Directional fractal signature analysis of self-structured surface textures
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Currently available directional fractal signature (DFS) methods are not suited for self-structured surface textures since they base on the assumption of Brownian fractal or they do not use the entire image data in calculation. To address these difficulties, two new DFS methods were developed in this study, i.e., an augmented blanket with rotating grid (ABRG) method and a blanket with shearing image (BSI) method. The performance of these methods in measuring surface roughness and directionality, the capacity for quantifying multi-patterned textures, and the ability to detect differences between textures of self-structured surfaces were evaluated. The methods were compared against a blanket with rotating grid (BRG) method. Computer-generated images of self-structured surface textures with different roughness, directions and patterns, and atomic force microscope images of real self-structured surfaces were used. The computer texture images were generated using a specially developed motif-based texture generator. Results obtained showed that the ABRG method is more accurate and reliable than the BRG and BSI methods.
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Texture analysis of self-structured surfaces in formation process using directional fractal signature methodWolski, M.; Podsiadlo, P.; Stachowiak, Gwidon (2014)The range of applications for self-structured surfaces is growing. They are used to increase wear resistance, reduce friction and corrosion, and also used in design of biosensors and innovative coatings. However, to ...
Wolski, Marcin; Podsiadlo, Pawel; Stachowiak, Gwidon (2013)A new method, called augmented blanket with rotating grid (ABRG), has been proposed in our recent work on characterizing roughness and directionality of self-structured surface textures. This is the first method that ...
Wolski, M.; Podsiadlo, P.; Stachowiak, Gwidon (2014)Results obtained showed that, for the isotropic surfaces, the ABRG method is not considerably affected (i.e. <5%) by image resolution, tip size (for surfaces with large motifs) and noise levels lower than 9%. On the other ...