Abstract: Aiming at the problems of low manual extraction efficiency of traditional ethnic pattern
symbols as well as the difficulty of designing creative graphic combination, this paper proposed an
innovative model of traditional ethnic pattern style by taking the batik and cross-stitch work of the
Miao nationality as an example. This model combined the improved shape grammar with neural style
transfer network based on deep learning, to extract e and encode ethnic pattern configuration frames.
Then, a large number of innovative ethnic patterns was generated through shape grammars, and the
basic features of ethnic patterns was extracted quickly using the style-transfer network, so as to
transfer and generate innovative ethnic pattern designs based on this framework. The experimental
results show that the model can generate brand-new ethnic ornament patterns on the basis of the
specified frame, which are more orderly than those generated directly by means of the neural network
transfer. The generated pattern will finally be applied to the design of the Miao fabric patterns, which
verifies the feasibility of this method and design process.

Key words: convolutional neural network, shape grammar, neural style transfer, cross stitch, batik