Fast Self-Adaptive Digital Camouflage Design Method Based on Deep Learning

Houdi Xiao,Zhipeng Qu,Ruiru Qin,Chuanzhi Wang,Yi Jiang,Mingyun Lv

doi:10.3390/app10155284

Abstract

Traditional digital camouflage is mainly designed for a single background and state. Its camouflage performance is appealing in the specified time and place, but with the change of place, season, and time, its camouflage performance is greatly weakened. Therefore, camouflage technology, which can change with the environment in real-time, is the inevitable development direction of the military camouflage field in the future. In this paper, a fast-self-adaptive digital camouflage design method based on deep learning is proposed for the new generation of adaptive optical camouflage. Firstly, we trained a YOLOv3 model that could identify four typical military targets with mean average precision (mAP) of 91.55%. Secondly, a pre-trained deepfillv1 model was used to design the preliminary camouflage texture. Finally, the preliminary camouflage texture was standardized by the k-means algorithm. The experimental results show that the camouflage pattern designed by our proposed method is consistent with the background in texture and semantics, and has excellent camouflage performance in optical camouflage. Meanwhile, the whole pattern generation process takes a short time, less than 0.4 s, which meets the camouflage design requirements of the near-real-time camouflage in the future.

Highlights

Camouflage is the most common and effective means to combat military reconnaissance [1,2].It can conceal military equipment in natural environments
The camouflage technology, which can change with the environment in real-time has become the inevitable direction of the development of the military camouflage field
Note that all images above have the same resolution. This difference is due to the camouflage texture designed by the method in literature [5] being inconsistent with the background texture and semantics, while the texture designed by the method we provide is consistent with the background texture and semantics

Summary

Introduction

Camouflage is the most common and effective means to combat military reconnaissance [1,2]. It can conceal military equipment in natural environments. The traditional way of realizing digital camouflage is to coat the equipment surface with camouflage paint according to the designed camouflage texture or to wear or cover the fabric with camouflage texture. The camouflage technology, which can change with the environment in real-time has become the inevitable direction of the development of the military camouflage field. To realize multi-region adaptive camouflage, texture and color must not be fixed, real-time camouflage texture is designed according to the changes in the environment.

Methods

Results

Discussion

Conclusion