The periodic woven structures of fabrics can be defined on the basis of the convolution theorem. Here an elementary unit with the minimum number of thread crossings and a nonrectangular two-dimensional comb function for the pattern of repetition is used to define woven structures. The expression derived is more compact than the conventional diagram for weaving, and the parameters that one needs to determine a given fabric can easily be extracted from its Fourier transform. Several results with real samples of the most common structures-plain, twill, and satin-are presented.

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Digital image processing techniques are applied to perform an automatic method for the objective measure of woven fabric's cover factor. Based on a frequency domain analysis, digital images of woven fabric samples, obtained with a camera assembled to a microscope, are cropped to enclose the maximum integer number of warp and weft periods and leveled for non-uniform illumination. Posterior thresholding, designed to perform suitably for both high and low cover factor fabric samples, gives rise to the objective value. The method has been applied to three different sets of samples manufactured in plain weave, with known yarn numbers and thread counts. Cover factors obtained by this method show good correlation with those obtained by a set of visual observers and are consistent with woven fabric parameters: yarn numbers (tex) and thread counts (yarns/cm). The procedure can be useful to monitor mean cover factor as well as cover factor variability in fabric batches. It does not require sophisticated equipment and can be straightforwardly implemented in a textile analysis laboratory. Keywords-Image analysis, cover factor, woven fabrics CF is a basic construction parameter of woven cloth related to its end use performance [2,3]. Weaving efficiency, fabric quality [4,5], thermo-physiological comfort of garments, air permeability [6] as well as protection against Ultra Violet Radiation [7] are features strongly related to CF. It is a fundamental feature of multiple base fabrics used in the elaboration of

It is widely accepted that cellular microprojections (microvilli and/or microplicae) of the corneal surface are essential to maintain the functionality of the tissue. To date, the characterization of these vital structures has been made by analysing scanning or transmission electron microscopy images of the cornea by methods that are intrinsically subjective and imprecise (qualitative or semiquantitative methods). In the present study, numerical data concerning three microprojection features were obtained by an automated method and analysed to establish which of them showed less variability. We propose that the most stable microprojection characteristic would be a useful sign in early detection of epithelial damage or disease. With this aim, the scanning electron microscopy images of 220 corneal epithelial cells of nine rabbits were subjected to several image processing techniques to quantify microprojection density, microprojection average size and surface covered by microprojections (SCM). We then assessed the reliability of the methods used and performed a statistical analysis of the data. Our results show that the thresholding process, the basis of all image processing techniques used in this work, is highly reliable in separating microprojections from the rest of the cell membrane. Assessment of histogram information from thresholded images is a good method to quantify SCM. Amongst the three studied variables, SCM was the most stable (with a coefficient of variation of 15.24%), as 89.09% of the sample cells had SCM values ≥ 40%. We also found that the variability of SCM was mainly due to intercellular differences (the cell factor contribution represented 88.78% of the total variation in the analysed cell areas). Further studies are required to elucidate how healthy corneas maintain high SCM values.

Two descriptions of the image of a web structure, a convolution model and an additive model, in both the spatial and frequency domains, are combined in the design of a method to extract information about the fabric structure by image analysis. The method allows the extraction of the conventional and also the minimal weave repeats, their size in terms of number of threads, their interlacing patterns, and their patterns of repetition. It is applicable to fabrics with square and nonsquare conventional weave repeat. Experimental results with image of real samples are presented and discussed.