Laser line scanning 3D detection method and system based on scanning galvanometer and event camera

Abstract

The invention belongs to the field of 3D detection and measurement, and particularly relates to a laser line scanning 3D detection method and system based on a scanning galvanometer and an event camera. The method comprises the following steps: the laser line is reflected to an object to be detected by the scanning galvanometer, so that laser line scanning is achieved; the event camera is adoptedto collect laser line signal information reflected from the object to be measured, and pixel points with changed brightness on the object to be measured and corresponding time points are stored and output; the position coordinate of the space point of the object to be detected scanned by the laser line at the moment is calculated through the relative position between the scanning galvanometer andthe event camera, the pixel point output in the step 2 and the scanning galvanometer rotation angle corresponding to the moment point corresponding to the pixel point; the steps are repeated to complete all space point coordinates of the object to be measured so as to obtain 3D point cloud data of the object to be measured, thereby solving the limitations of frame rate, resolution and illuminationresistance in the current 3D scheme.

Description

Technical field[0001]The invention belongs to the field of 3D detection and measurement, and in particular relates to a 3D detection method and system based on scanning galvanometer and event camera laser line scanning.Background technique[0002]With the rapid development of machine vision, intelligent manufacturing, security and logistics, non-contact fast 3D reconstruction technology has become a major research focus. The current mainstream 3D schemes are mainly binocular RGB scheme, structured light scheme, and TOF scheme. The three schemes have their limitations in frame rate, resolution, and anti-light performance:[0003]1. The depth information of the binocular solution is derived from pure software algorithms. This algorithm is highly complex and difficult. The processing chip requires high computing performance. It is not applicable in a dim environment and when the features are not obvious.[0004]2. The depth image resolution of the structured light scheme can be made relative...

AI Technical Summary

Problems solved by technology

[0003] 1. The depth information of the binocular solution relies on a pure software algorithm. This algorithm is highly complex and difficult, and the processing chip requires high computing performance. It is not applicable in dark environments and when the features are not obvious.

[0004] 2. The depth image resolution of the structured light solution can be made relatively high, but it is easily affected by light, and the outdoor environment is basically unusable; moreover, multiple photos are required to complete encoding and decoding, which greatly reduces the detection rate, and is only suitable for measuring static objects. , not suitable for measuring dynamic objects

[0005] 3. The TOF solution has good anti-interference performance and a wider viewing angle, but the resolution of the depth image is very low. It can be used for some simple obstacle avoidance and visual navigation, but it is not suitable for high-precision occasions.

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