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Wyszukujesz frazę "Wang, Lali" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary
Autorzy:
Wu, Ying
Wang, Ren
Wang, Jun
Wang, Lali
Lou, Lin
Wydawca:
Sciendo
Cytata wydawnicza:
Ying Wu, Ren Wang, Lin Lou, Lali Wang and Jun Wang. "Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary ". Fibres & Textiles in Eastern Europe Sciendo, 30, no. 3 (2022): 33-40. https://doi.org/10.2478/ftee-2022-0020
Opis:
To achieve enhanced accuracy of fabric representation and defect detection, an innovative approach using a sparse dictionary with small patches was used for fabric texture characterisation. The effectiveness of the algorithm proposed was tested through comprehensive characterisation by studying eight weave patterns: plain, twill, weft satin, warp satin, basket, honeycomb, compound twill, and diamond twill and detecting fabric defects. Firstly, the main parameters such as dictionary size, patch size, and cardinality T were optimised, and then 40 defect-free fabric samples were characterised by the algorithm proposed. Subsequently, the impact of the weave pattern was investigated based on the representation result and texture structure. Finally, defective fabrics were detected. The algorithm proposed is an alternative simple and scalable method to characterise fabric texture and detect textile defects in a single step without extracting features or prior information.
This research was supported by the Zhejiang Provincial Natural Science Foundation of China under Grant No. LQ18E030007; National Natural Science Foundation of China under Grant No. 52003245; Science Foundation of Zhejiang Sci-Tech University (ZSTU) [17072156-Y]; Key Laboratory of Advanced Textile Materials and Manufacturing Technology (Zhejiang Sci-Tech University), Ministry of Education, and Zhejiang Provincial Key Laboratory of Fiber Materials and Manufacturing Technology under Grant number 2019QN05; National Experimental Teaching Center of Clothing and National Virtual Simulation Experimental Teaching Center of Clothing Design [zx20212007].
Dostawca treści:
Repozytorium Centrum Otwartej Nauki
Artykuł
Tytuł:
Local Characterisation and Detection of Woven Fabric Texture Based on a Sparse Dictionary
Autorzy:
Wu, Ying
Wang, Ren
Lou, Lin
Wang, Lali
Wang, Jun
Tematy:
fabric texture representation
sparse representation
weave repeat
defect detection
dictionary learning
Pokaż więcej
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
Powiązania:
https://bibliotekanauki.pl/articles/2172000.pdf  Link otwiera się w nowym oknie
Opis:
To achieve enhanced accuracy of fabric representation and defect detection, an innovative approach using a sparse dictionary with small patches was used for fabric texture characterisation. The effectiveness of the algorithm proposed was tested through comprehensive characterisation by studying eight weave patterns: plain, twill, weft satin, warp satin, basket, honeycomb, compound twill, and diamond twill and detecting fabric defects. Firstly, the main parameters such as dictionary size, patch size, and cardinality T were optimised, and then 40 defect-free fabric samples were characterised by the algorithm proposed. Subsequently, the Impact of the weave pattern was investigated based on the representation result and texture structure. Finally, defective fabrics were detected. The algorithm proposed is an alternative simple and scalable method to characterise fabric texture and detect textile defects in a single step without extracting features or prior information.
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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