Department of Textile Engineering, Faculty of Engineering, Yazd University, P.O. Box: 89195-741, Yazd, Iran
Abstract
Detecting correct color and weave patterns in colored yarn fabrics is one of the most important demands of fabric designers and manufacturers; it is time consuming and acquires high working precision. In this regard, image processing of metaheuristic algorithms can present a useful method for achieving this point. In this research, a novel method, based on genetic algorithm, has been applied to distinguish fabric parameters of color pattern, its period number and weave pattern simultaneously. The parameters have been extracted from the fabric images simulated manually by the computer. The algorithm has been performed on 30 simulated fabric images with different weave and color patterns in variable sizes. Results indicate that in all the images except the defective ones, the fitness values of 100% have been obtained. In spite of existing maximum 3 faults in the simulated image, the presented algorithm is capable of detecting correct color patterns.
Fasahat, F., & Peivandi, P. (2013). Derivation of Fabric Parameters from Simulated Imaging by Genetic Algorithm Method. Journal of Textile Science and Technology, 3(2), 47-56.
MLA
F. Fasahat; P. Peivandi. "Derivation of Fabric Parameters from Simulated Imaging by Genetic Algorithm Method". Journal of Textile Science and Technology, 3, 2, 2013, 47-56.
HARVARD
Fasahat, F., Peivandi, P. (2013). 'Derivation of Fabric Parameters from Simulated Imaging by Genetic Algorithm Method', Journal of Textile Science and Technology, 3(2), pp. 47-56.
VANCOUVER
Fasahat, F., Peivandi, P. Derivation of Fabric Parameters from Simulated Imaging by Genetic Algorithm Method. Journal of Textile Science and Technology, 2013; 3(2): 47-56.
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