Applying Fuzzy Hough Transform for Identifying Honed Microgeometrical Surfaces Szilvia Nagy, Levente Solecki, Brigita Sziová, Balázs Sarkadi-Nagy and László T. Kóczy Abstract In the measurement of microgeometrical surfaces it is useful if the same location can be found on a surface for two or more different and independent mea- surements, as in this case not only statistical parameters of the measurements can be compared, but direct differences can be calculated. Honing is a typical surface pro- cessing method resulting in pattern consisting of straight valleys crossing at various angles. Honing pattern is of great help to find a special location. The main goal of this article is to find a method that is able to give some characteristic points that can be used for fitting two measured surfaces together. Hough transform is used in finding straight lines in an image or map, thus it could be used for determining crossing points of the honed surface. However, classical Hough transform either finds way too many disturbing lines in the case of a typical honed surface or almost none, depending on the parameter selection. To solve this rapid changing in the number of the resulting lines, we introduced fuzzy Hough transform. If a fuzzified version of the weights of the individual points in the Hough transform is used, the inverse of the transform becomes clearer, resulting in a pattern more suitable for finding the same location on two measured versions of a surface. Keywords Fuzzy sets · Hough transform · Microgeometrical surface analysis · Pattern analysis 1 Introduction In mechanical engineering and tribology it is often necessary to classify microgeo- metrical surfaces. Usually the wear of these surfaces is described using only statistical parameters [1–4]. It would be more favourable, if the surfaces before and after wear S. Nagy (B ) · L. Solecki · B. Sziová · B. Sarkadi-Nagy Széchenyi István University, Gy˝ or 9026, Hungary e-mail: nagysz@sze.hu L. T. Kóczy Budapest University of Technology and Economics, Budapest 1117, Hungary © Springer Nature Switzerland AG 2020 L. T. Kóczy et al. (eds.), Computational Intelligence and Mathematics for Tackling Complex Problems, Studies in Computational Intelligence 819, https://doi.org/10.1007/978-3-030-16024-1_5 35