东华大学学报（英文版）2008，Vol.25Issue(3)：345-348,4.
Fabric Defect Detection Technique Based on Two-double Neural Network
Fabric Defect Detection Technique Based on Two-double Neural Network
XIE Chun-ping 1XU Bo-jun 1CHEN Jun-jie1
作者信息
- 1. Key Laboratory of Science and Technology of Eco-Textiles Ministry of Education, Jiangnan University, Jiangsu 214122, China
- 折叠
摘要
Abstract
This paper introduces the identification of the defects on the fabric by using two-double neural network and wavelet analysis. The purpose is to fit for the automatic cloth inspection system and to avoid the disadvantages of traditional human inspection. Firstly, training the normal fabric to acquire its characteristics and then using the BP neural network to tell the normal fabric apart from the one with defects. Secondly, doing the two-dimensional discrete wavelet transformation based on the image of the defects, then wiping off the proper characteristics of the fabric, and identifying the defects utilizing the trained BP neural network. It is proved that this method is of high speed and accuracy. It comes up to the requirement of automatic cloth inspection.关键词
defect identification/wavelet analysis/neural network/quality inspectionKey words
defect identification/wavelet analysis/neural network/quality inspection分类
轻工纺织引用本文复制引用
XIE Chun-ping,XU Bo-jun,CHEN Jun-jie..Fabric Defect Detection Technique Based on Two-double Neural Network[J].东华大学学报（英文版）,2008,25(3):345-348,4.
