基于循环生成对抗网络算法的迷彩服图案设计

IF 0.6 4区 工程技术 Q4 MATERIALS SCIENCE, TEXTILES AATCC Journal of Research Pub Date : 2023-09-25 DOI:10.1177/24723444231185633
Min Li, Miao Yu, Bingqing Liu, Qinglong Peng
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引用次数: 0

摘要

迷彩是军事侦察中必不可少的防护手段。然而,传统的迷彩图像生成方法不允许端到端生成。本文采用的循环生成对抗网络算法既能保持原始图片的特征,又能实现端到端生成,能更好地解决季节性问题。利用循环GAN的循环对抗博弈概念训练生成模型和判别模型。在训练过程中,损失函数的作用是刺激背景图像和伪装图像相互映射。将生成的图像捕获到识别模型中进行识别,从而对发现结果进行反馈。最后输出具有背景图像特征的伪装图像,实现端到端伪装图像的生成。伪装评价指标用于检测实验输出图像的颜色、纹理和边缘质量。生成的图像在颜色、纹理、边缘对比等方面都表现出良好的伪装效果,验证了实际方案的有效性。
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The Pattern Design of A Camouflage Suit Based on the Cycle Generative Adversarial Network Algorithm
Camouflage refers to an essential means of protection for military reconnaissance. However, the traditional method of camouflage image generation does not allow for end-to-end generation. The algorithm of Cycle Generative Adversarial Network adopted in this article can not only keep the features of original pictures but also realize the end-to-end generation, which can better solve seasonal problems better. The generation model and the discrimination model are trained using the concept of the cyclic confrontation game of Cycle GAN. In the training process, the loss function served to stimulate the background image and camouflage images mapping to each other. The generated image is captured into the recognition model for recognition, so as to provide feedback on the findings. Finally, the camouflage image with background image characteristics is output to realize the generation of an end-to-end camouflage image. The camouflage evaluation index is used to detect the quality of color, texture, and edge of the experimental output image. The generated image shows a good camouflage effect in the color, texture, and comparison of edges, thus verifying the effectiveness of the practical scheme.
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来源期刊
AATCC Journal of Research
AATCC Journal of Research MATERIALS SCIENCE, TEXTILES-
CiteScore
1.30
自引率
0.00%
发文量
34
期刊介绍: AATCC Journal of Research. This textile research journal has a broad scope: from advanced materials, fibers, and textile and polymer chemistry, to color science, apparel design, and sustainability. Now indexed by Science Citation Index Extended (SCIE) and discoverable in the Clarivate Analytics Web of Science Core Collection! The Journal’s impact factor is available in Journal Citation Reports.
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