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Abstract

A new evaluation system is presented for measuring the smoothness appearance of fabric surfaces objectively and quantitatively. In this system, the contour of the fabric surface is measured with the stereo vision algorithm, and the data are then used to evaluate fabric smoothness by fractal geometry, which explicitly explains the degree of ruggedness of the fabric surface as a decimal fraction with precise grading. This study illustrates the stereo vision technique and its image processing for 3D measurements of surface contours using AATCC Test Method 124. The fractal dimensions of replicas are obtained by a fractal geometry algorithm such as reticular cell counting or cube counting. A new equation is established from a linear regression between the fractal dimensions of replicas and their grades. The experimental results show that the new grading based on 3D vision and the fractal dimension corresponds to a visual assessment of fabric smoothness with more accuracy and reliability. The new equation based on the fractal dimension should determine an objective rating of fabric smoothness that can substitute for the conventional subjective AATCC rating method for fabric smoothness and provide a quantitative reliable value to assess fabric smoothness with more accuracy and reproducibility.

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New Objective Evaluation of Fabric Smoothness Appearance

Abstract

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References