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Detection and Classification of Fabric Color Difference Based on Fuzzy Artificial Neural Network

机译:基于模糊人工神经网络的织物色差检测与分类

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The detection of fabric color difference and classification issues are studied. First, to the question of color differences and analysis of the characteristics of different color space, we chose L * a * b * color space model. In this method color difference is converted into geometric distance, so we can detect the color difference with the corresponding calculation. For the complexity of color difference classification, we consider that the classification of color difference is fuzzy, so we use fuzzy method to describe it and fuzzy neural network to complete the classification. We also explain the algorithm and structure of fuzzy neural network. Finally, for the detection and classification of color difference of the fabric samples, characteristic and comparative analysis of the detection and classification concludes that the methods chosen are effective and feasible.
机译:研究了织物色差和分类问题的检测。首先,对不同颜色空间特征的颜色差异和分析,选择L * A * B *彩色空间模型。在这种方法中,色差被转换为几何距离,因此我们可以检测与相应的计算的色差。为了色彩差异分类的复杂性,我们认为色差的分类是模糊的,因此我们使用模糊方法来描述它和模糊神经网络来完成分类。我们还解释了模糊神经网络的算法和结构。最后,对于织物样品的色差的检测和分类,检测和分类的特征和比较分析得出结论,所选择的方法是有效和可行的。

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