Fabric Surface Roughness Evaluation Using Wavelet-Fractal Method

Abstract

A wavelet-fractal method to calculate the fractal dimension is proposed to objectively evaluate the surface roughness of fabric wrinkle, smoothness appearance and seam pucker. The proposed method was validated using the fractal surfaces produced from the mathematical functions and compared with the box and cube counting methods. The more accurate three-dimensional mesh grid data points of wrinkle replicas, smoothness appearance replicas and seam pucker samples were obtained using a three-dimensional, noncontact scanning system. As a supplementary reference the standard roughness parameters, which differentiate the degree of fabric surface roughness, were also investigated. The results show that the fractal dimension measured by the wavelet-fractal method as well as the surface average mean curvature show the power to clearly discern the grades of wrinkle, smoothness appearance as well as seam pucker, and thus can evaluate the fabric surface roughness objectively and quantitativelyFabric appearance properties such as wrinkle, smoothness appearance and seam pucker are important factors for quality control during manufacturing as well as aesthetic aspects for consumer choice. Therefore both fabric and garment manufacturers have made considerable efforts to control the fabric roughness and to establish a test method to quantify roughness. The accurate measurement of fabric surface roughness will contribute to determining the optimum processing conditions to improve the dimensional stability of fabric properties. The evaluation method of fabric surface properties has been based on subjectively comparing the specimen with either the standard replica [2, 3] or a photographic replica [1] by well-trained observers. A considerable amount of work has been done [4, 10, 14, 18] by many researchers to precisely evaluate fabric surface roughness. In our earlier work [6, 7], we extracted the fractal dimension to describe the degree of fabric surface roughness from three-dimensional (3-D) surface data using a laser scanning method or stereo vision technique.The first critical step in grading the fabric surface properties is obtaining the 3-D coordinates of the fabric surface precisely and calculating the fractal dimension of it. With the rapid development of 3-D surface measurement technology, more accurate and finer 3-D surface data can be obtained. Using this system, it is expected that the fabric surface properties can be fully evaluated with greater accuracy. We adopted a 3-D non-contact scanning system to acquire 3-D data of the fabric surface of interest.The accurate calculation of the fractal dimension to represent the extent of the fabric surface roughness which, in our previous research, was evaluated by the application of an appropriate algorithm, remains a significant issue. Wavelet analysis has been a developing subject in recent years, especially in the field of surface metrology. Wang et al. [15,16] and Xiong et al. [17] proposed a wavelet transform method as a means to calculate the fractal dimension of surface p...

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