| 基于人工神经网络的织物疵点聚类分析 |
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| 引用本文： | 杨晓波.基于人工神经网络的织物疵点聚类分析[J].纺织学报,2011,32(9):29-33. |
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| 作者姓名： | 杨晓波 |
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| 作者单位： | 浙江财经学院 |
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| 基金项目： | 高等学校博士学科点专项科研基金资助项目(99025508) |
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| 摘 要： | 本文提出了一种基于人工神经网络的织物疵点分类方法。首先利用灰度共生矩阵提取织物疵点图像的纹理特征参数；然后阐述前馈BP神经网络的拓扑结构，并提出该网络的具体训练过程；最后利用人工神经网络对真实织物疵点样本进行分类，实验采用五类织物样本，网络训练完成后得到实际分类的疵点数据，并利用该数据进行织物疵点分类，分类的准确率达到100%，从而验证了该方法的可行性。
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| 关 键 词： | 人工神经网络 特征提取 模式识别 疵点分类 |
| 收稿时间： | 2010-09-06 |
Fabric defect clustering analysis based on artificial neural network |
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| YANG Xiaobo.Fabric defect clustering analysis based on artificial neural network[J].Journal of Textile Research,2011,32(9):29-33. |
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| Authors: | YANG Xiaobo |
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| Affiliation: | YANG Xiaobo(Department of Information,Zhejiang University of Finance & Economics,Hangzhou,Zhejiang 310018,China) |
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| Abstract: | For solving this problem that classification accuracy is not high due to human factors in the process of fabric defect classification,a method is proposed to classify fabric defects based on artificial neural network.Firstly,gray co-occurrence matrix is used to extract texture feature parameters from fabric defect image.Then,the topology structure of forward feedback BP neural network is narrated,and also indicated the training process in detail.Finally,the BP artificial neural network is applied to fabric ... |
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| Keywords: | artificial neural network feature extraction pattern recognition defect classification |
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