Coplanarity Detection Method Based on 3D Point Cloud and 2D Image Fusion

Abstract

The embodiment of the present invention discloses a coplanarity detection method based on the fusion of three-dimensional point cloud and two-dimensional image, including: step 1: establish a reference measurement coordinate system, determine the area to be measured and the anchor point; step 2: establish the coordinates of the measurement plane system; calibrate the coordinate system of the measurement equipment and transfer it to the matrix of the measurement plane coordinate system; Step 3: Convert the point cloud to obtain the three-dimensional coordinates of the point cloud under the measurement plane coordinate system; Step 4: Collect two-dimensional images and establish a mapping relationship; Step 5 : Extract the anchor point in the two-dimensional image to obtain the three-dimensional coordinate value of the anchor point; Step 6: Calculate the rotation and translation matrix required to align the standard model and the point cloud in the measurement plane coordinate system; Step 7: Transform the point cloud to the reference measurement coordinate Step 8: Calculate the height from each point in the target area to the reference plane. The invention realizes the automatic correction of the three-dimensional point cloud through online identification of the two-dimensional features, more effectively determines the position of the point to be detected, and improves the absolute accuracy and repeatability of the detection.

Description

technical field [0001] The invention relates to the technical field of three-dimensional measurement, in particular to a coplanarity detection method based on fusion of three-dimensional point clouds and two-dimensional images. Background technique [0002] In the past two years, with the rapid expansion of my country's electronic IC industry and high-end manufacturing industry, the demand for online testing of precision machining workpieces and electronic components has ushered in a blowout development. Such components have high manufacturing precision and relatively complex structures, which have extremely high requirements for quality control. In terms of detection, the requirements for detection accuracy and efficiency are relatively high. Traditional manual detection has errors, missed detection, inconsistent standards, etc., and the detection efficiency is low, which cannot meet the needs of large-scale production. [0003] The current traditional size detection of p...

AI Technical Summary

Problems solved by technology

If the change is large, the area selected by the fixed point of the mechanical sleeve will seriously deviate from the actual area to be measured, resulting in error in the measurement result and reducing the accuracy of repeated measurement

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