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DOI: 10.14569/IJACSA.2022.01309113
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Recognition Method of Dim and Small Targets in SAR Images based on Machine Vision

Author 1: Qin Dong

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 9, 2022.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Aiming at the problems of long recognition time and low recognition accuracy of traditional SAR image dim target recognition methods, a method of SAR image dim target recognition based on machine vision was proposed. SAR images are collected and preprocessed by machine vision, and the image information is processed by PCA dimension reduction considering the linear characteristics of the data to extract image features. Then, the SAR image target feature key frame frequency band is divided by the segmentation results, and the recognition model is established based on the image trajectory tracking and target analysis. The proposed algorithm is applied and analyzed. The simulation results show that the proposed algorithm has good recognition rate, average recognition rate and false detection rate are 99% and 0.9%, and can effectively ensure the data processing performance.

Keywords: Machine vision; SAR image; Weak target; PCA linear dimensionality reduction method; key frame frequency band

Qin Dong, “Recognition Method of Dim and Small Targets in SAR Images based on Machine Vision” International Journal of Advanced Computer Science and Applications(IJACSA), 13(9), 2022. http://dx.doi.org/10.14569/IJACSA.2022.01309113

@article{Dong2022,
title = {Recognition Method of Dim and Small Targets in SAR Images based on Machine Vision},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.01309113},
url = {http://dx.doi.org/10.14569/IJACSA.2022.01309113},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {9},
author = {Qin Dong}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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