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Statements

Subject Item
n2:RIV%2F46747885%3A24410%2F14%3A%230003876%21RIV15-MSM-24410___
rdf:type
n9:Vysledek skos:Concept
dcterms: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.
dcterms: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
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
skos:notation
RIV/46747885:24410/14:#0003876!RIV15-MSM-24410___
n3:aktivita
n8:I n8:P
n3:aktivity
I, P(EE2.3.30.0065)
n3:dodaniDat
n7:2015
n3:domaciTvurceVysledku
Tunák, Maroš
n3:druhVysledku
n4:O
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n11:predkladatel
n3:idSjednocenehoVysledku
15060
n3:idVysledku
RIV/46747885:24410/14:#0003876
n3:jazykVysledku
n16:eng
n3:klicovaSlova
Fiber system; Fourier analysis; Moments of image; Histogram; Chi-squared goodness of fit test
n3:klicoveSlovo
n5:Histogram n5:Fiber%20system n5:Moments%20of%20image n5:Fourier%20analysis n5:Chi-squared%20goodness%20of%20fit%20test
n3:kontrolniKodProRIV
[ADABF4059CB2]
n3:obor
n14:JS
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
2
n3:projekt
n13:EE2.3.30.0065
n3:rokUplatneniVysledku
n7:2014
n3:tvurceVysledku
Tunák, Maroš Antoch, J.
n10:organizacniJednotka
24410