基于U2Net神经网络的博物馆文创产品设计方法研究
王嘉玥 1夏雅琴1
作者信息
摘要
针对手动提取图像细节时局部的缺失问题,文章提出一种基于U2Net神经网络算法的图像外轮廓提取技术,并将其运用于河南博物院文创产品的数字化分析设计上.此方法从编码器提取妇好鴞尊图像特征,利用解码器基于这些特征生成分割图,大大节约设计师手动提取文物元素造型的时间效率.
Abstract
To solve the problem of partial missing when manually extracting image details,this paper proposes an image contour extraction technology based on U2Net neural network algorithm,and applies it to the digital analysis and design of cultural and creative products of Henan Museum.This method extracts image features from the encoder and uses the decoder to generate segmentation maps based on these features,which greatly saves the time efficiency of manual extraction of cultural relics element modeling,facilitates the subsequent design work of designers.
关键词
博物馆文创/神经网络/语义图像分割/文创设计Key words
museum cultural creation/neural network/semantic image segmentation/cultural creation design引用本文复制引用
出版年
2024
NETL
NSTL
万方数据