Multi-focus fusion with a new sharpness parameter for textile testing

2016 ◽  
pp. 329-332
Keyword(s):  
Textile Testing ◽  
Sharpness Parameter

Image Sharpness Enhancement for Textile Testing

AATCC Review ◽  
2018 ◽  
Vol 18 (2) ◽  
pp. 43-53
Author(s):  
Jinfeng Zhou ◽  
Lingjie Yu ◽  
Rongwu Wang ◽  
Bugao Xu
Keyword(s):  
Image Sharpness ◽  
Sharpness Enhancement ◽  
Textile Testing

scholarly journals A consumer-based textile quality scoring model using multi-criteria decision making

2019 ◽  
Vol 14 ◽  
pp. 155892501985477
Author(s):  
Romain Benkirane ◽  
Sébastien Thomassey ◽  
Ludovic Koehl ◽  
Anne Perwuelz
Keyword(s):  
Decision Making ◽  
Quality Criteria ◽  
Quality Score ◽  
Ranking Method ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Requirements Specifications ◽  
Textile Testing ◽  
Fuzzy Techniques ◽  
Hierarchy Process

In the clothing industry, the understanding of the quality is a major issue to well meet the customer needs. The dilemma that faces manufacturers is to find the balance between good quality and “overquality,” what the quality criteria are, and how to target requirements specifications. The aim of this study was to propose a multi-attribute ranking method of products. Ranking is based on an overall quality score. The quality score, here called consumer-based quality, is computed via the combination of textile testing and consumer perception to deterioration. Such a perception has been surveyed, and damage that can lead to end of life has been investigated. Collected data have been translated into a consumer sensitivity using multi-criteria decision making and fuzzy techniques. The fuzzy analytic hierarchy process has been used. Five damage categories have been weighted. A selection of appropriate tests according to standards has been completed to test the product resistance to the damage. The tests results have been computed with the consumer sensitivity to obtain the consumer-based quality score. Finally, the ranking method is applied on T-shirts, and a single score ranking is made possible and objectively depict perceived quality.

Machine vision of textile testing and quality research

2020 ◽  
Vol 38 (1) ◽  
pp. 319-325 ◽  
Author(s):  
Xiaomian Li ◽  
Yufeng Shu ◽  
Dali Zuo ◽  
Junhua Zhang ◽  
Zhanshuo Chen ◽  
...  
Keyword(s):  
Machine Vision ◽  
Quality Research ◽  
Textile Testing

Textile Testing in Germany

1948 ◽  
Vol 18 (1) ◽  
pp. 18-38 ◽  
Author(s):  
Herbert F. Schiefer ◽  
Lyman Fourt ◽  
Richard T. Kropf
Keyword(s):  
Textile Testing
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