Research on Sensitivity of Speckle Center Coordinate Values by Contour and Background Noise and Elimination Method

Abstract

The accuracy of measuring the target object displacement is greatly influenced by the offset of central coordinate value in a laser speckle contour (CCVLSC) due to the defects obtained in background or on measuring surface, as a measuring combination of both monocular vision and laser speckle is used. In this paper, the theoretical principle of displacement measurement is first presented by a combination of monocular vision and laser speckle. Then, a model between object displacement and CCVLSC (particularly, [Formula: see text] coordinate value) is derived. Finally, a denoising algorithm with competitive protection of contour effective points is proposed, on the basis of effects of noises coming from background and contour edge on CCVLSC. The algorithm includes ellipse fitting to laser speckle contour, calculating offsets between all contour points and the fitted eclipse, eliminating noise points with higher deviation (generally about 5% of all contour points) by using competitive strategy, ellipse refitting, and recalculating and re-eliminating until the deviation is below a specified threshold. It is shown that the algorithm can not only eliminate the fixed noise points in each round but also protect the number of effective points to the greatest extent. Finally, the feasibility of the algorithm is verified by two ways. One is an ideal data validation. It proves that the algorithm can guarantee the convergence towards the ideal center coordinate value. Another is an experimental verification. An experimental system is built up based on the relationship between object displacement and Y coordinate value of CCVLSC for obtaining relevant dada. It is shown by the comparison between predictions and experimental data that the algorithm has a better robustness and a higher accuracy of distance measurement than other typical algorithms.