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Processing depth distance data to increase precision of multiple infrared sensors in the automatic visual inspection system

机译:处理深度距离数据以提高自动视觉检查系统中多个红外传感器的精度

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摘要

Infrared depth recognition technology with an efficient custom-made signal smoothing algorithm is used as a base for a precise inspection system. The main purpose of this paper is to introduce the basics of an algorithm that will improve precision and stabilize distance measurements in projects with camera image and depth sensors. Such results are within the reach of currently available hardware but not with the available software, for which there is a lack of suppliers support. The second goal is to prove that golden sample data matrix compiled from multiple sensors data can be taken into consideration as a simple and general automated optical inspection system.
机译:具有高效定制信号平滑算法的红外深度识别技术被用作精密检查系统的基础。本文的主要目的是介绍一种算法的基础,该算法将提高具有相机图像和深度传感器的项目中的精度并稳定距离测量。这样的结果在当前可用硬件的范围之内,但在可用软件的范围之内,因为缺少供应商的支持。第二个目标是证明从多个传感器数据编译的黄金样本数据矩阵可以作为一种简单而通用的自动化光学检查系统加以考虑。

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