Journal of Textile Research ›› 2019, Vol. 40 ›› Issue (06): 111-116.doi: 10.13475/j.fzxb.20180600506

• Management & Information • Previous Articles     Next Articles

Weft knitted fabric appearance simulation using colored spun yarn image

WU Yilun, LI Zhongjian, PAN Ruru, GAO Weidong(), ZHANG Ning   

  1. Key Laboratory of Eco-Textiles(Jiangnan University), Ministry of Education, Wuxi, Jiangsu 214122, China
  • Received:2018-06-01 Revised:2019-03-08 Online:2019-06-15 Published:2019-06-25
  • Contact: GAO Weidong E-mail:gaowd3@163.com

RichHTML

3

PDF (PC)

62

Abstract:

In order to solve the time-consuming and labor-consuming problems caused by the prediction of fabric surface color of spun yarn knitwear products by making samples, a method for the simulation of knitted fabric appearance by using real spun yarn image was proposed. Firstly, image processing technology was adopted to preprocess the color images of the collected yarns, comprising image segmentation, morphological operations and closed operations to acquire the main binary image of the color spinning yarns, and the boundary and center line of the yarn main body were obtained. Furthermore, the main part of the original yarn image was obtained. Then, using the improved Peirce loop model, the texture information of the true colored spun yarn was mapped onto the geometric model of the loop. Finally, according to the established fabric structure transformation model, the coverage relationship of the loop was changed to complete simulation of weft knitted fabrics. Simulation results show that the proposed simulation algorithm can rapidly and accurately simulate the effect of different density and different yarn fabric cloth, which is consistent with the real scan fabric visual effect, thus, it is expected to replace physical proofing.

Key words: colored spun yarn, image processing, loop model, texture mapping, appearance simulation

CLC Number: 

  • TS181.8

Fig.1

Yarn image acquisition device"

Fig.2

Three color background board"

Fig.3

Calibration image"

Fig.4

Cropped colored spun yarn image"

Fig.5

Image acquisition and preprocessing. (a) Gray scale image; (b) Binary image;(c) Subject binary image; (d) Yarn body image"

Fig.6

Loop geometry model"

Fig.7

Yarn information mapping principle. (a) Yarn centerline and border; (b) Loop model needle arc section"

Fig.8

Loop simulation image. (a) Interpolation of front loop image; (b) Interpolated loop image"

Fig.9

Loop cover. (a) Not covered; (b) Covered processing"

Fig.10

Simulation results of colored spun yarn fabric. (a) Simulation image;(b) Physical image"

Fig.11

Comparison of simulated images with different densities. (a)Low density;(b)High density"

Fig.12

Simulation and physical map of different colored spun yarns. (a) Simulation image;(b) Physical image"

[1] 吴周镜, 宋晖, 李柏岩, 等. 纬编针织物在计算机中的三维仿真[J]. 东华大学学报 (自然科学版), 2011,37(2):210-214.
WU Zhoujing, SONG Hui, LI Boyan, et al. Three-dimensional simulation of weft knitted fabrics in computers[J]. Journal of Donghua University(Natural Science Edition), 2011,37(2):210-214.
[2] 吴周镜. 无缝针织物的织物外观模拟技术的研究与实现[D]. 上海:东华大学, 2010: 25-40.
WU Zhoujing. Research and realization of fabric appearance simulation technology for seamless knitted fabrics[D]. Shanghai: Donghua University, 2010: 25-40.
[3] DEMIROZ A, DIAS T. A study of the graphical representation of plain-knitted structures: part II: experimental studies and computer generation of plain-knitted structures[J]. Journal of the Textile Institute Proceedings & Abstracts, 2000,91(4):481-492.
[4] 于斌成, 李柏岩, 刘晓强, 等. 一种增强模拟纬编针织物外观真实感的方法[J]. 东华大学学报(自然科学版), 2013,39(5):644-649.
YU Bincheng, LI Baiyan, LIU Xiaoqiang, et al. A method to enhance the realistic appearance of simulated weft knitted fabrics[J]. Journal of Donghua Univer-sity(Natural Science Edition), 2013,39(5):644-649.
[5] 张宁, 李忠健, 潘如如, 等. 采用色纺纱图像的真实感色织物模拟[J]. 纺织学报, 2017,38(5):37-42.
ZHANG Ning, LI Zhongjian, PAN Ruru, et al. Simulation of real color fabrics using color spinning images[J]. Journal of Textiles Research, 2017,38(5):37-42.
[6] 祝成炎. 计算机模拟织物外观的一种方法研究[J]. 丝绸, 1996(6):41-43.
ZHU Chengyan. A method for computer simulation of the appearance of fabrics[J]. Journal of Silk, 1996(6):41-43.
[7] 沙莎, 蒋高明. 纬编针织物三维模拟技术的研究现状与发展趋势[J]. 纺织学报, 2016,37(11):166-172.
SHA Sha, JIANG Gaoming. Research status and development trend of 3D simulation technology for weft knitted fabrics[J]. Journal of Textiles Research, 2016,37(11):166-172.
[8] 李忠健, 潘如如, 高卫东. 应用纱线序列图像的电子织物构建[J]. 纺织学报, 2016,37(3):35-40.
LI Zhongjian, PAN Ruru, GAO Weidong. Construction of electronic fabrics using yarn sequence images[J]. Journal of Textiles Research, 2016,37(3):35-40.
[9] 张继东, 薛元, 张杰, 等. 应用混色纱纹理信息的纬编针织物模拟[J]. 纺织学报, 2017,38(7):148-154.
ZHANG Jidong, XUE Yuan, ZHANG Jie, et al. Weft knitted fabric simulation using textured yarn texture information[J]. Journal of Textile Research, 2017,38(7):148-154.
[10] 王辉, 方园, 潘优华. 纬编针织物线圈模型的分析与研究[J]. 浙江理工大学学报, 2008,25(5):521-525.
WANG Hui, FANG Yuan, PAN Youhua. Analysis and research on the weft knitted fabric loop model[J]. Journal of Zhejiang Institute of Technology, 2008,25(5):521-525.
[11] 居婷婷. 毛衫织物线圈结构建模与仿真研究[D]. 杭州:浙江理工大学, 2012: 30-35.
JU Tingting. Structure modeling and simulation of sweater fabric loop[D]. Hangzhou: Zhejiang Sci-Tech University, 2012: 30-35.
[12] LEAF G A V, GLASKIN A. The geometry of a plain knitted loop[J]. Journal of the Textile Institute Transactions, 2013,46(9):587-605.
[13] 吴义伦, 潘如如, 高卫东. 云纹纱纬编针织物外观模拟[J]. 丝绸, 2019,56(2):37-42.
WU Yilun, PAN Ruru, GAO Weidong. Appearance simulation of weft knitted fabric with cloud yarn[J]. Journal of Silk, 2019,56(2):37-42.
[1] ZHANG Zhengye, XIN Binjie, DENG Na, CHEN Yang, XING Wenyu. Research and application of algorithm for measuring hemp fiber cross-sectional parameters based on boundary tracking [J]. Journal of Textile Research, 2020, 41(02): 39-43.
[2] . Color shading detection and rating system for denim based on computer vision [J]. Journal of Textile Research, 2019, 40(05): 163-169.
[3] . Identification and application of yarn hairiness using adaptive threshold method under single vision [J]. Journal of Textile Research, 2019, 40(05): 150-156.
[4] . Defect detection of cheese yarn based on multi-scale multi-direction template convolution [J]. Journal of Textile Research, 2019, 40(04): 152-157.
[5] . Coloration rules between colored spun yarns and its fabrics based on spectral pan-similarity measure#br# [J]. Journal of Textile Research, 2019, 40(02): 30-37.
[6] . Research progress of computer color matching for colored spun yarn [J]. Journal of Textile Research, 2018, 39(11): 176-184.
[7] . Detection and evaluation on yarn hairiness of blackboard with image processing [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(08): 144-149.
[8] . Position recognition of spinning yarn breakage based on convolution neural network [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(06): 136-141.
[9] . Detecting method of foreign fibers in seed cotton based on deep-learning [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(06): 131-135.
[10] . Spinning breakage detection based on optimized hough transform [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(04): 36-41.
[11] . Stitch design and deformation simulation of cardigan based on loop model [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(04): 151-157.
[12] . Application of algorithm with improved frequency-tuned salient region [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(03): 154-160.
[13] . Global and local diversity features-fused colorimetry index testing and evaluation of colored spun yarns [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(02): 157-164.
[14] . On-line yarn cone defects detection system based on machine vision [J]. JOURNAL OF TEXTILE RESEARCH, 2018, 39(01): 139-145.
[15] . Rapid identification method of cashmere and wool based on bag-of-visual-word [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(07): 130-134.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
京ICP备14006648号
Copyright 2021 © Editorial office of Journal of Textile Research
Supported by Beijing Magtech Co.Ltd