典型文献
Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images
文献摘要：
The three-dimensional(3D) model is of great significance to analyze the performance of nonwovens. However, the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost. A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images. A convolutional neural network was trained to extract clear fibers from sequence images. Image processing algorithms were used to obtain the radius, the central axis, and depth information of fibers from the extraction results. Based on this information, 3D models were built in 3D space. Furthermore, self-developed algorithms optimized the central axis and depth of fibers, which made fibers more realistic and continuous. The method with lower cost could reconstruct 3D models of nonwovens conveniently.
文献关键词：
中图分类号：
作者姓名：
DONG Gaige;WANG Rongwu;LI Chengzu;YOU Xiangyin
作者机构：
College of Textiles,Donghua University,Shanghai 201620,China;Jiangsu Liyang New Material Co.,Ltd.,Nantong 226004,China
文献出处：
引用格式：
[1]DONG Gaige;WANG Rongwu;LI Chengzu;YOU Xiangyin-.Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images)[J].东华大学学报（英文版）,2022(03):185-192
A类：
Nonwovens,nonwovens
B类：
Three,Dimensional,Model,Reconstruction,from,Multi,Focus,Images,three,dimensional,great,significance,analyze,performance,However,existing,modelling,methods,could,not,reconstruct,structure,cost,new,deep,learning,was,proposed,models,multi,focus,images,convolutional,neural,network,trained,clear,fibers,sequence,processing,algorithms,were,used,obtain,radius,central,axis,depth,information,extraction,results,Based,this,built,space,Furthermore,self,developed,optimized,which,made,realistic,continuous,lower,conveniently
AB值：
0.540922
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机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
