Research on laser center positioning under CV model segmentation

Abstract

Spot positioning accuracy is an important index of laser processing system and ranging system. When the laser spot is noisy or the gray level is not uniform, the positioning accuracy is easily affected. Aiming at the above problems, this paper proposes a laser spot segmentation method based on the Chan-Vese model, which can improve the accuracy of spot center localization in combination with the gray centroid method. Firstly, the laser spot image is decomposed by two-dimensional wavelet, and the high-frequency component is suppressed by soft threshold function to eliminate the noise in the laser spot image. Secondly, the level set algorithm based on Chan-Vese model is used to segment the laser spot image with adaptive improvement of the initial coordinates of the evolution curve. Finally, the center coordinates are calculated inside the segmentation curve using the gray centroid method. Experimental results show that the method is more accurate and robust.