从工业环境的距离图像中生成表面模型

A. Sappa
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引用次数: 4

摘要

我们提出了一种混合分割技术,它结合了基于边缘的方法的速度和基于表面的方法的鲁棒性。它包括三个阶段。在第一阶段,扫描线逼近过程提取包含在给定范围图像中的边缘。这些边稍后用于定义种子点的位置。第二阶段采用两步区域生长技术。首先,二维生长过程扩大原始种子点,产生更大的区域。接下来,将每个区域装配到一个平面和一个圆柱体上。选择最适合给定点的一个来表示该区域,并在3D生长阶段使用。在进行三维生长阶段时,考虑了拟合曲面上待添加点的逼近误差。通过这种方式,每个表面都会生长,直到根据用户定义的阈值无法添加点为止。最后,在第三阶段,后处理算法合并属于同一表面的相邻区域。给出了在工业环境下的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surface model generation from range images of industrial environments
We present an hybrid segmentation technique that combines both the speed of an edge based approach with the robustness of a surface based approach. It consists of three stages. In the first stage a scan line approximation process extracts the edges contained into the given range image. These edges are later on used to define the positions of seed points. Through the second stage a two steps region growing technique is applied. First a 2D growing process enlarges the original seed points generating bigger regions. Next, each region is fitted to a plane and a cylinder. The one that best fit the given points is selected to represent that region and used during the 3D growing stage. The 3D growing stage is carried out taking into account the approximation error from candidate points to be added to the fitted surface. In this way, each surface is grown until no points can be added according to a user defined threshold. Finally, in the third stage, a post-processing algorithm merges neighbour regions that belong to the same surface. Experimental results by using industrial environments are presented.
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