A three-dimensional scanning method for intraoral scanning

Abstract

The invention discloses a three-dimensional scanning method for intraoral scanning, which is applied to the supplementary scanning process in the digital processing of intraoral data, and uses the characteristic information of 3D point clouds to realize the continuous scanning of intraoral data by scanning equipment and ensure the integrity of the data . And through the GPU to accelerate the matching process, the second-level re-scanning speed is achieved, which improves the scanning experience of the device.

Description

Technical field [0001] The present invention relates to the field of oral medical, and more particularly to a three-dimensional scanning method in an inlet scan. Background technique [0002] With the rapid development of three-dimensional measurement technology, this technology has important applications in various industries. Digitally in the digitalization of oral printing, three-dimensional information for measuring objects is generally obtained by striped projection techniques. Due to the limitations of measuring equipment and measurement conditions, three-dimensional data that measures the measurement scene is generally unable to obtain a measurement of the measurement scenario, there is a need to measure the measurement of the measured field, and repeatedly replenish it to acquire more complete measurement data. [0003] 3D point cloud free registration techniques are applied to the port three-dimensional scan, also known as scales, by repeated multiple, interrupt scans to...

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Problems solved by technology

[0004] (1) The general methods for calculating point cloud features include Spin Image, PFH, and PCA. Due to the algorithm itself, the calculation of 3D point cloud features is too slow and usually cannot meet real-time requirements;

[0005] (2) The accuracy of the 3D point cloud feature depends on the quality of the overall point cloud. When the point cloud noise is too large, the calculation accuracy of the 3D feature is not high, and it is easy to cause a mismatch;

[0006] (3) The amount of 3D point cloud data scanned in the mouth is very large, so there will be a lot of point cloud feature vectors that need to be retained. When performing supplementary scans on massive point cloud data, the algorithm complexity is large and cannot meet the requirements of real-time supplementary scans

[0007] (4) In intraoral scanning, due to the small field of view of intraoral measurement and the high similarity of 3D point cloud features in each frame, the general free registration technology cannot meet the measurement needs

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