The realistic significance of applying computer vision to fabric defect detection is analyzed firstly.
首先分析了将计算机视觉应用于织物疵点检测的现实意义。
The fabric defect automatic inspection is one of the technical problems that the textile industry is facing.
织物缺陷的自动检测是纺织行业所面临的技术难题之一。
Presents an efficient method of fabric defect classification based on cluster analysis and support vector machine (SVM).
提出一种基于聚类分析和支持向量机(SVM)的布匹瑕疵分类方法。
Fabric defect inspection using image processing technology is a problem of extracting of textural features and pattern recognition.
利用图像处理技术完成织物疵点检测是一个纹理特征提取和模式识别问题。
The defect could be detected rapidly by computer vision technology based on the characteristic of the fabric texture.
通过分析采集的布匹纹理特征，应用机器视觉技术能快速检测出布匹上的瑕疵。
The advantage is that simple device, easy adjustment and only revolving the column lens that can fabric various linear-defect in photonic lattices, they have different orientation relative toc-axis.
此方法的优点是装置简单，容易调节，只需旋转圆柱透镜，就可以制作出和光轴方向不同的各种线状缺陷光子晶格。
The advantage is that simple device, easy adjustment and only revolving the column lens that can fabric various linear-defect in photonic lattices, they have different orientation relative toc-axis.
此方法的优点是装置简单，容易调节，只需旋转圆柱透镜，就可以制作出和光轴方向不同的各种线状缺陷光子晶格。
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