Textile Research Journal · 2011 · 27 citations · 26 references
ComputingComputer ScienceManufacturing EngineeringComputer VisionMachine LearningMachine VisionDefect ClassificationDefect DetectionIndustrial InspectionPattern RecognitionTechnical TextilesTexture AnalysisComputer Vision For InspectionFabric Defect ClassificationGenetic Algorithm OptimizationGenetic Algorithm Variable SelectionImage-based Defect ClassificationMachine Learning-based Defect DetectionTextile ClassificationTexture Defect Analysis
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.
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Jeffrey L. Elman · Cognitive Science · 1990 · 10.8K citations
Unsupervised texture segmentation using Gabor filters
Anil K. Jain, F. Farrokhnia · Pattern Recognition · 1991 · 2.1K citations