Method for generating noncontact measurement feature points

Abstract

A method for generating noncontact measurement feature points solves measurement errors caused by pasting feature points in the noncontact measurement. The method comprises steps of: 1, projecting a first laser spot array onto a first measurement area on the surface of an object to be measured, wherein two laser spot arrays mutually contain three or more non-collinear laser spot feature points; 2, using the position, the size and the direction information of each laser spot feature point as a unique identification mark in plurality of imaging view angle; 3, deleting, by using a circular constraint algorithm, all other illegal feature points of non-laser spot feature points in the result of the laser spot feature point algorithm extracted in the step 2, and completing identical point matching of a laser spot center by means of the feature matching of an SIFT algorithm; and 4, repeating the steps 1 to 3 to complete the generation of measurement feature points in the measurement area each time. The method is simple in feature point generation and easy to operate. The feature points and the actual points are small low in errors and have density matching the laser light spot array.

Description

Technical field: [0001] The invention belongs to the field of non-contact measurement of digital close-range photography, and relates to a method for generating measurement feature points in the dense point measurement technology of the complete three-dimensional shape of an object without pasting marker points. Background technique [0002] Digital close-range photogrammetry technology is an optical three-dimensional measurement technology that uses multi-angle shooting images, extracts feature points on the image and calculates three-dimensional coordinates. [0003] Digital close-range photogrammetry technology has the advantages of large measurement range, simple working conditions, and high measurement accuracy. It is widely used in workpiece detection, deformation detection and other related 3D shape measurement fields. Its measurement mainly relies on a set of coded feature points and non-coded feature points pasted on the surface of the measured object, so the shortc...

AI Technical Summary

Problems solved by technology

[0005] The shortcomings of using the above measurement methods to obtain dense point data on the surface of the measured object are obvious: first, the operator needs to operate two different measurement systems, which increases the complexity; second, for accurate positioning, the frame points need to be precisely customized, and because the measured The size and shape of objects are ever-changing, and unreasonable layout of frame points will lead to measurement failure; finally, due to the introduction of other measurement technologies, the accuracy of the final measured data points is not entirely determined by digital close-range photogrammetry technology, but also depends on other measurements The precision of the technology, and the frame point only plays the role of unifying the coordinates, not the real coordinates on the surface of the measured object

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