Fabric defect clustering analysis based on artificial neural network

For solving this problem that classification accuracy is not high due to human factors in the process of fabric defect classification,a method is proposed to classify fabric defects based on artificial neural network.Firstly,gray co-occurrence matrix is used to extract texture feature parameters from fabric defect image.Then,the topology structure of forward feedback BP neural network is narrated,and also indicated the training process in detail.Finally,the BP artificial neural network is applied to fabric defect classification,and five kinds of fabric samples are used in the experiment.The defect data for classification can be gotten through neural network training process.These data can be used to classify fabric defects.The results show that artificial neural network can be used to classify the common defects with higher accuracy,verifying the feasibility of this method.