Automatic measurements of partial cover factors and yarn diameters in fabrics using image processing

Tàpias, Montserrat; Ralló, Miquel; Escofet, Jaume

doi:10.1177/0040517510380107

Cited by 18 publications

(27 citation statements)

References 16 publications

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“…Fabric digital images were captured with a microscope and preprocessed following our previous works (Tàpias et al 2010(Tàpias et al , 2011. Fig.…”

Section: Digital Images Of Fabricsmentioning

confidence: 99%

“…In order to determine the thresholds that led to the digital OF estimations we analyzed four classical global binarization algorithms (Gaussian modeling (GM), Kittler-Illingworth (K-I), Otsu and Kmeans) (Sezgin and Sankur 2004) in addition to the one proposed in our previous works (Tàpias et al 2010(Tàpias et al , 2011, the Minimum Sum of Squared Residuals (MSSQ). These five binarization algorithms were applied to the digital images of the 81 fabric samples.…”

Section: Performing Automatic Of Estimatesmentioning

confidence: 99%

“…1). OF is a critical feature regarding the end-use performance that has to be taken into consideration in the fields of protection (Gabrijelcicet al 2009;Webster et al 2009;Dimitrovski et al 2010;Gotipamul et al 2014), end-use performance (Teli et al 2008;Akgun et al 2012), thermo-physiological comfort ( € Ozc¸elik et al 2007;Lee and Obendorf 2012;Kumar and Mitra 2013) and fabric hand (Naebe et al 2013). In the specialized literature, it is more usual to deal with OF complementary, the cover factor (i.e., the fraction of the web area covered by yarns) (Marks et al 1993).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Psychophysical Validation of A Digital Method to Assess Ill‐Defined Visual Boundaries: An Example with Fabric Openness Factor

Tàpias

Ralló

Escofet

2015

Journal of Sensory Studies

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Fabric openness factor (OF) is the fraction of the web area that is uncovered by yarns. OF is a critical feature regarding the end-use performance of the fabric and should be accurately assessed.However, digital OF estimates yielded by image binarization algorithms differ among them depending on the criteria used, mainly due to ill-defined boundaries, thus precluding a PRACTICAL APPLICATIONSThis work addresses the problems that arise at the moment of measuring the area of a region with illdefined boundaries without any standard to control the process of measurement. Similar problems are also found in important fields such as medical imaging. In these cases, there are usually different digital methods that give rise to estimates of the magnitude which mismatch among them. To solve these differences, a more common approach is to use estimates provided by a panel of observers and consider them to be objective, regardless of the bias between subjective responses and actual values.However, visual estimates do not show either accuracy (because they are psychophysical measures) or precision (due to the variability among observers). To overcome these difficulties, we propose a procedure to validate a digital method through visual estimates provided by a panel of observers, taking into account the psychophysical models of Fechner and Stevens.

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“…Fabric digital images were captured with a microscope and preprocessed following our previous works (Tàpias et al 2010(Tàpias et al , 2011. Fig.…”

Section: Digital Images Of Fabricsmentioning

confidence: 99%

Section: Performing Automatic Of Estimatesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Psychophysical Validation of A Digital Method to Assess Ill‐Defined Visual Boundaries: An Example with Fabric Openness Factor

Tàpias

Ralló

Escofet

2015

Journal of Sensory Studies

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“…The end-use and performance requirements of woven fabrics are strongly related to their cover factors (CF) or in opposite terms, to their porosity and permeability [1][2][3]. Different features that are closely related to CF are weaving efficiency, fabric quality, thermo-physiological comfort of garments, air permeability and protection against ultraviolet radiation [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Effect of yarn structure on cover factor in woven fabrics

et al. 2018

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This experimental work investigates the effect of yarn structure on cover factor of fabrics at different weft settings by the light transmission method. To analyze the effect, two different types of fabric set have been prepared by using airjet and rotor yarns of the same linear densities in the weft direction and keeping the warp yarn unchanged. For each fabric, weft setting has been changed gradually. Cross-sectional diameter of yarn and its packing density has been analyzed to find out the differences between both yarn structures. The effective yarn diameter and packing density have been found to be almost same for both yarns while the hairiness is found to be higher in airjet yarn as compared to rotor yarn. Yarn cross-section in the fabric has also been analyzed to examine the deformation (flatness) in yarn, which was relatively higher in airjet yarns. At the same weft setting the cover factor (CF) of fabric woven by air jet yarn is found to be higher than fabric woven by rotor jet yarn, and this difference decreases as the weft setting increases in fabric. Correlation analysis results show the relation between the cover factor and weft setting. While analysis of variance results show statistically significant effect of spinning system (airjet and rotor yarn) and weft setting on the cover factor of woven fabric.

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“…al. [9,10] worked on automatic measurement of woven fabric cover factor using image analysis technique. They also explained that this technique exhibited good agreement between the objective values and subjective results.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Correlation of Air Permeability and Light Transmission Properties of Woven Cotton Fabrics

Nazir

Hussain

Afzal

et al. 2017

Autex Research Journal

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The aim of this study was to develop statistical models for predicting the air permeability and light transmission properties of woven cotton fabrics and determine the level of correlation between the two parameters. Plain woven fabrics were developed with different warp and weft linear densities, ends per inch and picks per inch. After desizing, scouring, bleaching, drying and conditioning, the air permeability and light transmission properties of the fabric samples were determined. Regression analysis results showed statistically significant effect of the fabric ends, picks and warp linear density on both the fabric air permeability and light transmission. Correlation analysis was performed to analyze the relation between the fabric air permeability and light transmission. A linear equation was also formulated to find the fabric air permeability through transmission of light intensity. A fitted line plot between the air permeability and light transmission exhibited significant correlation with R-sq. value of 96.4%. The statistical models for the prediction of fabric air permeability and light transmittance were developed with an average prediction error of less than 7%.

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Automatic measurements of partial cover factors and yarn diameters in fabrics using image processing

Abstract: Postprint (published version

Cited by 18 publications

References 16 publications

Psychophysical Validation of A Digital Method to Assess Ill‐Defined Visual Boundaries: An Example with Fabric Openness Factor

Psychophysical Validation of A Digital Method to Assess Ill‐Defined Visual Boundaries: An Example with Fabric Openness Factor

Effect of yarn structure on cover factor in woven fabrics

Prediction and Correlation of Air Permeability and Light Transmission Properties of Woven Cotton Fabrics

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