Key algorithm based on threshold segmentation for attitude correction application in tactical training

Abstract

In recent years, image segmentation technology has developed rapidly and become a hot topic in the field of vision. However, image segmentation still suffers from problems such as extracting multiple targets to appear as crops. In order to better solve the problems brought by single-threshold image segmentation, a new method of multi-threshold image segmentation based on the grey wolf optimization algorithm is proposed. The method overcomes the inefficiency and low accuracy of manual image segmentation and the limitations of the single-threshold OTSU(Maximum interclass variance method) algorithm by using the grey wolf optimisation algorithm to optimise, selecting the optimal threshold for segmenting the image and binarise the image into several regions as well as regions of interest. The segmented image can be better used for posture correction for tactical training.