A sub-pixel positioning method for centerline laser center in 3D laser scanning system

Abstract

The invention discloses a sub-pixel positioning method for the midline laser center of a three-dimensional laser scanning system. Threshold segmentation is performed on the image, and the line laser is roughly extracted; the burr phenomenon of the line laser after rough extraction is eliminated, and the width of the line laser is further reduced; the sub-pixel level coordinates of the center of the line laser are obtained by using the improved center of gravity method, and then the Hough transform is used Corrects false object pixels in sub-pixel coordinates. This positioning method combines the improved center-of-gravity method and Hough transform, which can meet the needs of the 3D laser scanning system to obtain the sub-pixel coordinates of the line laser center in real time and accurately, and realize the sub-pixel precise positioning of the line laser center.

Description

technical field [0001] The invention relates to a method for sub-pixel positioning of a line laser center in a three-dimensional laser scanning system. Background technique [0002] With the continuous development of machine vision technology, 3D laser scanning technology has gradually become the core force in this field. With the advantages of real-time acquisition of 3D data information on the surface of the object to be measured, high scanning accuracy and non-contact characteristics, 3D laser scanning has become one of the hotspots of new technology research. [0003] The three-dimensional laser scanning system is generally composed of a line laser, a camera, a stepping motor, a rotating platform, etc. The line laser is used to emit a line laser light band, and the camera is used to capture the image containing the line laser on the surface of the measured object in real time. The motor and the rotating platform are used to obtain scanning information from multiple angl...

AI Technical Summary

Problems solved by technology

The curve fitting algorithm has high extraction accuracy and can reach sub-pixel accuracy, but the amount of data processed in the calculation process is relatively large

[0006] Various algorithms have their advantages and disadvantages according to their different principles. The advantages of the extreme value method, the threshold method, and the gray center of gravity method are that the algorithm is simple, the speed is fast, and it can realize real-time scanning, but it is seriously affected by noise.

Curve fitting method and Hessian matrix method have high extraction accuracy, can reach the sub-pixel level, are less susceptible to noise interference and have good robustness, but the algorithm complexity is high, the detection speed is slow, and it cannot meet the real-time requirements

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