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| Description
| - Analysis of textile materials often includes measurement of structural anisotropy or directional orientation of textile object systems. To that purpose the real-world objects are replaced by their images, which are analyzed, and the results of this analysis are used for decisions about the product(s). Study of the image data allows to understand the image contents and to perform quantitative and qualitative description of objects of interest. This study deals particularly with the problem of estimating the main orientation of fiber systems. The methods we consider are based on the two-dimensional discrete Fourier transform combined with the method of moments. We suggest currently used global analysis of the whole image, which typically leads to just one estimate of the characteristic of interest, and advise replacing it with a local analysis. This means splitting the image into many small, non-overlapping pieces, and estimating the characteristic of interest independently of the others. As a result we obtain many estimates of the characteristic of interest, one for each sub-window of the original image, and instead of averaging them to get just one value we suggest analyzing the distribution of the estimates obtained for the respective sub-images. Method can be effectively used for estimating directional orientation of fibrous textile materials from the point of view of their homogeneity, eventual defects, random violation of regularity of the structure, etc. Change of obtained distribution of directional estimates against the expected (or desired) distribution indicates failure of regular structure. Chi-squared goodness of fit test is used as a tool for analysis of such task and it is performed on simulated and real data.
- Analysis of textile materials often includes measurement of structural anisotropy or directional orientation of textile object systems. To that purpose the real-world objects are replaced by their images, which are analyzed, and the results of this analysis are used for decisions about the product(s). Study of the image data allows to understand the image contents and to perform quantitative and qualitative description of objects of interest. This study deals particularly with the problem of estimating the main orientation of fiber systems. The methods we consider are based on the two-dimensional discrete Fourier transform combined with the method of moments. We suggest currently used global analysis of the whole image, which typically leads to just one estimate of the characteristic of interest, and advise replacing it with a local analysis. This means splitting the image into many small, non-overlapping pieces, and estimating the characteristic of interest independently of the others. As a result we obtain many estimates of the characteristic of interest, one for each sub-window of the original image, and instead of averaging them to get just one value we suggest analyzing the distribution of the estimates obtained for the respective sub-images. Method can be effectively used for estimating directional orientation of fibrous textile materials from the point of view of their homogeneity, eventual defects, random violation of regularity of the structure, etc. Change of obtained distribution of directional estimates against the expected (or desired) distribution indicates failure of regular structure. Chi-squared goodness of fit test is used as a tool for analysis of such task and it is performed on simulated and real data. (en)
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| Title
| - Estimation of Fiber System Orientation based on Image Analysis and Quality Monitoring of Fibrous Layers
- Estimation of Fiber System Orientation based on Image Analysis and Quality Monitoring of Fibrous Layers (en)
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| skos:prefLabel
| - Estimation of Fiber System Orientation based on Image Analysis and Quality Monitoring of Fibrous Layers
- Estimation of Fiber System Orientation based on Image Analysis and Quality Monitoring of Fibrous Layers (en)
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| skos:notation
| - RIV/46747885:24410/14:#0003876!RIV15-MSM-24410___
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| http://linked.open...avai/riv/aktivita
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| http://linked.open...avai/riv/aktivity
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| http://linked.open...vai/riv/dodaniDat
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| http://linked.open...aciTvurceVysledku
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| http://linked.open.../riv/druhVysledku
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| http://linked.open...iv/duvernostUdaju
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| http://linked.open...titaPredkladatele
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| http://linked.open...dnocenehoVysledku
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| http://linked.open...ai/riv/idVysledku
| - RIV/46747885:24410/14:#0003876
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| http://linked.open...riv/jazykVysledku
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| http://linked.open.../riv/klicovaSlova
| - Fiber system; Fourier analysis; Moments of image; Histogram; Chi-squared goodness of fit test (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...ontrolniKodProRIV
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| http://linked.open...in/vavai/riv/obor
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| http://linked.open...ichTvurcuVysledku
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| http://linked.open...cetTvurcuVysledku
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| http://linked.open...vavai/riv/projekt
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| http://linked.open...UplatneniVysledku
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| http://linked.open...iv/tvurceVysledku
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| http://localhost/t...ganizacniJednotka
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