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- W1998062757 abstract "A novel approach is proposed for representing fabric texture orientations and recognizing weave patterns. Wavelet packet transform is suited for fabric image decomposition in fabric texture. Since different weave patterns have their own regular orientations in original image and sub-band images decomposed by Wavelet packet transform, and the regular orientations can be represented as the energy distributions of these images because the average energies of different fabric texture directions are changeable in a certain way. These energy orientations features are extracted and used as SOM and LVQ inputs to achieve automatic recognition of fabric weave. The experimental results show that the neural network of LVQ is more effective than SOM. The contribution of this study is that it not only can identify fundamental fabric weaves but also can classify some complex weaves." @default.
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- W1998062757 date "2013-09-01" @default.
- W1998062757 modified "2023-09-26" @default.
- W1998062757 title "Fabric Weave Pattern’s Recognition Based on Texture Orientation Features" @default.
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- W1998062757 doi "https://doi.org/10.4028/www.scientific.net/amm.423-426.2404" @default.
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