Hidden Markov random field models applied to color homogeneity evaluation in dyed textile images

Author(s)

Freguglia, Victor ^[1] ; Garcia, Nancy L. ^[1] ; Bicas, Juliano L. ^[2]

Affiliation

^[1] Univ Estadual Campinas UNICAMP, Inst Matemat Estat & Comp Cient, Dept Estat, BR-13083959 Campinas, SP - Brazil

^[2] Univ Estadual Campinas UNICAMP, Fac Engn Alimentos, Campinas, SP - Brazil

• Document type: Journal article
• Source: ENVIRONMETRICS; v. 31, n. 4 DEC 2019.
• Web of Science Citations: 0

Abstract

Color is one of the most important features in any textile material. Due to its competitive price, most of the colorants currently used for textile dyeing are synthetic, originated from nonrenewable sources, and highly pollutant. There is an increasing interest for natural processes to dye fabrics. When new textile dyeing technologies are developed, evaluating the quality of these techniques involves measuring the resulting color homogeneity using digital images. The presence of a texture effect, caused by the interlacing of warp and weft yarns, as well as small displacement of the fabric, creates a sophisticated dependence structure in pixels coloring. A random effects model is employed in order to separate the signal from the dyeing effect (fixed effect described by smooth functions) and warp and weft texture effect (Gaussian mixture driven by a hidden Markov random field), allowing an evaluation of color homogeneity in dyed textiles regardless of the effect of the texture. (AU)

• FAPESP's process: 17/25469-2 - Bayesian inference for signal segmentation in dyed textile images
• Grantee: Victor Freguglia Souza
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 17/10555-0 - Stochastic modeling of interacting systems
• Grantee: Fabio Prates Machado
• Support Opportunities: Research Projects - Thematic Grants