Authors: Haidar Jalal Ismail1 & Azeez Abdullah Barzinjy1&2 & Samir Mustafa Hamad3&4
1Department of Physics, College of Education, Salahaddin University, Erbil, Iraq
2Department of Physics Education, Faculty of Education, Ishik University, Erbil, Iraq
3Research centre, Cihan University, Erbil, Iraq
4Scientific Research Centre, Delzyan Campus, Soran University, Iraq
Abstract: The importance of nanopores increases with time due to their application. For instance, nanopores may be used to sense molecules like DNA and RNA, single proteins, etc. Sequencing by nanopore has also a possibility to be a direct, fast, and inexpensive DNA sequencing tool. Diameters of nanopores are the main keys for mentioned sensing processes. Three segmenting methods used in this study namely Thresholding, Gaussian Mixture Model-Expectation Maximization (GMM-EM) and Hidden Markov Random Field-Expectation Maximization (HMRF-EM). These methods applied on three SEM nanopore images after enhancing them through obtaining optimum parameters of CLAHE contrast-enhanced method to give high PSNR. The results of the Rand index and time of running code show that the HMRF-EM is better than GMM-EM. Hence, their segmented images are used to find out nanopore parameters including total counting pores, diameter, and porosity. The results of porosity were in good agreement with former investigations. Consequently, the HMRF-EM segmenting technique with procedures utilized in this study using image processing for finding porosity gives promising results among other examined methods.
Keywords: Nanopore, Image Segmentation, Segmentation Evaluation, GMM-EM, HMRF-EM
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