Colour matching by principal component analysis-based spectrophotometric technique / Ali Shams Nateri in COLORATION TECHNOLOGY, Vol. 125, N° 1 (2009)  

[article]  inCOLORATION TECHNOLOGY > Vol. 125, N° 1 (2009) . - p. 36-42 Titre : Colour matching by principal component analysis-based spectrophotometric technique Type de document : texte imprimé Auteurs : Ali Shams Nateri, Auteur Année de publication : 2009 Article en page(s) : p. 36-42 Note générale : Bibliogr. Langues : Anglais (eng) Index. décimale : 667.3 Teinture et impression des tissus Résumé : One of the most important aspects of the physics of colour is colour matching and recipe prediction. In this work, a new method is presented to evaluate the concentration of dyes in textile fabrics. The algorithm of the new technique is based on principal component analysis and single constant spectrophotometric matching methods. Using the normal spectrophotometric matching method, match prediction is carried out at three and 16 wavelengths. With the new algorithm, 3, 6, 9, 12 and 16 principal components are used in spectral match prediction. The performance of the new method improves with increasing numbers of principal components. In addition, the recipe prediction accuracy of the new method with three principal components is better than spectrophotometric matching at three wavelengths. The accuracy of principal component analysis–spectrophotometry with 16 principal components is comparable with the normal spectrophotometric matching method at 16 wavelengths. DOI : 10.1111/j.1478-4408.2008.00173.x En ligne : http://onlinelibrary.wiley.com/doi/10.1111/j.1478-4408.2008.00173.x/pdf Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=4823 [article]

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Effect of a standard colorimetric observer on the reconstruction of reflectance spectra of coloured fabrics / Ali Shams Nateri in COLORATION TECHNOLOGY, Vol. 124, N° 1 (2008)  

[article]  inCOLORATION TECHNOLOGY > Vol. 124, N° 1 (2008) . - p. 14-18 Titre : Effect of a standard colorimetric observer on the reconstruction of reflectance spectra of coloured fabrics Type de document : texte imprimé Auteurs : Ali Shams Nateri, Auteur Année de publication : 2009 Article en page(s) : p. 14-18 Note générale : Bibliogr. Langues : Anglais (eng) Index. décimale : 667.3 Teinture et impression des tissus Résumé : Principal component analysis is a statistical and mathematical method in colour science, which can be used in compression and reconstruction of reflectance spectra. The goal of this work is to study the effect of standard colorimetric observers and illuminant source combinations on the reconstruction of reflectance spectra of textile fabrics. Several computational approaches were introduced by using different combinations of D65, A and D75 illuminant sources and 2° and 10° standard colorimetric observers in reconstruction reflectance spectra from corresponding tristimulus values. The obtained results indicate that the accuracy of the estimation depends on the type of illuminant sources, standard observers and number of principal components. The best result was achieved by a 2° standard observer with more than four principal components. The optimal numbers of principal components for achieving the imperceptible colorimetric accuracy are 4 and 6 for 2° and 10° standard observers, respectively. DOI : 10.1111/j.1478-4408.2007.00115.x En ligne : http://onlinelibrary.wiley.com/doi/10.1111/j.1478-4408.2007.00115.x/pdf Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=3134 [article]

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Instrumental shade sorting of coloured fabrics using genetic algorithm and particle swarm optimisation / Elham Hasanlou in COLORATION TECHNOLOGY, Vol. 139, N° 4 (08/2023)  

[article]  inCOLORATION TECHNOLOGY > Vol. 139, N° 4 (08/2023) . - p. 454-463 Titre : Instrumental shade sorting of coloured fabrics using genetic algorithm and particle swarm optimisation Type de document : texte imprimé Auteurs : Elham Hasanlou, Auteur ; Ali Shams Nateri, Auteur ; Hossein Izadan, Auteur Année de publication : 2023 Article en page(s) : p. 454-463 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Algorithmes génétiques Colorimétrie Dispositifs de tri Optimisation par essaims particulaires L'optimisation par essaims particulaires (OEP ou PSO en anglais) est une métaheuristique d'optimisation, inventée par Russel Eberhart (ingénieur en électricité) et James Kennedy (socio-psychologue) en 1995. Algorithme Cet algorithme s'inspire à l'origine du monde du vivant. Il s'appuie notamment sur un modèle développé par Craig Reynolds à la fin des années 1980, permettant de simuler le déplacement d'un groupe d'oiseaux. Une autre source d'inspiration, revendiquée par les auteurs, James Kennedy et Russel Eberhart, est la socio-psychologie. Cette méthode d'optimisation se base sur la collaboration des individus entre eux. Elle a d'ailleurs des similarités avec les algorithmes de colonies de fourmis, qui s'appuient eux aussi sur le concept d'auto-organisation. Cette idée veut qu'un groupe d'individus peu intelligents peut posséder une organisation globale complexe. Ainsi, grâce à des règles de déplacement très simples (dans l'espace des solutions), les particules peuvent converger progressivement vers un minimum global. Cette métaheuristique semble cependant mieux fonctionner pour des espaces en variables continues. (Wikipedia) Textiles et tissus teints Index. décimale : 667.3 Teinture et impression des tissus Résumé : In the present research by combination of Clemson Colour Clustering (CCC) instrumental shade sorting method and two metaheuristic algorithms, a genetic algorithm (GA) and a particle swarm optimisation (PSO), two new shade sorting methods, called CCCGA and CCCPSO were proposed. Then these proposed methods were applied on 16 well-prepered colour sets made of coloured fabrics and their results were compared using some important performance evaluation factors. The results of the methods were also compared with conventional CCC shade sorting method and a method based on CCC combined with k-means technique (CCCk). The results obtained from various shade sorting methods showed that the CCCGA and CCCPSO methods successfully sorted the coloured fabrics with high efficiency, and their results slightly outperformed the results of the CCC method. Note de contenu : - INTRODUCTION : Genetic algorithm - Particle swarm optimisation - MATERIALS AND METHODS : Preparation of samples and colour measurement - Determining the colour tolerance of coloured fabrics - Shade sorting using the genetic algorithm - Shade sorting using particle swarm optimisation - RESULTS AND DISCUSSION : Performance evaluation factors of shade sorting methods - Number of sorted groups - Colour variation within the groups - Compactness of the points in sorted groups - Utilisation of the fabric - Table 1 : Specifications and colour tolerance of the 16 fabric colour sets - Table 2 : The values of the parameters and genetic operators used in the genetic algorithm - Table 3 : The values of the parameters used in the particle swarm optimisation - Table 4 : The colour variation within the groups formed by various shade sorting methods and the number of sorted groups by Clemson Colour Clustering (CCC) shade sorting - Table 5 : The compactness of the points in sorted groups by different shade sorting methods - Table 6 : The number of groups containing only one sample and the percentage of groups in low utilisation by different shade sorting methods DOI : https://doi.org/10.1111/cote.12663 En ligne : https://onlinelibrary.wiley.com/doi/epdf/10.1111/cote.12663 Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=39682 [article]

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The use of Monte Carlo simulation to evaluate the optical properties of polyester fabric treated with titanium dioxide nanopigments / Laleh Asadi in COLORATION TECHNOLOGY, Vol. 139, N° 1 (02/2023)  

[article]  inCOLORATION TECHNOLOGY > Vol. 139, N° 1 (02/2023) . - p. 28-44 Titre : The use of Monte Carlo simulation to evaluate the optical properties of polyester fabric treated with titanium dioxide nanopigments Type de document : texte imprimé Auteurs : Laleh Asadi, Auteur ; Ali Shams Nateri, Auteur Année de publication : 2023 Article en page(s) : p. 28-44 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Caractérisation Coefficient de diffusion Un coefficient de diffusion est une grandeur caractéristique du phénomène de diffusion de la matière. Le coefficient de diffusion mesure le rapport entre le flux molaire dû à la diffusion moléculaire, et le gradient de concentration de l'espèce chimique considérée (ou, plus généralement, de la variable d'effort entraînant cette diffusion), comme formulé par la loi de Fick. Dioxyde de titane Enduction textile Fibres textiles -- Propriétés optiques Lumière -- Diffusion Mie, Diffusion de Monte-Carlo, Méthode de Pigments Pigments inorganiques Spectroscopie de réflectance Textiles et tissus -- Propriétés optiques Index. décimale : 667.3 Teinture et impression des tissus Résumé : The current study utilises Monte Carlo simulation and Mie scattering theory to estimate the reflectance spectra of fabric coated with titanium dioxide nanopigments of various diameters and concentrations. Image processing was carried out and experimental data were gathered to evaluate the performance of Monte Carlo simulation. The distribution and location of the nanopigments on the surface of fabric were determined using the Monte Carlo method. Reflection of the fabric was calculated based on Monte Carlo simulation with the partitive mixing method and Mie theory. According to the experimental and simulation results, the reflectance of coated samples was increased by increasing the concentration and number of titanium dioxide nanoparticles. There was a good match between the results obtained by Monte Carlo simulation and the experimental results. For coated samples (dTiO2: 500 nm), the root mean square error between measured and predicted reflectance by the Monte Carlo and partitive mixing method and by Monte Carlo and Mie theory was 0.022 and 0.0078, respectively. The results indicate that the performance of the Monte Carlo and Mie method was better than that of the Monte Carlo and partitive mixing method. According to t-test analysis, there was no statistically significant difference between the experimental data and Monte Carlo simulation. Note de contenu : - EXPERIMENTAL : Materials - Polyester fabric coating - Characterisation - MODEL DESCRIPTION : MC and the partitive mixing method - MC and the Mie method - Table 1 : For polyester fabric, the percentages of uncoated surface and surface coated with titanium dioxide (TiO2) based on the image processing system - Table 2 : CIELab and colour difference (∆E) values for the uncoated (raw fabric) sample and samples coated with titanium dioxide (TiO2) - Table 3 : Scattering coefficient values for titanium dioxide nanopigments with average diameters of 30, 50, 150, 250 and 500 nm - Table 4 : Forward and backward light scattering of titanium dioxide (TiO2) nanoparticles based on Mie theory - Table 5 : Forward and backward light scattering of titanium dioxide (TiO2) nanoparticles based on image processing - Table 6 : Percentages of empty and occupied particles using the Monte Carlo method for different hypothetical numbers of titanium dioxide (TiO2) nanoparticles - Table 7 : Estimated percentages of empty and occupied particles using the Monte Carlo method for actual numbers of titanium dioxide (TiO2) nanoparticles - Table 8 : Area occupied on the fabric surface by single, double and multiple titanium dioxide (TiO2) nanopigments - Table 9 : L*, a*, b* and ∆E values for samples with different numbers of titanium dioxide (TiO2) nanopigments - Table 10 : CIELab and ∆E values and the root mean square error (RMSE) for reflectance predictions using the Monte Carlo and partitive mixing method - Table 11 : CIELab and ∆E values and the root mean square error (RMSE) for reflectance predictions using the Monte Carlo and Mie method - Table 12 : T-stat and P values for the experimental and Monte Carlo simulation results DOI : https://doi.org/10.1111/cote.12632 En ligne : https://onlinelibrary.wiley.com/doi/epdf/10.1111/cote.12632 Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=39203 [article]

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