Three-dimensional morphology measurement method based on reflector and monocular vision

Abstract

The invention discloses a three-dimensional topography measurement method based on a reflector and monocular vision. The method comprises the following steps of designing an infrared three-dimensionaltarget in advance, and arranging a plurality of infrared LEDs on the target; calibrating a monocular camera to obtain a distortion coefficient matrix participating in the camera; and calculating theposition and attitude of the line laser scanner in the camera coordinate system according to the conversion relationship of coordinate systems of systems and a PnP algorithm, and converting and splicing the point cloud data in the line laser scanner by using the position and attitude so as to perform three-dimensional reconstruction on the surface topography. The method is advantaged in that monocular vision is used for positioning, complex equipment such as a high-precision guide rail is not needed for providing y-direction coordinates of the point cloud, and a problem that a light path is blocked when monocular vision is used for visual positioning of a target can be solved through addition of reflection measurement.

Description

technical field [0001] The invention relates to the technical field of measurement systems, in particular to a three-dimensional measurement method based on reflection measurement and monocular vision principles. Background technique [0002] With the development of intelligence, equipment and parts require higher manufacturing precision, as well as higher-precision and high-efficiency detection methods. Technologies such as digital twins also require the acquisition of the three-dimensional shape of objects. With the development and wide application of non-contact measurement equipment such as lasers and structured light, it is possible to obtain the three-dimensional shape of the object surface more efficiently and accurately. Point cloud-based 3D reconstruction technology, the key to accuracy is point cloud splicing. The point cloud splicing process will produce error accumulation. The larger the size, the more splicing times and the greater the error. The current conven...

AI Technical Summary

Problems solved by technology

[0003] In summary, the existing 3D reconstruction methods are difficult to obtain effective point cloud data and follow-up reconstruction work when rays cannot be traced.

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