纺织学报 ›› 2011, Vol. 32 ›› Issue (7): 49-53.

• 纺织工程 • 上一篇    下一篇

基于二维经验模态分解算法的织物疵点自动检测

厉征鑫1,刘基宏1,高卫东2,潘如如1,柴智雷1   

  1. 1. 江南大学
    2. 江南大学纺织服装学院
  • 收稿日期:2010-08-12 修回日期:2011-01-23 出版日期:2011-07-15 发布日期:2011-09-15
  • 通讯作者: 高卫东 E-mail:gaowd3@163.com
  • 基金资助:

    江苏省高等学校优秀科技创新团队项目,苏教科[2009]10号;江苏省自然科学基金(BK2009511);省级

Automatically fabric defect detection based on bidimensional empirical mode decomposition

  • Received:2010-08-12 Revised:2011-01-23 Online:2011-07-15 Published:2011-09-15

摘要: 本文提出一种基于二维EMD的多方向自适应的织物疵点检测方法。通过Delaunay三角分割、径向基函数插值与二维三次样条插值等方法实现二维EMD算法,用该方法将织物灰度图像分解为一系列子图像,选取包含疵点信息的子图像进行融合,最后通过阈值化来识别织物图像中的疵点。文中借助于工业线阵相机采集包含不同疵点的织物图像,并利用提出的方法进行自动检测,结果表明子图像融合结果中疵点信息明显,与背景的反差强烈,通过阈值法可以直接判断出图像中是否包含疵点,并完成疵点定位,对织物疵点的检测十分有效。

Abstract: In this paper, an adaptive and multidirectional method for fabric defect detection based on bidimensional EMD was proposed. Delaunay triangular partition, radial basis function interpolation and bidimensional cubic spline interpolation were used and combined to implement the algorithm of bidimensional EMD, which was applied to decompose digital images of fabric into a set of sub-images, then sub-images contained defect features were selected to reconstruct a new image, and finally the defects could be distinguished from the binaryzation of the reconstructed image. Several different defective fabric images captured by an industrial line scan camera were analyzed using the proposed approach and the results demonstrated that features of defect contained in reconstructed images were distinguishing and had strong contrast against the background; defects could be recognized and located from binary results without other processes such as noise eliminating. This detecting method could be qualified to fabric defects.

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