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

Abstract

This article introduces the new paradigm of intelligent measurement process in the context of 3-D optical metrology. Because new 3-D sensor technologies can capture 3-D 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 3-D point observations allows one to examine the local distribution of these points on section areas before validating their consis- tency 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. We describe a framework adapted for implementing such a process. The result section presents some application cases in metrology. The article concludes with prospective comments on intelligent measurement systems.