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首页> 外文期刊>Journal of Computing and Information Science in Engineering >Algorithms for Generating Adaptive Projection Patterns for 3D Shape Measurement
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Algorithms for Generating Adaptive Projection Patterns for 3D Shape Measurement

机译：用于生成3D形状测量的自适应投影图案的算法

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摘要

Point cloud construction using digital fringe projection (PCCDFP) is a noncontact technique for acquiring dense point clouds to represent the 3D shapes of objects. Most existing PCCDFP systems use projection patterns consisting of straight fringes with fixed fringe pitches. In certain situations, such patterns do not give the best results. In our earlier work, we have shown that for surfaces with large range of normal directions, patterns that use curved fringes with spatial pitch variation can significantly improve the process of constructing point clouds. This paper describes algorithms for automatically generating adaptive projection patterns that use curved fringes with spatial pitch variation to provide improved results for an object being measured. We also describe the supporting algorithms that are needed for utilizing adaptive projection patterns. Both simulation and physical experiments show that adaptive patterns are able to achieve improved performance, in terms of measurement accuracy and coverage, as compared to fixed-pitch straight fringe patterns.
机译：使用数字条纹投影（PCCDFP）的点云构造是一种非接触式技术，用于获取密集的点云以表示对象的3D形状。现有的大多数PCCDFP系统都使用由直条纹和固定条纹间距组成的投影图案。在某些情况下，此类模式无法提供最佳结果。在我们的早期工作中，我们表明，对于法线方向范围较大的曲面，使用具有空间间距变化的弯曲条纹的图案可以显着改善构建点云的过程。本文介绍了用于自动生成自适应投影图案的算法，该算法使用具有空间间距变化的弯曲条纹为被测物体提供改进的结果。我们还描述了利用自适应投影模式所需的支持算法。仿真和物理实验均表明，与固定螺距直条纹图案相比，自适应图案在测量精度和覆盖范围方面能够实现更高的性能。

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