THE NEW IMAGE PROCESSING ALGORITHM FOR QUALITATIVE AND QUANTITATIVE STM DATA ANALYSIS

Date

2012-12

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Abstract

Image processing can be used to extract cluster parameters from STM image. The objective observation from the obtained data can be used to understand certain processes in Material Science. One such application is to study under-potential deposition where the substrate surface is modified with a sub-monolayer of different noble metal. This thesis aims to develop a user friendly GUI (Graphical User Interface) that helps researchers to draw an inference by quantifying parameters like layer coverage, nucleation density, cluster area, and perimeter by area from an STM image. It uses an algorithm that filters noise using a custom made filter mask and then applies the OTSU segmentation technique to fit Gaussian curve on the image histogram for detecting the presence of a layer(s) of cluster in the STM image. It creates a binary image for each layer detected in the image. Cluster parameters are obtained by processing this binary image.

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Keywords

Microfabrication, STM, Image processing, Matlab GUI, Software engineering, Material Science, Nanofabrication, STM Image Analysis, Algorithm Development, Image Segmentation, OTSU, Gaussian

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