首页> 外文会议>Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09 >Fabric Defect Detection Using Fuzzy Inductive Reasoning Based on Image Histogram Statistic Variables
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Fabric Defect Detection Using Fuzzy Inductive Reasoning Based on Image Histogram Statistic Variables

机译:基于图像直方图统计变量的模糊归纳推理的织物疵点检测

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This paper deals with the fuzzy inductive reasoning (FIR) for fabric defect detection. Based on linear and regular texture of the fabric, we first extract histogram statistic variables as the distinguishing features between faultless and faulty fabric images. By applying FIR to the histogram statistic variables and subtracting the class values of the real statistic variables and the predicted class values using the qualitative model, cumulative errors are computed, which are used to determine if a defect has been detected. Simulation experiments show that the proposed method can achieve a robust and accurate detection of fabric defects.
机译:本文讨论了用于织物缺陷检测的模糊归纳推理(FIR)。基于织物的线性和规则纹理,我们首先提取直方图统计变量作为无缺陷织物图像和有缺陷织物图像之间的区别特征。通过将FIR应用于直方图统计变量并使用定性模型减去实际统计变量的类别值和预测的类别值,将计算累积误差,该累积误差用于确定是否已检测到缺陷。仿真实验表明,该方法可以实现对织物疵点的鲁棒和准确检测。

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