An intelligent model for detecting and classifying color-textured fabric defects using genetic algorithms and the Elman neural network

Abstract

In this paper, an intelligent color-textured fabric defect detection and classification model using genetic algorithms and the Elman neural network is introduced. A color ring projection is used for image processing, and the solution for optimization of parameters is based on the genetic algorithm method. The new modified Elman network is proposed to classify the type of fabric defects, which have proportional, integral, and derivative properties. The proposed inspecting model in this study is more feasible and applicable in fabric and stitching garment defect detection and classification.