The regular periodic nature of many textile patterns permits Fourier transform techniques in image processing to be used to measure their visual characteristics. In carpets, the patterns may be due to either the arrangement of the pile or the repetition of a colored design. The Fourier power spectrum provides a useful description of the spatial frequency content in a digital image, and in particular the coarseness of any texture present. It is also an intermediate step in deriving the two-dimensional autocorrelation function, which graphically describes the translational and rotational symmetry of an image. The cross-correlation function enables comparisons of similar patterns to be made and gives a means of measuring the changes in pattern definition that arise from wear. The low or high frequency components in an image can be suppressed with appropriate Fourier masks, allowing the pile texture or the colored pattern in a patterned carpet to be enhanced. This sort of transformation permits image processing methods that have proved useful in measuring the pile texture in plain carpets to be applied to patterned types.Fourier transform concepts provide a unifying mathematical approach to the study of a wide range of phenomena in physics and engineering [2]. These studies encompass the theory of electrical networks and antennas and the acquisition and presentation of data. In this paper, we examine the application of the two-'

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To use wool successfully in technical applications requires a high-value application that can exploit its natural properties, a reduction in costs, or modifying the fibre to achieve a particular target performance. Wool is increasingly heing used in technical applications in which its unique properties and the opportunities for specific enhancements can be profitably utilised. This paper examines wool's attributes for technical textiles and introduces a wide range of new and future applications, with particular reference to developments emerging from wool-based projects at Canesis Network Ltd.

Image analysis techniques have been applied to the objective measurement of carpet texture. By converting an image into a form that highlights the regions of largest intensity variation, small differences in texture between carpets, due to either wear treatment or construction, can be reliably detected. This has been demonstrated using sets of samples that have received controlled wear treatments in the Hexapod tumbler tester. The optimum conditions for texture measurement are discussed, in particular the requirements for lighting and camera focusing. The influences of sample orientation and substrate color are also stressed. While the emphasis in this study is on plain shade carpets, possible methods of measuring the pile texture of colored pattern carpets are also discussed. Image analysis is considered to have a promising future as a scientific tool in studying carpet performance, as an objective means of carpet grading, and for product optimization and quality control in carpet manufacture.

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A review is presented of the WRONZ approach for measuring carpet appearance using digital image analysis. The emphasis in this paper is on practical aspects, and it highlights recent research findings, particularly the benefits of high-pass filtering. Var ious parameters that are considered to be necessary to fully characterize the textural properties of new and worn carpets are defined, illustrated, and discussed. Texture parameters include tuft definition, pile lightness, texture coarseness, directionality, coherence, tuft-size uniformity, and bright-spot density. The relative importance of these parameters in describing initial carpet texture and the changes in texture caused by wear depends on the kind of carpet being measured. Potential applications of the technology to quality control in carpet manufacture are now being explored with the cooperation of a local mill.

Texture change (or retention) is an important aspect of a carpet's performance in use. Objective measurement of texture change using image analysis has become a useful tool for assessing the textural quality of carpets. This paper discusses a new approach to measuring changes in carpet texture by analyzing the Fourier power spectra of the images of control (unworn) and worn carpets. Through a series of steps involving analysis of the intensity profile of a carpet image using template matching, pre-processing by high-pass filtering, and reduction to a one-dimensional spectrum by taking the rotationally averaged power spectrum of the carpet image, a feature can be extracted that represents the pile texture change. The algorithm has been tested experimentally using a range of carpet types, including those that have been difficult to measure reliably with other image analysis algorithms. The new measure agrees well with the subjective impression of tuft texture change and wear, and excellent discrimination between different levels of wear has been achieved in all cases.Much work has been done on the objective evaluation of carpet texture using image analysis, including co-occurrence matrix analysis [ 5,11,7 ] , edge detection [ 12 ] , particle analysis [ 16 ] , and Fourier techniques [ 13 ] . All of these approaches are applicable to certain carpet types, but a universal method for quantifying the texture of all carpets has yet to be devised.To quantify texture change in carpets, we have derived and applied a method based on mathematical analysis of the change in a digital image of the tuft shape. This method provides a more reliable measure of the severity of carpet texture change than subjective approaches. In this paper, we propose a measure calculated from Fourier power spectrum analysis using a template matching technique. Measuring Tuft Distortion by Template MatchingThe three-dimensional tuft structure in the carpet has a considerable influence over the nature of the image of the carpet. The difference in tuft structure between the new and worn carpet is usually very pronounced..There is a high level of contrast between the tips of tufts and the background (the voids between the tufts) when the tufts (or loops) are well defined, as in a new carpet sample. Taking a line of pixels from the image of a new carpet sample, the intensity profile formed by the tufts and the background resembles a sine-squared function. As the carpet undergoes wear, however, the tips of tufts become less well defined through untwisting of the fiber components and crushing and matting of the pile. The distorted tufts gradually lose their discrete nature and merge to form a more uniform surface; the sinusoidal intensity profile of the tufts becomes distorted and flattened, so that in extreme cases the tuft structure is almost undiscemible.Measurements of the presence and degree of distortion of these peaks in the intensity profile will represent the degree of degradation of tuft definition. Thus a comparison of the variation of the inten...

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