This paper presents the development of a fairly new fractal analysis method (Extended Morphological Fractal Analysis) that aims at characterizing polar fleece fabric appearance after abrasion. At the same time, we also study the psychological behaviors during subjective evaluating process to extract the essential features for the most effective image analysis. The digital gray level image is treated as a three-dimensional surface whose fractal dimension is calculated by performing a series of dilation and erosion on this surface and plotting the area of the resulting set of surfaces against the size of the structuring element. In contrast to single morphological fractal parameter, which is scale-invariant, extended fractal analysis is able to characterize fabric textures where the roughness of these textures is not necessarily scale-invariant. This approach can be applied to describe the surface roughness and texture regularity physically by using the parameter-MFV (Multiscale Fractal Vector) and classify the appearance grade by using Bayes Classification method. The experimental results in our research demonstrate that good correlation can be established between calculated subjective grade and subjective grade.
|Title of host publication||[Missing Source Name from PIRA]|
|Publication status||Published - 2001|
|Event||Asian Textile Conference [ATC] - |
Duration: 1 Jan 2001 → …
|Conference||Asian Textile Conference [ATC]|
|Period||1/01/01 → …|