AUTOMATED LINE FLATTENING OF ATOMIC FORCE MICROSCOPY IMAGES

S. A. Tsaftaris*, J. Zujovic, A. K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, an automated algorithm to flatten lines from Atomic Force Microscopy (AFM) images is presented. Due to the mechanics of the AFM, there is a curvature distortion (bowing effect) present in the acquired images. At present, flattening such images requires human intervention to manually segment object data from the background, which is time consuming and highly inaccurate. The proposed method classifies the data into objects and background, and fits convex lines in an iterative fashion. Results on real images from DNA wrapped carbon nanotubes (DNA-CNTs) and synthetic experiments are presented, demonstrating the effectiveness of the proposed algorithm in increasing the resolution of the surface topography.

Original languageEnglish
Title of host publication2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2968-2971
Number of pages4
ISBN (Print)978-1-4244-1765-0
Publication statusPublished - 2008
Event15th IEEE International Conference on Image Processing (ICIP 2008) - San Diego, Canada
Duration: 12 Oct 200815 Oct 2008

Publication series

NameIEEE International Conference on Image Processing (ICIP)
PublisherIEEE
ISSN (Print)1522-4880

Conference

Conference15th IEEE International Conference on Image Processing (ICIP 2008)
Country/TerritoryCanada
Period12/10/0815/10/08

Keywords

  • curve fitting
  • nanotechnology
  • polynomial approximation
  • object detection

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