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1 article(s) from Ren, Shuai

Robust nanobubble and nanodroplet segmentation in atomic force microscope images using the spherical Hough transform

Yuliang Wang,
Tongda Lu,
Xiaolai Li,
Shuai Ren and
Shusheng Bi

Beilstein J. Nanotechnol. 2017, 8, 2572–2582, doi:10.3762/bjnano.8.257

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Figure 1: Segmentation of nanobubble AFM images using the thresholding method. (a) In a raw AFM image with a ...

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Figure 2: AFM height images of nanobubbles and nanodroplets. (a) and (d) are the polystyrene and HOPG surface...

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Figure 3: Sketch of the morphological characterization and AFM tip correction for nanobubbles and nanodroplet...

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Figure 4: Illustration of the proposed two-step nanobubble/nanodroplet (NB/ND) segmentation based on the sphe...

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Figure 5: Schematic diagram showing the principle of the spherical Hough transform. (a) Calculation of gradie...

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Figure 6: Demonstration of the spherical Hough transform detection of an nanobubble. (a) Gradient vector calc...

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Figure 7: Demonstration of contour expansion operation to obtain the optimized boundary detection for a nanob...

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Figure 8: Comparison of nanobubble detection in a raw AFM image with the (a) thresholding method, (b) circle ...

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Figure 9: Robustness of the proposed method in nanobubble image segmentation with uneven background. Nanobubb...

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Figure 10: Segmentation result for a NB (a) and ND (b) in AFM images using the proposed method. The scale bar ...

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Figure 11: Comparison of three different automated morphological characterization methods for nanobubbles. (a)...

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Figure 12: Automated morphological characterization of nanobubbles (NBs) and nanodroplets (NDs). (a) The heigh...

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Full Research Paper

Published 01 Dec 2017

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