Development and optimisation of image analysis technique for fabric buckling evaluation
Source abstract
Abstract
Purpose The purpose of this paper is to optimise parameters of digital image analysis to investigate the deformation behaviour of woven sample and to detect the onset and variation of wrinkling that occurs due to bias-tensioned fabric buckling. Design/methodology/approach Using models of predescribed shape, the relationship between the digitized gray scale intensities and wrinkles of the surface are analysed and conditions of specimen illumination and filtering procedures are chosen. Findings It is proposed to convert acquired images to binary to record the onset of buckling and to estimate critical buckling parameters of stretched woven samples. The threshold value is determined as mean value of approximated histogram of stretched specimen centre line. It is defined that profile curve and gray scale disperse presented by parameter CV can be used to obtain additional information and to compare behaviour of different samples during bias tension. Research limitations/implications Proposed image analysis technique allows detection of the onset of buckling wave formation and evaluation of surface waviness changes in woven samples different in colour and weave type tension. However, the behaviour of fabric samples with sharp multicoloured and complicated patterns cannot be assessed by gray scale imaging. Originality/value The proposed approach can be adjusted to investigate different wrinkling problems – buckling during simple shearing or picture frame test, seam puckering, draping.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Textile materials and evaluations · Optical measurement and interference techniques · Industrial Vision Systems and Defect Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Clothing and Polymer Products Technology, Faculty of Design and Technologies, Kaunas University of Technology, Kaunas, Lithuania
References (32)
Show source-provided references
1. Abouelela, A. , Abbas, H.M., Eldeeb, H., Wahdan, A.A. and Nassar, S.M. (2005), “Automated vision system for localizing structural defects in textile fabrics”, Pattern Recognition Letters, Vol. 26, pp. 1435-43.10.1016/j.patrec.2004.11.016 ↗
2. Abril, H.C. , Millan, M.S. and Valencia, E. (2008), “Influence of the wrinkle perception with distance in the objective evaluation of fabric smoothness”, Journal of Optics A: Pure and Applied Optics, Vol. 10, pp. 1-10.10.1088/1464-4258/10/10/104030 ↗
3. Evaluation of the basic low stress mechanical properties (bending, shearing and tensile)10.1108/09556220010377850 ↗
4. Behera, B.K. (2004), “Image-processing in textiles – a critical appreciation of recent developments”, Textile Progress, Nos 2-4.10.1080/00405160408689005 ↗
5. Analysis of fabric specimen aspect ratio and deformation mechanism during bias tension
6. Bekampienė, P. , Diliūnas, S., Domskienė, J. and Strazdienė, E. (2008), “Analysis of woven element deformation in fabric forming process”, Mechanika 2008: Proceedings of 13th International Conference, April 3-4, Technologija, Kaunas Lithuania, Kaunas, pp. 57-61.
7. Boisse, P. , Zouari, B. and Gasser, A. (2005), “A mesoscopic approach for the simulation of woven fibre composite forming”, Composite Science and Technology, Vol. 65, pp. 429-36.10.1016/j.compscitech.2004.09.024 ↗
8. Decrimping behavior of uncoated plain-woven fabrics subjected to combined biaxial tension and shear stresses10.1177/0040517507080258 ↗
9. Geometry of plain weave fabric under shear deformation. Part II: 3D model of plain weave fabric before deformation10.1080/00405000701830631 ↗
10. Geometry of plain weave fabric under shear deformation. Part III: 3D model of plain weave fabric before deformation10.1080/00405000701830326 ↗
11. Domskiene, J. and Strazdiene, E. (2005), “Investigation of fabric shear behaviour”, Fibers and Textile in Eastern Europe, Vol. 13, pp. 26-30.
12. Applying image analysis to automatic inspection of fabric density for woven fabrics10.1007/BF02875608 ↗
13. Seam pucker indicators and their dependence upon the parameters of a sewing machine10.1108/09556220810878856 ↗
14. Image analysis for quantifying marquisette damage in home laundering10.1177/0040517505053868 ↗
15. Lebrun, G. , Bureau, M.N. and Denault, J. (2003), “Evaluation of bias-extension and picture-frame test methods for the measurement if intraply shear properties of PP/glass commingled fabrics”, Composite Structures, Vol. 61, pp. 341-52.10.1016/S0263-8223(03)00057-6 ↗
16. A method of inspecting non-woven basis weight using the exponential law of absorption and image processing10.1177/0040517506060141 ↗
17. Prediction of post-buckling deformation in fabric drape10.1080/00405000701582547 ↗
18. Image analysis method of surface roughness evaluation10.1108/09556220710741650 ↗
19. Investigations of the relation between fabric mechanical properties and behaviour10.1108/09556220310478332 ↗
20. Peng, X.Q. , Cao, J., Chen, J., Xue, P., Lussier, D.S. and Liu, L. (2004), “Experimental and numerical analysis on normalization of picture frame test for composite materials”, Composite Science and Technology, Vol. 64, pp. 11-21.10.1016/S0266-3538(03)00202-1 ↗
21. Potluri, P. , Perez Ciurezu, D.A. and Ramgulam, R.B (2006), “Measurements of meso-scale shear deformations for modelling textile composites”, Composite: Part A, Vol. 37, pp. 303-14.10.1016/j.compositesa.2005.03.032 ↗
22. Comparison of hyperelastic material models in the analysis of fabrics10.1108/09556220610685249 ↗
23. Stylios, G. and Sotomi, J.O. (1993), “A new instrument for routine objective assessment of seam deformations in limp materials”, Laser Metrology and Machine Performance, Lamdamap 93, Computational Mechanics Publications, Blackshaw, pp. 233-8.
24. Grading of yarn appearance using image analysis and artificial intelligence technique10.1177/0040517506056868 ↗
25. Willems, A. , Lomov, S.V., Verpoest, I. and Vandepitte, D. (2009), “Drape-ability characterization of textile composite reinforcements using digital image correlation”, Optics and Lasers in Engineering, Vol. 47, pp. 343-51.10.1016/j.optlaseng.2008.03.012 ↗
26. Visualization of textile surface roughness based on silhouette image analysis10.1177/0040517508093779 ↗
27. Objective evaluation of fabric pilling using image analysis techniques10.1177/004051750207201204 ↗
28. Xue, P. , Cao, J. and Chen, J. (2005), “Integrated micro/macro-mechanical model of woven fabric composite under large deformation”, Composite Structures, Vol. 70, pp. 69-80.10.1016/j.compstruct.2004.08.013 ↗
29. A non-orthogonal constitutive model for characterizing woven composites10.1016/S1359-835X(02)00052-0 ↗
30. An experimental study of in-plain large shear deformation of woven fabric composite10.1016/j.compscitech.2006.08.011 ↗
31. Theoretical modelling of large shear deformation and wrinkling of plain woven composite10.1177/0021998308098237 ↗
32. Geometry of plain weave fabric under shear deformation. Part I: measurement of exterior positions of yarns10.1080/00405000701830474 ↗