| LVQ神经网络在磁瓦表面缺陷分类中的运用 |
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| 引用本文： | 严俊龙,郑晓曦,李铁源. LVQ神经网络在磁瓦表面缺陷分类中的运用[J]. 计算机与数字工程, 2009, 37(12): 147-150 |
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| 作者姓名： | 严俊龙 郑晓曦 李铁源 |
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| 作者单位： | 1. 暨南大学信息技术研究所,广州,510075
2. 五邑大学信息学院,江门,529020 |
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| 摘 要： | 在基于磁瓦表面缺陷图像直方图、纹理、投影和形状的特征提取的基础上,提出了一种用LVQ神经网络进行缺陷分类的方法,对现场采集到的6种主要缺陷类型进行了试验。试验结果表明,基于LVQ神经网络的分类器训练与分类的时间短,多缺陷种类分类时准确率高。
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| 关 键 词： | 磁瓦 表面缺陷 缺陷分类 LVQ神经网络 |
Application of LVQ Neural Network in Classification of Surface Defects for Arc Segments Ceramic Magnet |
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| Yan Junlong,Zheng Xiaoxi,Li Tieyuan. Application of LVQ Neural Network in Classification of Surface Defects for Arc Segments Ceramic Magnet[J]. Computer and Digital Engineering, 2009, 37(12): 147-150 |
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| Authors: | Yan Junlong Zheng Xiaoxi Li Tieyuan |
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| Affiliation: | Yan Junlong, Zheng Xiaoxi, Li Tieyuan (1.Institute of Information Technology, Jinan University, Guangzhou 510075;2.College of Information, Wuyi University , Jiangmen 529020) |
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| Abstract: | The LVQ neural network classification method was introdued based on feature extraction of arc segments ceramic magnet for histogram, texture, projection, shape. Testing by 6 main defect types collected from online was made. The results indicated that the surface defects classification based on LVQ neural network spent little time for training and classifying, and its accuracy was higher. |
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| Keywords: | arc segments ceramic magnet surface defects disfigurement classification LVQ neural network |
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