An Improved Defect Detection Algorithm of Jean Fabric Based on Optimized Gabor Filter


Shuangbao Ma, Wen Liu, Changli You, Shulin Jia, Yurong Wu, Journal of Information Processing Systems Vol. 16, No. 5, pp. 1008-1014, Oct. 2020  

10.3745/JIPS.02.0140
Keywords: Defect Detection, Denim Fabric, False Defect Removal, Gabor filter, Iterative Segmentation
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Abstract

Aiming at the defect detection quality of denim fabric, this paper designs an improved algorithm based on the optimized Gabor filter. Firstly, we propose an improved defect detection algorithm of jean fabric based on the maximum two-dimensional image entropy and the loss evaluation function. Secondly, 24 Gabor filter banks with 4 scales and 6 directions are created and the optimal filter is selected from the filter banks by the onedimensional image entropy algorithm and the two-dimensional image entropy algorithm respectively. Thirdly, these two optimized Gabor filters are compared to realize the common defect detection of denim fabric, such as normal texture, miss of weft, hole and oil stain. The results show that the improved algorithm has better detection effect on common defects of denim fabrics and the average detection rate is more than 91.25%.


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Cite this article
[APA Style]
Shuangbao Ma, Wen Liu, Changli You, Shulin Jia, & Yurong Wu (2020). An Improved Defect Detection Algorithm of Jean Fabric Based on Optimized Gabor Filter. Journal of Information Processing Systems, 16(5), 1008-1014. DOI: 10.3745/JIPS.02.0140.

[IEEE Style]
S. Ma, W. Liu, C. You, S. Jia and Y. Wu, "An Improved Defect Detection Algorithm of Jean Fabric Based on Optimized Gabor Filter," Journal of Information Processing Systems, vol. 16, no. 5, pp. 1008-1014, 2020. DOI: 10.3745/JIPS.02.0140.

[ACM Style]
Shuangbao Ma, Wen Liu, Changli You, Shulin Jia, and Yurong Wu. 2020. An Improved Defect Detection Algorithm of Jean Fabric Based on Optimized Gabor Filter. Journal of Information Processing Systems, 16, 5, (2020), 1008-1014. DOI: 10.3745/JIPS.02.0140.