Detection of Atypical Data in Point Cloud of Technical Vision System using Digital Filtering

2022 IEEE Mexican International Conference on Computer Science (ENC) Pub Date : 2022-08-24 DOI:10.1109/ENC56672.2022.9882955

Ivan Yeniseysk Alba Corpus, W. Flores-Fuentes, J. Rodríguez-Quiñonez, D. Hernández-Balbuena, F. F. González-Navarro, O. Sergiyenko, Ruben Alaniz-Plata

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引用次数: 2

Abstract

Most non-contact methods and systems for 3D spatial coordinate measurement are based on optical sensors and signal processing. Object surfaces are discretely detected to obtain their coordinates and generate a point cloud that can be processed to reconstruct the object's shape and dimensions. Optical sensor-based technologies are the most widely used because they are non-destructive and do not need to touch objects. One of their best properties is their fast measurement acquisition rate. However, one of their disadvantages is the presence of atypical values in their measurements due to their sensitivity to optical ambient noise. Filtering atypical values from point clouds allow the generation and reconstruction of mesh and geometrical models of objects with appearance and dimensions similar to reality. This work is focused on the point cloud post-processing of 3D spatial coordinates measurements obtained from a technical vision system to eliminate inaccuracies in the reconstruction models.

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基于数字滤波的技术视觉系统点云非典型数据检测

大多数非接触式三维空间坐标测量方法和系统都是基于光学传感器和信号处理的。对物体表面进行离散检测以获得其坐标并生成点云，该点云可以通过处理重建物体的形状和尺寸。基于光学传感器的技术应用最广泛，因为它们是非破坏性的，不需要接触物体。其最佳特性之一是测量采集速度快。然而，它们的缺点之一是由于对光学环境噪声的敏感性，在测量中存在非典型值。从点云中过滤非典型值允许生成和重建具有与现实相似外观和尺寸的物体的网格和几何模型。这项工作的重点是对从技术视觉系统获得的三维空间坐标测量进行点云后处理，以消除重建模型中的不准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 IEEE Mexican International Conference on Computer Science (ENC)

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