Estimation of Nano-Pore Size Using Image Processing

Abstract

A B S T R A C TNanopores, which are nanometer-sized holes, have been utilized in apparatus that point toward sensing a range of molecules such as DNA and RNA and single proteins The important factor for sensing molecules is diameters of nanopores which can be found through a substantial process called segmenting for nanopores of scanning electron microscope (SEM) images. In this investigation, four segmentation methods, namely, threshold, bilateral filter, k-means, and expectation maximizationGaussian mixture model (EM-GMM) which has been utilized to segment three SEM images of nanopores efficiently. The quality of segmentation evaluated objectively through computing Rand index among them. Consequently, the nanopore size of Al 2 O 3 films computed by means of SEM images. This study found that EM-GMM segmenting method gives promising results among other examined methods. It is for their high R-index, minimum adjustment parameters (just one variable which set usually 2), and low consuming time. Hence, it can be used efficiently for computing nanopore count and size.