Optical metrology has experienced a fast development in recent years—cross laser-pattern has become a common cooperative measuring marker in optical metrology equipment, such as infrared imaging equipment or visual 3D measurement system. The rapid and accurate extraction of the center point and attitude of the cross-marker image is the first prerequisite to ensure the measurement speed and accuracy. In this paper, a cross laser-pattern is used as a cooperative marker, in view of the high resolution of the cross laser-pattern image in the project and the vulnerability to adverse environmental effects, such as stray light, smoke, water mist and other interference in the environment, resulting in poor contrast, low signal-to-noise ratio (SNR), uneven energy distribution. As a result, a method is proposed to detect the center point and attitude of cross laser-pattern image based on Gaussian fitting and least square fitting. Firstly, the distortion of original image is corrected in real time, the corrected image is smoothed by median filter, and the noise is suppressed while preserving the edge sharpness and detail of the image. In order to adapt to different environments, the maximum inter-class variance method of threshold automatic selection is used to determine the threshold of image segmentation to eliminate the background interference caused by different illumination intensities. To improve the real-time performance of the algorithm, the four cross laser edge pixels are obtained by line search, and then fitted by least square. With the edge lines, the transverse and portrait line of the cross-laser image are separated, then we calculate Gaussian center points of all Gaussian sections of transverse and portrait lines based on Gaussian fitting method, respectively. Based on the traditional line fitting method, the sub-pixel center of the transverse and portrait laser strip images are fitted by removing the Outlying Points, and the center coordinates and attitude information of the cross laser-pattern are calculated by using the center equation of the laser strip, realizing cross laser-pattern center and attitude accurate positioning. The results show that the method is robust, the center positioning accuracy is better than 0.6 pixels, the attitude positioning accuracy is better than ±15” under smoke and water mist environment and the processing speed is better than 0.1 s, which meets the real-time requirements of the project.
Optical and visual measurement technology is used widely in fields that involve geometric measurements, and among such technology are laser and vision-based displacement measuring modules (LVDMMs). The displacement transformation coefficient (DTC) of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process, and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view (FFOV). To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands, a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV. First, an image coordinate system, a pixel measurement coordinate system, and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM. In addition, marker spots in the FFOV are selected, and the DTCs at the marker spots are obtained from calibration experiments. Also, a fitting method based on locally weighted scatterplot smoothing (LOWESS) is selected, and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots. Finally, the calibrated distribution functions of the DTCs are applied to the LVDMM, and experiments conducted to verify the displacement measurement accuracies are reported. The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than ±15 µm and ±19 µm, respectively, and that for oblique displacement is better than ±24 µm. Compared with the traditional calibration method, the displacement measurement error in the FFOV is now 90% smaller. This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV, and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.
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