A Preliminary Study on Artificial Intelligence-Based Camouflage Pattern Generation Method

DOI: https://doi.org/10.62517/jbdc.202501208

Author(s)

Qi Jia, Yuntao Li*

Affiliation(s)

College of Field Engineering, Army Engineering University of PLA, Nanjing, Jiangsu, China *Corresponding Author

Abstract

In response to the problems of time-consuming and ineffective manual design of existing camouflage patterns, efforts have been made to integrate artificial intelligence into camouflage design. Artificial intelligence driven camouflage pattern generation has been studied, and a comparative study of deep learning-based environment fusion image processing has been conducted. The research method is to use the AI image processing functions of several mainstream mobile phones to process images, so that the location of the target is fused with the surrounding environment. Then, camouflage design is carried out based on the processed target area, and the camouflage that can be generated by the target area processed by different AI algorithms is analyzed and compared. The experimental results show that compared to camouflage patterns designed in traditional ways, camouflage patterns designed based on artificial intelligence have outstanding advantages in camouflage performance, with better integration and matching with the environment. The minimum average brightness difference of AI processed images is only 4.52. Up to 90% of the participants in the evaluation believe that the image camouflage effect processed by AI is better than traditional methods.

Keywords

Artificial Intelligence, Camouflage, Color, Camouflage Effectiveness

References

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