Fringe analysis is a commonly used method to quantify soot nanostructures. However, the settings of the involved filters and their impact on the results are rarely addressed. In this study, the influence of the three filter parameters as well as two aspects of the image acquisition was assessed experimentally. For the analysis, a carbon black as well as one diesel engine and one gasoline direct injection (GDI) engine soot sample were used. Gaussian low-pass filter standard deviations larger 1.5 yielded only minor differences in fringe metrics. Standard deviations between 2.0 and 3.0 enabled realistic representation of fringes. A linear correlation was found between the white top-hat transformation disk size and all fringe analysis metrics. For realistic nanostructure representation, disk sizes of 5 px and 7 px are most suitable. Threshold values as calculated by Otsu's method generally yielded the best nanostructure representation. Any deviation distorted the extracted fringes and noticeably reduced their total number. Thus, consistent use of Otsu thresholds without alterations is advised. Deviating from the neutral electron microscope focus point by under- and over-focusing resulted in distinctive drops in both fringe lengths and Otsu thresholds. Consistent focusing with the help of fast Fourier transformations of the respective particles is vital for reliable results. The effect of reduced noise levels by repeated averaged images was found to be minor beyond the model of the camera used. The region of interest size correlated linearly with the number of extracted fringes, however, it did not affect the fringe metrics. For statistically reliable analysis, a minimum of 4000 fringes is suggested. The GDI sample exhibited the shortest fringes and the highest tortuosity. For diesel soot and carbon black, similar fringe lengths could be observed. The highest tortuosity was found for GDI soot, followed by diesel soot and carbon black. (C) 2019 The Author(s). Published by Elsevier Inc. on behalf of The Combustion Institute.