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| Regression Analysis on Tie-dye Technique and Pattern Feature
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| School of Textile and Garment, Jiangnan University, Wuxi 214122, China
Art College, Jinling Institute of Technology, Nanjing 211169, China
College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210002, China,
Jiangsu Huayi Group, Haian 226600, China |
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Abstract Based on computer vision technology, we studied predictive method of tie-dye pattern information.
We extracted the average value of HSV (hue, saturation, value) tri-component of valid tie-dye area,
proportion of tie-dye white area and coarseness as pattern feature, and designed correlation analysis on
tie-dye production process and pattern feature accordingly. The results showed that dye concentration
and pattern feature are highly correlated and the speed is also an important indicator of the effect of tie-
dye pattern. In view of tie-dye production speed, concentration process parameters and pattern feature
linear regression analysis, the findings are as follows: there is a positive correlation between process
parameters and H, S component mean; process parameters negatively correlate with V component mean
and proportion of tie-dye white area and coarseness; R-Squared values of prediction model are greater
than 0.5. The linear regression models can be used to predict tie-dye image pattern effects.
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| Fund:Project supported by National-sponsored Social Sciences Funding Program of China (No. 12BMZ049), the
Ministry of education for New Century Excellent Tal ents Project of China (No. NCET-10-0454), and Jiangsu
Natural Science Foundation of China (No. BK2012363).
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| Cite this article: |
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Suqiong Liu,Huie Liang,Weidong Gao, et al. Regression Analysis on Tie-dye Technique and Pattern Feature
[J]. Journal of Fiber Bioengineering and Informatics, 2014, 7(4): 561-571.
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2014, Vol. 7 
