Recoloring Textile Fabric Images Based on Improved Fuzzy Clustering

被引：4

作者：

Zou, Zhe ^{[1
]}

Shen, Hui-Liang ^{[1
]}

Du, Xin ^{[1
]}

Shao, Sijie ^{[2
]}

Xin, John H. ^{[2
]}

机构：

[1] Zhejiang Univ, Coll Informat Sci & Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China

[2] Hong Kong Polytech Univ, Inst Text & Clothing, Hong Kong, Hong Kong, Peoples R China

来源：

COLOR RESEARCH AND APPLICATION | 2017年 / 42卷 / 01期

基金：

中国国家自然科学基金;

关键词：

coloration; recoloring; color theme design; textile fabric image; fuzzy clustering; image segmentation; LOCAL INFORMATION; COLOR TRANSFER; SEGMENTATION; ALGORITHM;

D O I：

10.1002/col.22023

中图分类号：

O69 [应用化学];

学科分类号：

081704 ;

摘要：

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. (C) 2016 Wiley Periodicals, Inc. Published Online 11 January 2016 in Wiley Online Library (wileyonlinelibrary.com).

引用

页码：115 / 123

页数：9

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