Abstract
In order to establish an objective, stable and efficient wrinkle evaluation system for fabric wrinkle evaluation, a method based on 2-D Gabor transform was proposed. Among this system, the directions of Gabor filter were determined according to the range of amplitude response. Then a set of Gabor filters were obtained by selecting and optimizing the central frequency, the half peak bandwidth and the shape factor of the Gaussian surface. After Gabor transform by such filter bank, the amplitudes of different response spectrums were extracted, constructing a multi-dimensional feature vector. Finally, the feature vectors of the fabric image samples, whose wrinkle degrees were evaluated manually in advance, were extracted and used to train a support vector machine (SVM), which achieved 81.82 % evaluation accuracy on the 345 samples. The trained SVM was applied to evaluate the wrinkle degree of the fabric samples acquired in different illumination directions, and verified the stability of the proposed method to illumination environment. Compared with the existing method, the proposed method has higher classification accuracy. The comparison results indicate the Gabor amplitude feature proposed by this research has a high correlation with the fabric wrinkle grades.
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Acknowledgment
This work was supported by the National Key R&D Program of China (Grant number 2017YFB0309200), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant number KYCX191878), the China Postdoctoral Science Foundation Funded Project (Grant number 2018M640453) and the Jiangsu Province Postdoctoral Science Foundation (Grant number 2018K037B).
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Shi, K., Wang, J., Wang, L. et al. Objective Evaluation of Fabric Wrinkles Based on 2-D Gabor Transform. Fibers Polym 21, 2138–2146 (2020). https://doi.org/10.1007/s12221-020-9699-9
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DOI: https://doi.org/10.1007/s12221-020-9699-9