engineering

M. Ćurković, A. Curkovic, D. Vucina, D. Samardžić
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Abstract

Image segmentation and segmentation of geometry are one of the basic requirements for reverse engineering, shape synthesis, and shape optimization. In terms of shape optimization and shape synthesis where the original geometry should be faithfully replaced with some mathematical parametric model (NURBS, hierarchical NURBS, T-Spline, …) segmentation of geometry may be done directly on 3D geometry and its corresponding parametric values in the 2D parametric domain. In our approach, we are focused on segmentation of 2D parametric domain as an image instead of 3D geometry. The reason for this lies in our dynamic hierarchical parametric model, which controls the results of various operators from image processing applied to the parametric domain.
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形状合成、形状优化和逆向工程中的图像分割
图像分割和几何分割是逆向工程、形状综合和形状优化的基本要求之一。在形状优化和形状综合中,需要用一些数学参数模型(NURBS、分层NURBS、t样条等)忠实地代替原始几何形状,可以直接在二维参数域中对三维几何及其相应的参数值进行几何分割。在我们的方法中,我们专注于将2D参数域分割为图像,而不是3D几何形状。其原因在于我们的动态分层参数模型,该模型控制了应用于参数域的图像处理的各种算子的结果。
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