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| Automatic Inspection of Woven Fabric Density Based on Digital Image Analysis |
| Junfeng Jing, Qiying Deng, Pengfei Li |
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Abstract In order to inspect woven fabric density automatically, a method
combining image processing and multi-scale wavelet transform is
proposed in this paper. Firstly, fabric images are pre-processed by
Bimodal Gaussian function histogram equalization to obtain more
structure information. Secondly, fabric images are decomposed into
horizontal and vertical sub-images by using wavelet filter. Thirdly,
texture features are extracted from the sub-images through
binarization and smooth processing. Finally, density of yarns is
acquired accurately after analyzing features of warps and wefts of
the fabric. The experiment results prove that the proposed algorithm
is perfectly suitable for three principle weaves and the relative
error of automatic inspection compared with manual inspection is
less than 0.86\%.
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| Cite this article: |
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Junfeng Jing,Qiying Deng,Pengfei Li. Automatic Inspection of Woven Fabric Density Based on Digital Image Analysis[J]. Journal of Fiber Bioengineering and Informatics, 2015, 8(2): 259-266.
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2015, Vol. 8 
