|Institution:||Missouri University of Science and Technology|
|Full text PDF:||http://hdl.handle.net/10355/43410|
"Atomic force microscopy (AFM) is a versatile and powerful tool for imaging and measuring small-scale objects such as nanoparticles, single molecules, semiconductor devices and living cells. The basic operation of an AFM can be to utilize a sharp cantilever tip that interacts with the sample surface and senses the local force between the tip and sample surface. Based on the physical interaction between the AFM and the small-scale object for image acquisition, there can be a number of artifacts, including curvature distortion (bowing effects), high-frequency or low-frequency noise, which may not be easily recognized by users accustomed to conventional microscopy. In this research, different image processing functions are designed to visualize AFM data, address different types of AFM artifacts problems and analyze features. Algorithms according to AFM image processing functions are presented. Analysis of AFM images acquired from silicon chips, which are provided by the Mechanical Engineering Department at Missouri University of Science and Technology, is displayed." – Abstract, page iii.