Manipulating existing camouflage patterns is a challenging issue in the process of camouflage pattern design. In this article, we present an effective approach based on the neural style transfer method to generate a hybrid camouflage pattern by manipulating two given camouflage patterns. Using a convolutional network trained on image recognition, content and style are represented by the correlations between feature maps in several layers of the network. In this regard, we utilized different commonly used camouflage patterns as content and style images. Then, by performing the style transfer algorithm on selected camouflage patterns, a new hybrid camouflage pattern was generated. The hybrid pattern inherits the appearance features of the content and the style images. Also, the colors of the hybrid pattern were controlled by carefully selecting the input colors. It was concluded that the proposed method is useful for adding or deleting some features of an existing camouflage pattern. In fact, it is a professional tool for pixelating, depixelating, blurring, and gradual coloring of camouflage patterns. Furthermore, we demonstrate the effectiveness of hybrid camouflage patterns using visual assessment. The results of the subjective assessment show that the proposed method is efficient for generating successful camouflage patterns.

中文翻译：

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使用神经风格迁移方法生成混合迷彩图案

操纵现有迷彩图案是迷彩图案设计过程中的一个具有挑战性的问题。在本文中，我们提出了一种基于神经风格迁移方法的有效方法，通过操纵两个给定的迷彩图案来生成混合迷彩图案。使用经过图像识别训练的卷积网络，内容和风格由网络几层中的特征图之间的相关性表示。在这方面，我们利用不同的常用迷彩图案作为内容和风格图像。然后，通过对选定的迷彩图案执行风格转移算法，生成了一种新的混合迷彩图案。混合模式继承了内容和风格图像的外观特征。还，通过仔细选择输入颜色来控制混合图案的颜色。得出的结论是，所提出的方法对于添加或删除现有迷彩图案的某些特征很有用。事实上，它是一款专业的迷彩图案像素化、去像素化、模糊化、渐变着色工具。此外，我们使用视觉评估证明了混合迷彩图案的有效性。主观评估的结果表明，所提出的方法对于生成成功的伪装图案是有效的。我们使用视觉评估证明了混合迷彩图案的有效性。主观评估的结果表明，所提出的方法对于生成成功的伪装图案是有效的。我们使用视觉评估证明了混合迷彩图案的有效性。主观评估的结果表明，所提出的方法对于生成成功的伪装图案是有效的。