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Real-time vision system for defect detection and neural classification of web textile fabric

机译:实时视觉系统的网状织物缺陷检测和神经分类

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Abstract: A real-time pilot system for defect detection and classification of web textile fabric is presented in this paper. The general hardware and software platform, developed for solving this problem, is presented and a powerful novel method for defect detection is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where the presence of many types of noise is an inevitable phenomenon. For the defect classification an artificial neural network, trained by using a back-propagation algorithm, is implemented. Using a reduced number of possible defect classes, the system gives consistent and repeatable results with sufficient speed.!32
机译:摘要:本文提出了一种实时检测网状织物缺陷和分类的试验系统。介绍了为解决该问题而开发的通用硬件和软件平台,并提出了一种功能强大的缺陷检测新方法。在实际工业条件下检测低对比度缺陷时,此方法可提供良好的结果,在实际工业条件下,不可避免地会出现多种类型的噪声。对于缺陷分类,实现了一种人工神经网络,该人工神经网络通过使用反向传播算法进行了训练。使用减少的可能的缺陷类别数量,系统以足够的速度给出一致且可重复的结果!32

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