Year: 2014
Journal of Fiber Bioengineering and Informatics, Vol. 7 (2014), Iss. 4 : pp. 561–571
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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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.3993/jfbi12201409
Journal of Fiber Bioengineering and Informatics, Vol. 7 (2014), Iss. 4 : pp. 561–571
Published online: 2014-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 11
Keywords: Tie-dye