An Approach for Defect Detection and Classification of the Yarn Ends for Splicing
An Approach for Defect Detection and Classification of the Yarn Ends for Splicing
复制标题
捻接纱头缺陷检测与分类的方法
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
H. Nagahashi
中科院分区：
文献类型：
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作者：
Khaled Issa;H. Nagahashi
本文提出了一种基于视觉的纱线成品拼接质量自动控制系统，旨在建立一种标准的质量控制措施，降低生产成本。提出了一种新的缺陷检测和分类方法。在该方法中，提取描述形状和表面缺陷的特征，并将缺陷分类为不同的类别。利用缺陷实例训练神经网络分类系统。实验结果表明，该方法具有较高的检测率和分类率。
This paper presents an automatic vision based system for quality control of yarn ends ready for splicing, which is aimed to establish a standard quality measure and lower manufacturing cost. New approach for defect detection and classification is presented. In this approach, features describing the shape and surface defects are extracted and defects are classified into different classes. Examples of defects are used to train the classification system using neural network. Experimental results show that a high detection and classification rate can be obtained using this approach.