Optical strip centerline extraction is an important part of a linear structured light measurement system. However, in the actual detection, to reduce noise and smooth the optical strip, the optical strip centerline extraction needs to be filtered, and the current Gaussian filter is used in image filtering. In this paper, an optical strip centerline compensation method based on a Gaussian filter is proposed. Firstly, the image Gaussian filter is qualitatively analyzed from the analytical and graphic directions, and then the approximate linear relationship between the offset of the optical strip centerline and the standard deviation of the filter as well as the shape of the optical strip is determined by numerical simulation. Through simulation and experiment, it is proved that the linear image filter compensation method can effectively compensate the offset of the center line of the optical strip by Gaussian filter, reduce the error of the optical strip center extraction, and improve the repeatability and accuracy of the measurement results.
Light strip extraction is important in a structured light measurement system. However, the extraction of light strip is incomplete, losing the information, in the detection of highly reflective surface. This paper presents an iterative threshold segmentation algorithm based on information entropy. Firstly, the image is initially segmented, then using the eightneighborhood detection to remove the noise and retain the light strip, after which the iterative segmentation is carried out with the inflection point of the information entropy of the extracted image as the termination condition to improve the integrity of the light strip segmentation and avoid the excessive segmentation of the background. Compared with the results of Otsu algorithm, the proposed method can retain more complete light strip information, with fewer breaking points.
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