Multiple Plane Fitting Algorithm to Evaluate the Accuracy of 3D Point Cloud Using Structured Light Measurement ☆

3D shape measurement by structured light is a high-speed method and the ability to profile complex surfaces. In particular, the processing of measuring data also greatly affects the accuracy of obtained point clouds. In this paper, an algorithm to detect multiple planes on point cloud data was developed based on RANSAC algorithm to evaluate the accuracy of point cloud measured by structural light. To evaluate the accuracy of the point cloud obtained, two step height parts are used. The planes are detected and measured in the distance between them need high accuracy processing. Therefore, the distance measurement data between the planes found in the point cloud is compared with the data measured by CMM measurement. The experimental results have shown that the proposed algorithm can identify multiple planes at the same time with a maximum standard deviation of 0.068 (mm) and maximum relative error is 1.46%.