JOURNAL OF TEXTILE RESEARCH ›› 2010, Vol. 31 ›› Issue (4): 55-59.

• 纺织工程 • Previous Articles     Next Articles

Detection of fabric defects based on Gabor filter

YANG Xiaobo   

  1. Department of Information, Zhejiang University of Finance & Economics
  • Received:2009-04-09 Revised:2009-08-16 Online:2010-04-15 Published:2010-04-15
  • Contact: YANG Xiaobo

Abstract:

The enhanced principle of defective edge based on Gabor filter is narrated from the texture model of defective fabrics. The self-adaptive Gabor filter is designed according to fabric features which determine the central frequency of Gabor filter. Then, the designed Gabor filter is applied to enhance fabric defects with directional aberration and the defective edges test of the fabric is finished through threshold value processing. The experimental results show that self-adaptive Gabor filter of fabric well enhance the edge of directional aberration defect, which can make prominent the energy of fabric texture while restraining the energy of defective texture. The maximum test of this method can achieve 7 m/min.

CLC Number: 

  • TP311.131
[1] . Detection of fabric defects based on Gabor filters and Isomap [J]. JOURNAL OF TEXTILE RESEARCH, 2017, 38(03): 162-167.
[2] . Study on simulation of flexible fabric bend surface based on four-point interpolation method [J]. JOURNAL OF TEXTILE RESEARCH, 2015, 36(06): 50-0.
[3] . Fabric defect detection of statistic aberration feature based on GMRF model [J]. JOURNAL OF TEXTILE RESEARCH, 2013, 34(4): 137-142.
[4] . Research of mixture feature aberrance fabric defect recognition based on self-adaptive disperse wavelet transform [J]. JOURNAL OF TEXTILE RESEARCH, 2013, 34(1): 133-137.
[5] . Fabric Defect Clustering Analysis based on Artificial Neural Network [J]. JOURNAL OF TEXTILE RESEARCH, 2011, 32(9): 29-33.
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