Intelligent Measurement Processes in 3D Optical Metrology: Producing More Accurate Point Clouds

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Abstract

This article introduces the new paradigm of intelligent measurement processes in the context of 3D optical metrology. Because new 3D sensor technologies can capture 3D points at very high rates on the surface of objects, it is now possible to quickly capture very dense sets of points on an object’s surface. This very large quantity of 3D point observations allows one to examine the local distribution of these points on section areas before validating their consistency with the expected error model developed at the calibration stage. From these dense point observations, higher quality surface point measurements can be produced for metrology. An intelligent measurement process will integrate these steps in real time during capture. In this article, we describe a framework adapted for implementing such a process and present some metrology application cases. The article concludes with prospective comments on intelligent measurement systems.