Search results

This paper aims to investigate using scanner-based adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANNs) and polynomial regression methods for prediction of silver nanoparticles (AgNPs) and dye concentrations on AgNP-treated silk fabrics.

For estimation of the dye and AgNPs concentration using image processing, the silk fabrics were scanned under the condition of 200 pixels per inch. The red green blue (RGB) values of scanned images were obtained after applying the median filter. Then, the relationship between scanner RGB values and dye and AgNPs concentrations were obtained by using artificial intelligence methods such as ANFIS and ANNs.

The best result was achieved by the ANFIS system for calculation concentration of dye with 0.07% error and concentration of AgNPs with 0.008 (gr/l) error. The obtained results indicate that the performance of the ANFIS system method is better than the other methods.

Using a scanner-based artificial intelligence technique for prediction of nanosilver and dye content on silk fabric.

This work aims to study the effect of mordanting method as pre-mordanting (on-chrome), meta-mordanting (meta-chrome) and post-mordanting (after-chrome) on wool dyeing with madder natural dye without tannin and pomegranates peel, as a natural dye contains tannin.

The woolen yarn was dyed with madder and pomegranate peel natural dyes by three methods as pre-mordant, meta-mordant and pos-mordant. The color parameters and reflectance spectra of dyed samples were analyzed by using derivative spectroscopy and the principal component analysis (PCA) techniques.

The obtained results indicate that the color difference between the samples dyed with madder by pre-mordanting, and the samples dyed by other methods is more than the color difference between the samples dyed by meta-mordanting and post-mordanting. However, the color difference between samples dyed with pomegranate peel by pre-mordanting and meta-mordanting methods is less compared to other pairs. Also, analysis of reflectance spectra and color depth (K/S) values indicate that the color depth of dyed sample with madder by pre-mordanting method is more than other dyeing methods. But, the color depth of sample dyed with pomegranate peel by post-mordanting method is less compared to other methods. The analysis of first-, second-, third- and fourth-order derivatives of reflectance spectra and the study of the first, second, third and fourth PCs of reflectance spectra indicate that the reflectance of dyed samples with madder and pomegranates peel depends on the mordanting method.

Evaluation of the effect of mordanting method on color and reflectance of wool dyed with madder and pomegranates peel natural dyes using derivative spectroscopy and the PCA techniques

Artificial intelligence (AI) methods, such as genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS), are capable of providing superior solutions for the simulation and the modeling of complex problems. The purpose of this study is to estimate the dye and the silver nanoparticle (AgNP) concentrations of silver nanoparticle-treated silk fabrics by the aforementioned methods.

In this study, the color and the antimicrobial properties of silver nanoparticle-treated silk fabrics were matched by using the GA technique based on spectrophotometric color matching. The ANFIS method was also used; this method is based on the grid partitioning algorithm across four different methods. The first and second methods are provided for dye concentration prediction, and the third and the fourth methods are given for AgNP concentration prediction.

The mean of absolute error and root mean square (RMS) of the best dye concentration prediction by the ANFIS method based on the second method are 0.087 and 0.103, respectively. In addition, the mean of the absolute error and the RMS of the best results for AgNP concentration prediction by the ANFIS method by using the third method is 0.002 and 0.003, respectively. The obtained results indicate that the performance of the ANFIS method is better than the GA method.

The simultaneous prediction of the color and the antimicrobial properties of silver nanoparticle-treated silk fabrics was performed by using the GA and the ANFIS. The suggested method led to acceptable accuracy for color and antibacterial matching.

This study aimed to Simultaneous matching of color and antimicrobial properties of silk fabric treated with silver nanoparticle. The antimicrobial finishing using silver nanoparticles (AgNPs) is one of the most important finishing processes in the textile industry. Color matching is widely applied in the textile industry, but there has been a need for the prediction of AgNPs concentration for the matching of dyed silver-treated samples.

In this research, the silk fabrics were dyed with various concentrations of C.I. Acid Red 359 dye at 0.5, 1, 1.5 and 2 per cent (w/w). The dyed fabrics were then coated with AgNPs in several concentrations at 0.015, 0.030, 0.050, 0.100 and 0.250 ml/l. The prediction of dye and AgNPs concentrations were evaluated using single constant color matching and artificial neural network techniques.

The obtained results indicate that the accuracy of dye concentration prediction, as well as AgNPs concentration prediction, was improved by using a neural network method. Also, the correlation between actual and predicted dye and AgNPs concentrations in the best neural networks is more than the single constant color matching method.

Simultaneous antibacterial and color matching of nanosilver-treated fabric is novel. This method achieved acceptable accuracy for antibacterial and color matching.

The purpose of this study is evaluate the optical properties of polyacrylonitrile (PAN) nanofibers containing fluorescent agents such as fluorescent dye and carbon quantum dots (CQDs) by using image-processing technique of Fluorescence microscope image.

The fluorescence microscope image of the pure PAN, PAN/CQDs and PAN/fluorescent dye nanofibers composite was analyzed using several image-processing techniques such as color histogram, lookup table (LUT), Fourier transform, RGB profile and surface plot analysis.

The fluorescence microscope image indicates that the fluorescence emission of nanocomposites depends on the type of fluorescent agent. The fluorescence intensity of nanofiber containing CQDs is more than nanofiber containing fluorescent dye. Various image-processing methods provide similar results for optical property of nanocomposites. Analyzing the LUT, the blue value of CQDs/PAN nanocomposite image was significantly higher than other nanocomposites. This was confirmed by other methods such as Fourier transform, color histogram and 3D topography of the electrospun nanofibers. According to analysis of colorimetric parameters, higher negative value of b* indicates bluer color for CQDs/PAN nanofibers than other nanocomposites. The obtained results indicate that the image-processing technique can be used to evaluate the optical property of fluorescent nanocomposite.

This study evaluates the optical properties of fluorescent nanocomposites by using image-processing techniques such as Fourier transform, color histogram, RGB profiles, LUT, surface plot and histogram analysis.

This study aimed to use a scanner as a low-cost method for measuring the opacity of textile fabric. Textile fabrics must have specific ranges of opacity according to their uses for shirting, curtaining, etc. In this way, opacity is an important property in the textile industry. Conventionally, textile opacity is estimated using a spectrophotometer, which is an expensive method.

In this study a scanner was used as a low-cost method for measuring the opacity of textile fabric. The opacity was estimated by using red, green and blue (RGB) parameters of images of fabric against white and black background.

The accuracy of opacity estimation was improved by converting RGB into several color spaces. The best opacity estimation was obtained by using the XYZ color space. In addition, using a regression method, the best estimation was obtained by using a fourth-order polynomial regression with the LSLM color space.

The opacity of fabric has been measured by spectrophotometer, but in this study, the opacity of fabric was measured by scanner as a low cost device and also with novel and simple method. This method achieved acceptable accuracy for opacity estimation. The obtained result is comparable with spectrophotometer results.

The main objective of this study is to highlight the relationship between RGB values of digital camera as a device-dependent color space and a device-independent CIE color space. Calibration and testing databases are the colorimetric specifications of colored polyester fabrics. The colored fabrics were dyed with a variety of disperse dyestuffs. Camera characterization was done based on the polynomial regression technique. The methods adopted in the study were non-linear filtering applied to camera RGB values and a polynomial regression function directly applied to the CIELAB space.

The performances of the methods improved by increasing the number of terms in the polynomial. The estimation errors of the linear polynomial regression to CIEXYZ, the nonlinear polynomial regression to CIEXYZ, the linear polynomial regression to CIELAB, and the nonlinear polynomial regression to CIELAB were 3.29, 4.43, 3.05, and 3.04 DE*ab respectively. The generalization capability decreased by increasing the number of terms in the polynomial regression. The best generalization capability was obtained by the linear polynomial regression to CIELAB. The best result was obtained by non-linear filtering while the second-best result was obtained by the polynomial regression to the CIELAB values.

In this article, a simple system will be presented to measure reflectance of metallic surfaces quickly and precisely based on goniospectrophotometric geometry. The paper aims to discuss these issues.

This system works by capturing reflected light from different colored patches by digital camera and with the knowledge of spectral power distribution of light source and defined observer, reflection of each sample can be reproduced. By fixing the light source, the position of the detector would be eliminated to four angles of observation.

This method can achieve acceptable reconstruction accuracy for metallic samples. This approach confirmed repeatability and practicality of the simple imaging acquisition to replace spectral reflectance measurement devices in different viewing angles.

The reflectance of metallic samples has been measured at several angles such as 20°, 45°, 75° and 110° from specular reflection. A simple system was used to measure multi-angle reflectance of metallic surfaces by digital camera. By suggested system can be measured the reflectance without contact and limitation in the shape of surfaces. This method achieved acceptable reconstruction accuracy for metallic samples. This simple imaging acquisition is comparable with goniospectrophotometer for measuring multi-angle reflectance of metallic samples.

The purpose of this paper is to synthesise a tetrakisazo reactive dye and to characterise its dyeing property to meet the demand for better black reactive dyes.

The novel tetrakisazo navy-blue reactive dye based on 4,4′-diaminostilbene-2,2′-disulphonic acid was designed and synthesized. The dyeing behaviour of it on cotton fabric was discussed. The synergistic blackening effect and absorbance spectra were investigated by absorbance and reflectance spectra, K/S and colorimetric data.

The exhaustion and fixation of the designed reactive dye were higher than 20 per cent than those of the commercial reactive dye, CI Reactive Black 5. The novel reactive dye has complementary with Reactive Red SPB and Reactive Yellow C-5R in absorbance spectra from 360 to 700 nm. Three reactive dyes had synergistic effect in colour deepening properties. The dyed cotton fabric possessed high K/S value and low reflectance in the whole visual spectrum range from 360 to 700 nm.

Comparison with the commercial Reactive Black DN-RN, the blackness of the dyed fabrics with the mixture dyes was greatly improved and the fastness properties on cotton fabrics were also good.

The paper is an original research work. Because the mixture dyes had better blackness and good fastness properties, it would have wide application in the dyeing of cotton fabric.

The purpose of this study is to investigate the possibility of dyeing polyester (PET) fabric with natural dye extracted from annatto seeds using high temperature dyeing method.

PET fabric was dyed with annatto extract by varying dyeing parameters (temperature, time, pH and dye concentration) to determine the optimum dyeing conditions. The influences of KAl(SO₄)₂, FeSO₄, gallnut mordants or a commercial UV absorber on colour yield and fastness properties were further studied.

Optimum results were obtained when the fabric was dyed at 130°C for 30 min in a dyebath containing 15 per cent (owf) annatto dye at pH 6. The dyed fabric had an orange shade and exhibited good to excellent wash, crock, perspiration fastness and fair light fastness. Further dyeing with mordants or UV absorber mostly resulted in lower colour yield and similar fastness properties.

Although the light fastness was slightly improved to moderate level for the sample with UV absorber, a noticeable colour staining on cotton portion of multi-fibre fabric occurred when subjected to standard washing test. Compared to C.I. Disperse Orange 73, the annatto dye exhibited comparable colour fastness but had inferior light fastness when dyed at approximately the same colour strength.

Natural colourants from annatto seeds can be used to dye PET fabric at high temperature without mordants, yielding deep orange shade and satisfactory fastness properties. This study provides a promising application to reduce the environmental impact of synthetic dyes.