Recoloring textile fabric images based on improved fuzzy clustering

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.

Pattern‐driven color pattern recognition for printed fabric motif design

“…There are recoloring algorithms for manipulating textile color patterns, 2,8,9 adaptive algorithms for simulating plant decorative patterns, 10,11 symmetry groups theories for generating Islamic geometrical patterns, 12 Markov random field models for modeling trees, 13 near regular color texture manipulations for manipulating textures, 14 color pattern detection methods for reconstructing fabric images, 15 and so on. 16 Color pattern detection methods can be used to detect fabric color pattern parameters for fabric design 2,9 and quality control. 1,17 Zheng et al 2 use color transfer model and color mood model to extract color bias field and construct color themes for fabric color design.…”

“…At present, many researchers have tried to use computer‐aided design methods for developing color pattern designs from different angles. There are recoloring algorithms for manipulating textile color patterns, 2,8,9 adaptive algorithms for simulating plant decorative patterns, 10,11 symmetry groups theories for generating Islamic geometrical patterns, 12 Markov random field models for modeling trees, 13 near regular color texture manipulations for manipulating textures, 14 color pattern detection methods for reconstructing fabric images, 15 and so on 16 …”

“…Color pattern detection methods can be used to detect fabric color pattern parameters for fabric design 2,9 and quality control 1,17 . Zheng et al 2 use color transfer model and color mood model to extract color bias field and construct color themes for fabric color design.…”

Color pattern recognition for yarn‐dyed fabrics

“…Detection of interstices between weft and warp yarns could be conducted by using a modified K-means clustering approach. 7 Zhang et al 8 and Pan et al 9 adopted the Fuzzy C-means method and Zou et al 10 using the improved fuzzy clustering approach to detect the yarn colors in yarn-dyed fabrics. These clustering approaches are the extended version of K-means clustering method.…”

“…Zhang et al and Pan et al adopted the Fuzzy C‐means method and Zou et al using the improved fuzzy clustering approach to detect the yarn colors in yarn‐dyed fabrics. These clustering approaches are the extended version of K‐means clustering method.…”