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Imitation camouflage synthesis based on shallow neural network

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Abstract

Deep learning technology has been widely used in the military field, which have achieved great success. The traditional method for painting camouflage either using the background information or the artificial pattern. None of the traditional methods can both consider the background information and camouflage rules. In this paper, a new automatic camouflage generation framework is proposed. A method for generating camouflage pattern is designed. The imitation camouflage pattern is synthesized from the features of both background and artificial pattern. In our method, the texture feature of both background and traditional pattern patches are extracted from the feature maps of shallow neural network (SNN). Based on the feature maps, statistic information of second order differential and mean subtracted contrast normalized coefficients for texture and color is extracted. By iterating to optimize the imitation camouflage to be generated, the statistical information of the imitation camouflage can approximate the characteristic statistical information of the background and pattern. The new generated camouflage pattern can contain the color and texture information of background; besides, it can maintain the traditional patch camouflage criteria. Our approach makes camouflage painting more flexible and allows the target to better infuse into the background. And our method is designed for the preparation of painting camouflage.

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Data availability

The texture data that support the findings of this study are available in http://www.cgtextures.com/.

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Acknowledgements

The authors would like to express sincere gratitude to National Natural Science Foundation of Shaanxi Province (Grant No. 2020SF-377) for providing fund for conducting experiments, and also the National Key Laboratory of Lightning Protection and Electromagnetic Camouflage for its support.

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    Authors and Affiliations

    1. School of Electronic Engineering, Xi’an University of Post and Telecommunications, Changan, Xi’an, 710121, Shaanxi, China

      Cai Xiuxia & Du Shuaibin

    2. National Key Laboratory of Lightning Protection and Electromagnetic Camouflage, Army Engineering University of PLA, Houbiaoying, Nanjing, 210007, Jiangsu, China

      Zhang Pin

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    1. Cai Xiuxia
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    Contributions

    Xiuxia Cai wrote the main mauscript text. Pin Zhang prepared all the figures of this paper. Shuaibin Du prepared all the tables. All authors reviewed the manuscript.

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    Correspondence to Zhang Pin.

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    Communicated by J. Gao.

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    Xiuxia, C., Pin, Z. & Shuaibin, D. Imitation camouflage synthesis based on shallow neural network. Multimedia Systems 29, 2705–2714 (2023). https://doi.org/10.1007/s00530-023-01149-z

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