Illumination compensation in textile colour constancy, based on an improved least-squares support vector regression and an improved GM(1,1) model of grey theory / Jian-xin Zhang in COLORATION TECHNOLOGY, Vol. 133, N° 2 (04/2017)  

[article]  inCOLORATION TECHNOLOGY > Vol. 133, N° 2 (04/2017) . - p. 128-134 Titre : Illumination compensation in textile colour constancy, based on an improved least-squares support vector regression and an improved GM(1,1) model of grey theory Type de document : texte imprimé Auteurs : Jian-xin Zhang, Auteur ; Pan Zhang, Auteur ; Xiao-liang Wu, Auteur ; Zhi-yu Zhou, Auteur ; Chong Yang, Auteur Année de publication : 2017 Article en page(s) : p. 128-134 Note générale : Bibliogr. Langues : Anglais (eng) Catégories : Algorithmes Textiles et tissus vision des couleurs Index. décimale : 667.3 Teinture et impression des tissus Résumé : In many colour-related fields, such as textile colour measurement systems based on computer vision as well as dyestuff synthesis, colour constancy with illumination variation is a key problem to be solved. A new algorithm of illumination compensation for colour constancy for textured textiles is proposed in this paper, combining an improved least-squares support vector regression (LSSVR) and an improved GM(1,1) model of grey theory. The LSSVR algorithm was improved by determining the error limitation according to the distance between a standard sample and a test sample, while the improved GM(1,1) model used the average value of the sequence x^(1)(1)-x^(1)(n) as the initial iteration value. The disadvantage of LSSVR, that it easily falls into global optimisation, can be compensated for by the local optimisation capacity of the GM(1,1) model. Experimental results show that the algorithm of this paper is very stable and provides good illumination compensation, whereby the time complexity of compensation is reduced by repeatedly processing fractional data with the LSSVR algorithm, and the prediction accuracy is improved by combining the improved GM(1,1) model and the LSSVR algorithm. Note de contenu : - ILLUMINATION COMPENSATION MODEL WITH IMPROVED LSSVR AND GM(1,1) : Improved LSSVR algorithm - GM(1,1) model with initial value as average of x^(1)(1)-x^(1)(n) - ILLUMINATION COMPENSATION : Colour space - Illumination compensation procedure - EXPERIMENTS AND DISCUSSION : Comparison of the LSSVR + GM(1,1) algorithm with the SSR and BP_Adaboost algorithms - Evaluation of the LSSVR+GM(1,1) algorithm DOI : 10.1111/cote.12243 En ligne : https://drive.google.com/file/d/1_uIjBeBakHbXbUrT0Y7yuufOr5nvev-Y/view?usp=drive [...] Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=28226 [article]

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