Research on image segmentation algorithm based on automatic beetle antennae search and K-means clustering

In machine recognition, image segmentation is an important step, and traditional segmentation methods have certain defects. In this paper, the initial cluster center sensitive defects of traditional K-means clustering segmentation are optimized, and the Automatic Beetle Antennae Search (ABASK) is used to avoid this problem. The experimental results show that the ABASK segmentation of the image can not only ensure the segmentation of the image contour, but also preserve the image details.