An identification method of cashmere and wool by the two features fusion
International Journal of Clothing Science and Technology
ISSN: 0955-6222
Article publication date: 9 February 2021
Issue publication date: 1 March 2022
Abstract
Purpose
The purpose of this paper is to select the optimal feature parameters to further improve the identification accuracy of cashmere and wool.
Design/methodology/approach
To increase the accuracy, the authors put forward a method selecting optimal parameters based on the fusion of morphological feature and texture feature. The first step is to acquire the fiber diameter measured by the central axis algorithm. The second step is to acquire the optimal texture feature parameters. This step is mainly achieved by using the variance of secondary statistics of these two texture features to get four statistics and then finding the impact factors of gray level co-occurrence matrix relying on the relationship between the secondary statistic values and the pixel pitch. Finally, the five-dimensional feature vectors extracted from the sample image are fed into the fisher classifier.
Findings
The improvement of identification accuracy can be achieved by determining the optimal feature parameters and fusing two texture features. The average identification accuracy is 96.713% in this paper, which is very helpful to improve the efficiency of detector in the textile industry.
Originality/value
In this paper, a novel identification method which extracts the optimal feature parameter is proposed.
Keywords
Acknowledgements
This work was support by the program general projects of Shaanxi Provincial Department of Science and Technology Key R&D (No.2019GY-098), the service local science research plan of Shaanxi Provincial Department of education (No.18JC012), Science and technology innovation new town project of Yulin science and Technology Bureaugs3: (No.2018-2-24), Shaoxing Keqiao District West Textile Industry Innovation Research Institute Project (No.19KQYB10) and Yulin City Science and Technology Plan Project (No.CXY-2020-052).
Citation
Zhu, Y., Huang, J., Wu, T. and Ren, X. (2022), "An identification method of cashmere and wool by the two features fusion", International Journal of Clothing Science and Technology, Vol. 34 No. 1, pp. 13-20. https://doi.org/10.1108/IJCST-06-2020-0101
Publisher
:Emerald Publishing Limited
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