| 基于小波神经网络的帘子布疵点智能识别技术 |
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| 引用本文： | 肖俊明,彭喜英,李建建,焦凌云,张锐.基于小波神经网络的帘子布疵点智能识别技术[J].现代纺织技术,2009,17(1). |
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| 作者姓名： | 肖俊明 彭喜英 李建建 焦凌云 张锐 |
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| 作者单位： | 中原工学院电子信息学院,郑州,450007 |
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| 摘 要： | 针对帘子布疵点图像特征,提出了将小波变换和人工神经网络技术应用在帘子布疵点检测上.在融合图像灰度的基础上,经小波变换后再提取分解子图像的特征值,利用BP神经网络进行图像分类.结果表明:对帘子布常见疵点如油污、破洞、抽经、断纬等能比较准确地识别.
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| 关 键 词： | 小波变换 帘子布 织物疵点 神经网络 图像处理 |
Technique of Intelligent Recognition for Cord Fabric Defects Based on Wavelet Neural Network |
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| XIAO Junming,PENG Xiying,LI Jianjian,JIAO Lingyun,ZHANG Rui.Technique of Intelligent Recognition for Cord Fabric Defects Based on Wavelet Neural Network[J].Advanced Textile Technology,2009,17(1). |
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| Authors: | XIAO Junming PENG Xiying LI Jianjian JIAO Lingyun ZHANG Rui |
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| Affiliation: | Dept.of Electronics and Information;Zhongyuan University of Technology;Zhengzhou 450007;China |
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| Abstract: | According to the image characteristics of the defects,wavelet transform and neural network technology was used to detect the fault of the cord fabric.In this method,with the combination of the image grayscale,the image characteristic value was extracted after wavelet transform and the image was classified by the BP neural network.The experimental results demonstrate that four kinds of common fabric defects,weft-lacking,warp-lacking,oil stains and holes,can be recognized with high identification correctness. |
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| Keywords: | wavelet transform fabric defect neural network lmage preprocessing |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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