[Retracted] An Empirical Study on the Artificial Intelligence‐Aided Quantitative Design of Art Images

Abstract

This paper presents an indepth analysis and research on the quantitative design of fine art images through artificial intelligence algorithms. A CycleGAN-based network model for automatic generation of sketches of fine art images is constructed to extract the edge and contour features of fine art images. The network uses 512 × 1024 high-resolution art images as input and Pitchman as a discriminator. To further enhance the sketch generation effect, a bilateral filtering algorithm is added to the generator model for noise reduction, and then a K -means algorithm is used for color quantization to solve the problem of cluttered lines in the generated sketches. The experimental results show that the network model can effectively realize the automatic generation of art image sketches and can retain the detailed part of the costume information well. A rendering platform is built to realize the application of art image generation algorithms and coloring algorithms. The platform integrates the functions of image preprocessing, sketch generation, and sketch coloring, demonstrates the results of the main research content of this paper, and finally increases the interest of the system through the rendering function of the art image grid, which further improves the practicality of the platform.

Animation Costume Style Migration Based on CycleGAN

“…The main work is to improve the processing method for the two problems in the introduction of this paper and propose a method that uses the combination of full convolutional network (FCN) and CycleGAN to realize the style migration of local targets of animated costumes, i.e., the instance style migration. (1) For the problem of background color change during migration, since CycleGAN is a style transformation of the whole animated costume, in the network, although it can learn the style of horses and zebras, the background information is also integrated in the training process. For this reason, the animated costumes to be style migrated are first semantically segmented using a full convolutional network, and then, the identified objects are style migrated, which adds a prerecognition network to CycleGAN.…”

“…In today's globalization, culture and art are the remarkable labels of the country and nation [1]. While facing the world and accepting the multiethnic culture of the world, how to make modern clothing keep Chinese national characteristics and style is the question we should think about now [2].…”

Ranking the art design and applications of artificial intelligence and machine learning

“…The platform is a combination of image processing, sketch generation, and coloring. 5 AI is playing a very important role in the advancements of educational activities. Cao 6 has employed AI virtual reality methodologies in the area of art education design for efficient learning activities in vocational art teaching schools.…”

“…For the study of applications of image generation and coloring models, a rendering platform was constructed. The platform is a combination of image processing, sketch generation, and coloring 5 . AI is playing a very important role in the advancements of educational activities.…”