A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Hidden Markov random field models applied to color homogeneity evaluation in dyed textile images
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.
Hidden Markov random field models applied to color homogeneity evaluation in dyed textile images
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.
Hidden Markov random field models applied to color homogeneity evaluation in dyed textile images
Freguglia, Victor (author) / Garcia, Nancy L. (author) / Bicas, Juliano L. (author)
Environmetrics ; 31
2020-06-01
13 pages
Article (Journal)
Electronic Resource
English
Spectral-Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields
| Online Contents | 2014
Spectral-Spatial Classification of Hyperspectral Images Based on Hidden Markov Random Fields
| Online Contents | 2014
Hidden Markov Models Applied to Vegetation Dynamics Analysis Using Satellite Remote Sensing
| Online Contents | 1994
Multilayer Markov Random Field models for change detection in optical remote sensing images
| Online Contents | 2015