基于卷积神经网络的楚国纺织品服装元素迁移

Element Migration of Textiles and Clothing in Chu State based on Convolutional Neural Network

文章以楚国纺织品为研究对象,通过目标内容图轮廓提取和线条增强,生成具有楚国纺织品风格的图像;提出基于VGG-19优化模型的楚国纺织品纹样图像迁移方法,克服了图案组合创新设计、自动提取数量少和资源大量损耗等困难。研究表明:该算法在楚国纺织品风格迁移中的表现优于现有方法,保留了纺织品艺术风格的完整性,并成功地将迁移的纹样应用到不同的服装品类中,有利于传承和发展中国优秀传统服饰文化,为服装设计者降低了试错成本并提供新的思路。

This paper takes Chu textile as the research object.An image with Chu textile style is generated by extracting the contours of the target content diagram and enhancing the lines.An image migration method of Chu textile pattern based on VGG-19 optimization model is presented.Overcame the difficulties of innovative design of pattern combination,low number of automatic extraction and large loss of resources.The results show that this algorithm is better than the existing method in Chu textile style migration.The integrity of the textile art style is preserved.The transplanted patterns were successfully applied to different clothing types.It is conducive to the inheritance and development of China's excellent traditional clothing culture.It reduces the cost of trial and error and provides new ideas for clothing designers.