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A new intelligent fabric defect detection and classification system based on gabor filter and modified elman neural network

机译:基于gabor滤波器和改进Elman神经网络的新型智能织物缺陷检测与分类系统。

摘要

In this paper, one fabric defect detection and classification system based on 2D Gabor wavelet transform and Elman neural network is introduced. In the proposed scheme, the texture features of the textile fabric are extracted by using an optimal 2D Gabor filter. A new modified Elman network is proposed to classify the type of fabric defects which have a proportional (P), integral (I) and derivative (D) properties. The proposed inspecting system in this study is more feasible and applicable in fabric defect detection and classification.
机译:介绍了一种基于二维Gabor小波变换和Elman神经网络的织物疵点检测与分类系统。在所提出的方案中,通过使用最佳的二维Gabor滤波器来提取织物的质地特征。提出了一种新的改进的Elman网络来对具有缺陷(P),积分(I)和导数(D)属性的织物缺陷类型进行分类。本研究提出的检测系统在织物疵点的检测和分类中更为可行和适用。

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