Video SAR Moving Target Detection Method Based on Machine Vision

Authors

  • Wu Di
  • He Ming

DOI:

https://doi.org/10.59782/sidr.v3i1.129

Keywords:

Gaussian mixture model, adaptive threshold, HSV model, reflectivity, YOLO algorithm

Abstract

When detecting moving targets in video SAR, it is impossible to accurately obtain the moving targets in dynamic images. In order to solve the problems of low detection integrity and poor effectiveness, a video SAR moving target detection method based on machine vision is proposed. Firstly, the moving target pixel points are matched by the mixed Gaussian model to obtain the target area of the video SAR moving image; secondly, the HSV model and reflectivity algorithm are used to remove the shadows caused by the moving target; finally, the processed target area is input into the YOLO algorithm to complete the final video SAR moving target detection. Experimental results show that the proposed algorithm has high detection integrity, high detection rate, low false detection rate, and better detection effectiveness.

How to Cite

Di, W., & Ming, H. (2024). Video SAR Moving Target Detection Method Based on Machine Vision. Scientific Insights and Discoveries Review, 3, 129–135. https://doi.org/10.59782/sidr.v3i1.129