Please use this identifier to cite or link to this item:
Title: Recoloring textile fabric images based on improved fuzzy clustering
Authors: Zou, Z
Shen, HL
Du, X
Shao, SJ 
Xin, JH 
Keywords: Coloration
Color theme design
Textile fabric image
Fuzzy clustering
Image segmentation
Issue Date: 2017
Publisher: John Wiley & Sons
Source: Color research & applications, 2017, v. 42, no. 1, p. 115-123 How to cite?
Journal: Color research & applications 
Abstract: This article proposes a new recoloring method for textile fabric images based on improved fuzzy local information c-means (FLICM) clustering. In the clustering algorithm, the fuzzy factor was modified so that it can produce reliable segmentation in areas with rich details. With the obtained cluster labels and pixel-wise memberships, the color of each pixel is modeled as the linear combination of the two most dominant colors. The recoloring process was then conducted by replacing the specified dominant color with user-provided target colors. Experimental results showed that the proposed method can produce natural and faithful color appearance on both printed and yarn-dyed fabric images, and outperforms the state-of-the-art.
ISSN: 0361-2317
EISSN: 1520-6378
DOI: 10.1002/col.22023
Appears in Collections:Journal/Magazine Article

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


Citations as of Nov 28, 2018

Page view(s)

Last Week
Last month
Citations as of Dec 9, 2018

Google ScholarTM



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