Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary

Wu, Ying; Wang, Ren; Lou, Lin; Wang, Lali; Wang, Jun

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Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary

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oraz

28 wrz 2022

Fibres & Textiles in Eastern Europe

Tom 30 (2022): Zeszyt 3 (Październik 2022)

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Kategoria artykułu: Research Article

Data publikacji: 28 wrz 2022

Zakres stron: 33 - 40

DOI: https://doi.org/10.2478/ftee-2022-0020

Słowa kluczowe
fabric texture representation, sparse representation, weave repeat, defect detection, dictionary learning

This work is licensed under the Creative Commons Attribution 3.0 Public License.

Procedure of fabric characterisation and defect detection

Visual reconstruction samples with different dictionary sizes: (a) reconstruction of plain fabric image; (b) reconstruction of twill fabric image.

Representation result of the fabric samples with different dictionary sizes k: (a) PSNR; (b) SSIM

Representation results for two fabric samples: (a) and (b) are plain fabric's PSNR and SSIM for different patch sizes with various sparse cardinality T; (c) and (d) are twill fabric's PSNR and SSIM for different patch sizes with various sparse cardinality T

Original fabric sample with different weave patterns: (a) plain, (b) twill, (c) weft satin,(d) warp satin, (e) basket weave, (f) honeycomb, (g) compound twill, (h) diamond twill

Reconstructed fabric samples: (a) plain, (b) twill, (c) weft satin, (d) warp satin, (e) basket weave, (f) honeycomb, (g) compound twill, (h) diamond twill.

Representation results of all test samples; (a) PSNR, (b) SSIM

Texture period for various weave patterns, for every weave pattern, the left is warp period and the right is weft period

No. Sample	Plain		twill		warp satin		weft satin		basket weave		honey comb		compound twill		diamond twill
1	11	17	14	14	5	19	15	14	11	10	5	5	20	22	25	20
2	6	7	7	10	5	5	13	17	8	7	10	10	11	18	17	9
3	3	3	6	7	14	17	14	10	6	8	9	12	11	13	16	9
4	7	7	8	6	12	13	6	16	7	7	16	14	15	12	12	9
5	11	8	9	9	28	14	17	23	6	6	9	26	13	12	28	28
Average	8	8	9	9	13	14	13	16	8	8	10	13	14	15	20	15

Język:: Angielski

Częstotliwość wydawania:: Volume Open
Dziedziny czasopisma:: Biznes i ekonomia, Zarządzanie biznesem, Informatyka biznesowa, Zarządzanie procesem, Chemia przemysłowa, Celuloza, papier i tekstylia, Nauka i technologia polimerów, Nauka o materiałach, Biomateriały i materiały naturalne

Kanał RSS czasopisma

Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary

Kategoria artykułu: Research Article

Data publikacji: 28 wrz 2022

Zakres stron: 33 - 40

DOI: https://doi.org/10.2478/ftee-2022-0020

Słowa kluczowe
fabric texture representation, sparse representation, weave repeat, defect detection, dictionary learning

© 2022 Ying Wu, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 3.0 Public License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

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Fig. 7

Fig. 8

Fig. 9

Texture period for various weave patterns, for every weave pattern, the left is warp period and the right is weft period

Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary

Ying Wu

Ren Wang

Lin Lou

Lali Wang

Jun Wang

Kategoria artykułu: Research Article

Data publikacji: 28 wrz 2022

Zakres stron: 33 - 40

DOI: https://doi.org/10.2478/ftee-2022-0020

Słowa kluczowefabric texture representation, sparse representation, weave repeat, defect detection, dictionary learning

© 2022 Ying Wu, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 3.0 Public License.

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Texture period for various weave patterns, for every weave pattern, the left is warp period and the right is weft period

Słowa kluczowe
fabric texture representation, sparse representation, weave repeat, defect detection, dictionary learning