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一种新的基于纹理分水岭的纺织品缺陷检测方法

DOI: 10.11834/jig.20091012

Keywords: 图像分割,纺织品缺陷,纹理分水岭,小波变换

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Abstract:

纺织品缺陷检测是纺织品自动检测的重要环节,而纺织品缺陷检测的目的是为了准确地对纺织品的缺陷区域进行定位。为了对纺织品缺陷进行准确有效的检测,提出了一种新的基于纹理分水岭的纺织品缺陷检测方法。该方法首先利用小波变换提取了图像的各子带纹理特征;然后对各子带纹理特征求梯度,并通过融合各子带梯度来获得纹理梯度,使其在纹理梯度中能有效地突出纹理区域的边界;最后在此基础上,结合分水岭分割,即能准确地检测出纺织品的缺陷区域。通过对一组6类纺织品缺陷进行检测的实验证明,该新算法是有效的。

References

[1]  Sari-Sarraf H,Goddard J S.Vision system for on-loom fabric inspection[J].IEEE Transactions on Industrial Applications,1999,35 (6):1252-1259.
[2]  Kim S,Lee M H,Woo K B.Wavelet analysis to fabric defects detection in weaving processes[A].In:Proceedings of the IEEE Internutionul Symposiitrn on Industrial Electronics[C],Bled,Slovenia,1999,3:1406-1409.
[3]  Yang X Z,Pang G,Yung N.Discriminative fabric defect detection using adaptive wavelet[J].Optical Engineering,2002,41 (12):3116-3126.
[4]  Hill P,Canagarajah C,Bull D.Image segmentation using a texture gradient-based watershed transform[J].IEEE Transactions on Image Process,2003,12(12):1618-1633.
[5]  Randen Trygve,Hnsφy John Hakon.Filtering for texture classification:A comparative study[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21 (4):291-310.
[6]  Sonka M,Hlavae V,Boyle R.Image Processing,Analysis,and Machine Vision[M].2nd ed.London,UK:Books/Cole Publishing,1999:506-507.
[7]  Vachtsevanos G J,Mufti M,Dorrity J L.Method and Apparatus for Analyzing an Image to Detect and Identify Defects[P].United States Patent,58 15 198,1998,674-693.
[8]  Hill P,Canagarajah C,Bull D.Texture gradient based watershed segmentation[J].Speech and Signal Processing,2002,4 (2):3381-3384.
[9]  Jain A K,Farrokhnia F.Unsupervised texture segmentation using Gabor filters[J].Pattern Recognition,1991,23(2):1167-1186.
[10]  Canny J.A computational approach to edge detection[J].IEEE Transactions on Pattern Analysis Machine Intelligence,1986,8 (2):269-285.

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