基于深度神经网络的唐卡的色彩风格特征提取

Color Style Feature Extraction of Thangka Based on Depth Neural Network

唐卡是一门以表现宗教题材为主的重彩装饰绘画艺术,其用色上强调对比,讲究色彩富丽,追求金碧辉煌的效果,这些灿烂的色彩给人以视觉的冲击和心灵的震撼。其原始使命服务于宗教,取材于经文,通过精美的绘制,成了一件件精致的艺术品。唐卡的内容、颜色、造型等诸多方面也都为当今的为绘画艺术的发展提供了多种借鉴意义,但是其博大精深难以复制。图像风格迁移指利用给定的内容图与风格图生成同时具有内容特征和艺术风格特征的风格迁移图,基于神经网络的深度学习技术推动了图像风格迁移的研究。本文借助当前在视觉领域中快速发展的深度神经网络方法,对唐卡的色彩特征进行分析,并且提取唐卡色彩的色彩特征,为唐卡的整体风格转移研究提供新的方法。利用该方法在图像数据上进行实验,该方法能够高效、快速并自然地实现唐卡的全部风格迁移。

Thangka is an art of decorative painting with religious themes. It emphasizes contrast in color, pays attention to rich colors, and pursues resplendent effects. These brilliant colors give people visual impact and spiritual shock. Its original mission is to serve religion, draw materials from scriptures, and become exquisite works of art through exquisite painting. The content, color, shape and many other aspects of Thangka also provide a variety of reference for today’s development of painting art, but it is profound and difficult to copy. Image style transfer refers to the generation of style transfer map with both content and artistic style features by using the given content map and style map. The deep learning technology based on neural network promotes the research of image style transfer. This paper analyzes the color features of Thangka with the help of the depth neural network method which is developing rapidly in the field of vision, and extracts the color features of Thangka, which provides a new method for the research of the overall style transfer of Thangka. Using this method to conduct experiment on image data, this method can realize all style transfer of Thangka efficiently, quickly and naturally.