Defect Identification and Statistics Toolbox (DIST): A Tool for Automating Defect Analysis and Statistics Generation

Widely available scanning tunneling microscopy (STM) image analysis software do not automate the process of identifying and analyzing atomic defects in images. We present the Defect Identification and Statistics Toolbox (DIST) as a solution for automated defect analysis, based in MATLAB. DIST provides a graphical user interface for interactive image processing and background noise reduction to aid in defect identification. In DIST, topographical contour plots are generated in the image to isolate defects based on their brightness compared to the background. DIST implements an ant colony optimization (ACO) algorithm [1] to compare the shapes of individual defects defined by the contour plots. DIST also automatically compiles and outputs statistics of identified defects, such as apparent height, line profiles, and area. The novel automation techniques in DIST allow users to quickly and accurately analyze hundreds of defects at a time without relying on the user to manually identify each one.

[1] O. van Kaick, et al., Proc. 15th Pacific Conference on Computer Graphics and Applications (Pacific Graphics 2007), pp. 271-280, 2007. http://dx.doi.org/10.1109/PG.2007.56