| 基于人工神经网络的织物疵点检测 |
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| 引用本文： | 沈咏军,朱桂英.基于人工神经网络的织物疵点检测[J].丝绸,2007(6):38-41. |
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| 作者姓名： | 沈咏军 朱桂英 |
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| 作者单位： | 浙江广厦建设职业技术学院,建筑工程系,浙江,金华,322100;浙江理工大学,信息电子学院,杭州,310018 |
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| 摘 要： | 根据疵点的特征对常见织物疵点进行了简单的划分。采用直方图均衡化、二值化、中值滤波、腐蚀和膨胀等方法对织物图像进行一系列的预处理，对织物疵点的特征参数进行提取，利用人工BP神经网络来判别疵点的类别并进行分类。结果表明，利用BP神经网络识别织物疵点并进行分级是行之有效的。
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| 关 键 词： | 人工神经网络 织物疵点 分类 质量等级评定 |
| 文章编号： | 1001-7003（2007）06-0038-04 |
| 修稿时间： | 2007-01-09 |
Detection of Fabric Defect Based on Artificial Neural Network |
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| SHEN Yong-jun,ZHU Gui-ying.Detection of Fabric Defect Based on Artificial Neural Network[J].Silk Monthly,2007(6):38-41. |
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| Authors: | SHEN Yong-jun ZHU Gui-ying |
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| Affiliation: | 1.Guangsha College of Applied Construction Technology, Jinhua 322100, China; 2.Zhejiang Sci-Tech University, Hangzhou 310018, China |
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| Abstract: | The common fabric defects were classified by according to their characteristic.The-defect images are pretreated by series of methods, such as histogram transformation, two-value transformation, middle-value wave flitting, eroding and dilating. Then some characteristic parameters of each defect were acquired. After that, artificial BP neural network was used to identify the classification of fabric defects. The results show that it is effective to identify and classify the fabric defects by using BP neural network. |
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| Keywords: | Artificial neural network Fabric defect Classification Evaluation of quality rank |
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