Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31653
Title: Evaluating and predicting fabric bagging with image processing
Authors: Yeung, KW
Li, Y 
Zhang, X
Yao, M
Issue Date: 2002
Publisher: SAGE Publications
Source: Textile research journal, 2002, v. 72, no. 8, p. 693-700 How to cite?
Journal: Textile research journal 
Abstract: The aim of this work is to develop a method to evaluate garment bagging by image processing with different modeling techniques. Garment bagging is a kind of three-dimen sional residual deformation during wear, which can be characterized by a few parameters such as bagging height, volume, shape, and anisotropy. Traditional methods are limited to evalu ating bagging appearance by single parameters such as height, which cannot represent the abundant information given by the appearance of a bagged fabric. In this paper, we develop a method to evaluate fabric bagging from captured images of bagged fabrics by image processing and abstracting the criteria to recognize bagging magnitude. Based on an analysis of the intensity images, eight criteria are extracted to characterize the image features including bagging height, volume, and shape, and fabric surface patterns on bagging appearance. The criteria are used as variables in three predictive models. The work shows that bagging appearance can be predicted by the criteria extracted from the images of bagged fabrics.
URI: http://hdl.handle.net/10397/31653
ISSN: 0040-5175
EISSN: 1746-7748
DOI: 10.1177/004051750207200808
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

27
Citations as of Feb 26, 2017

WEB OF SCIENCETM
Citations

22
Last Week
0
Last month
1
Citations as of Aug 14, 2017

Page view(s)

31
Last Week
1
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.