Robustness of Surface Roughness against Low Number of Picture Elements and Its Benefit for Scaling Analysis

Abstract

Surface roughness is widely used in the research of topography, and the scaling characteristics of roughness have been noticed in many fields. To rapidly obtain the relationship between root-mean-squared roughness (Rq) and measurement scale (L) could be helpful to achieve more understandings of the surface property, particularly the Rq-L curve could be fitted to calculate the fractal dimension (D). In this study, the robustness of Rq against low number of picture elements was investigated. Artificial surfaces and the surfaces of two actual samples (a silver thin film and a milled workpiece) were selected. When the number of picture elements was lowered, Rq was found to be stable within a large portion of the concerned scope. Such a robustness property could validate the feasibility of Rq-L curve obtained by segmenting a single morphological picture with roughness scaling extraction (RSE) method, which was proposed in our previous study. Since the traditional roughness (TR) method to obtain Rq-L curves was based on multiple pictures, which used a fixed number of picture elements at various L, RSE method could be significantly more rapid than TR method. Moreover, a direct comparison was carried out between RSE method and TR method in calculating the Rq-L curve and D, and the credibility and accuracy of RSE method with flatten order 1 and 2 was verified.

Effect of Non‐Thermal Sulfur Hexafluoride Cold Plasma Modification on Surface Properties of Polyoxymethylene

“…Figure 14 presents the quantified summary of the effect of the SF 6 plasma using the 1 C sample compiling the results of the AFM and optical profilometer roughness measurements. The dependence of the S q areal roughness parameter on the measurement window is a common fact discussed extensively in the literature [57,58] . For the self‐affine surfaces which are, often artificially generated, this dependence is linear on the log–log representation and the slope of the linear fit is related to the fractal dimension of the surface.…”

Determination of the Spatial Anisotropy of the Surface MicroStructures of Different Implant Materials: An Atomic Force Microscopy Study

“…According to the so-called roughness method [31], H iso can be evaluated from the linear fitting of the Log-Log plot of the (1) at L << ξ. Note that 0 < H iso < 1; it essentially measures how much the surface ruggedness changes towards small length scales, so that H iso closer to 0 means very jagged surface while closer to 1 means a smoother surface [3,31,32,43].…”

“…We now briefly discuss some practical aspects inherent to the methods used here. As regards the determination of H iso , we underline that several algorithms other than the "roughness method"-used in this study for its superior numerical accuracy [43]are available for extracting it from topographic images. For example, box-counting or triangulation algorithms could be used reliably [43,47]; in this case, H iso will be calculated as an average over several images all with the same (and opportune) size L.…”

“…Finally, it should be underlined that an effective limitation of using ACF or PSD functions to quantify spatial anisotropy is given, respectively, by the arbitrariness in both thresholding the ACF to determine S tr and when one measures the correct slope C α to determine H α from a single PSD. These issues may require to improve image sampling, especially on surfaces with strong height variations [43,45,46].…”

Surface Roughness Evaluation in Turning of Nimonic C263 Super Alloy Using 2D DWT Histogram Equalization

“…Electrical discharge machining was recently used to machine Nimonic super alloy (EDM) [3]. The measurement scale (L) and root mean squared roughness (Rq) are determined to comprehend the surface property based on scaling analysis [4]. Researchers have developed a method to determine the degree of tool wear by evaluating the machined surfaces' texture using an image processing methodological approach to the image of the machined surface to overcome these limitations.…”