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A robust method for processing scanning probe microscopy images and determining nanoobject position and dimensions
Author(s) -
SILLY F.
Publication year - 2009
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1111/j.1365-2818.2009.03191.x
Subject(s) - robustness (evolution) , position (finance) , image processing , artificial intelligence , computer science , scanning probe microscopy , computer vision , microscopy , nanoscopic scale , optics , algorithm , pattern recognition (psychology) , materials science , image (mathematics) , physics , nanotechnology , chemistry , biochemistry , finance , economics , gene
Summary Processing of scanning probe microscopy (SPM) images is essential to explore nanoscale phenomena. Image processing and pattern recognition techniques are developed to improve the accuracy and consistency of nanoobject and surface characterization. We present a robust and versatile method to process SPM images and reproducibly estimate nanoobject position and dimensions. This method is using dedicated fits based on the least‐square method and the matrix operations. The corresponding algorithms have been implemented in the FabViewer portable application. We illustrate how these algorithms permit not only to correct SPM images but also to precisely determine the position and dimensions of nanocrystals and adatoms on surface. A robustness test is successfully performed using distorted SPM images.