Three-Dimensional Model Reconstruction of Nonwovens from Multi-Focus Images

• Published in: 东华大学学报（英文版） Vol. 39; no. 3; pp. 185 - 192
• Main Authors: DONG Gaige, WANG Rongwu, LI Chengzu, YOU Xiangyin
• Format: Journal Article
• Language: English
• Published: College of Textiles,Donghua University,Shanghai 201620,China%Jiangsu Liyang New Material Co.,Ltd.,Nantong 226004,China 2022
• Subjects: image processing; deep learning; nonwoven; three-dimensional(3D) model reconstruction; microscopy
• ISSN: 1672-5220
• DOI: 10.19884/j.1672-5220.202106004

TS171; 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.