@article{sun_fast_2023,
	title = {Fast textile pattern generation combining {MRF}-based and {Gram}-based methods},
	volume = {74},
	issn = {12225347},
	url = {http://revistaindustriatextila.ro/images/2023/4/009%20YUEXIN%20SUN%20INDUSTRIA%20TEXTILA%20no.4_2023.pdf},
	doi = {10.35530/IT.074.04.202254},
	abstract = {Textile pattern design is a tedious and challenging task for designers. This paper proposes a fast textile pattern
generation algorithm that combines MRF-based and Gram-based methods. First, the reconstruction method based on
image optimisation is determined after analysing the specific requirements of textile pattern design. The pre-trained
VGG19 is selected as the style feature extraction neural network. Then, we compare the generation results of various
combinations of style loss functions and propose a multi-resolution image optimisation method. Finally, the smoothing
loss and colour histogram matching are added to improve the generation quality further, thus constructing an image
generation algorithm for textile pattern design. Experimental results demonstrate that our algorithm can effectively
generate complex textile patterns with global style and local detail features. The average image generation time is 575s,
over 84.3\% faster than traditional algorithms. At the same time, this algorithm is convenient for switching styles and
requires lower computational capability. It can improve pattern design efficiency and promote the application of image
generation technology in textile design.},
	number = {04},
	urldate = {2023-09-03},
	journal = {Industria Textila},
	author = {Sun, Yuexin and Chen, Yu},
	month = aug,
	year = {2023},
	pages = {439--445},
}