Automatic AFM Images Distortion Correction Based on Adaptive Feature Recognition Algorithm

Atomic Force Microscope (AFM) images will appear tilt and bending of the image background due to the tilt angle between the sample surface and the probe, thermal noise of system, or external vibration of environment. Feature recognition is very crucial for removing unstable imaging background when u...

Full description

Saved in:
Bibliographic Details
Published in2020 Chinese Automation Congress (CAC) pp. 4981 - 4986
Main Authors Yang, Chengpeng, Wang, Shoujin, Hao, Chunxue, Yang, Yang, Shi, Jialin, Yu, Peng
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.11.2020
Subjects
adaptive threshold
AFM
Distortion
edge detection
Feature extraction
Fitting
Graphics
Gray-scale
horizontal distortion
Image edge detection
least squares fitting
Robots
Online AccessGet full text

Cover

More Information
Summary:Atomic Force Microscope (AFM) images will appear tilt and bending of the image background due to the tilt angle between the sample surface and the probe, thermal noise of system, or external vibration of environment. Feature recognition is very crucial for removing unstable imaging background when using the least square fitting method to horizontally correct the AFM full image, which the topography structures higher or lower than the sample substrate will affect the fitting correction results. To realize universal automatic correction of AFM images, this paper proposes an adaptive feature recognition algorithm based on improved image edge detection method to automatically identify, frame and mark the features and then remove the detorsion background using Least Squares Fitting Correction. The experiment results show that this method can realize adaptive feature recognition and automatic fitting correction of the whole image, and improve the correction accuracy.
ISSN:2688-0938
DOI:10.1109/CAC51589.2020.9327265