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Quantification and Morphology Studies of Nanoporous Alumina Membranes: A New Algorithm for Digital Image Processing

Published online by Cambridge University Press:  24 May 2013

Khoobaram S. Choudhari*
Affiliation:
Centre for Atomic and Molecular Physics, Manipal University, Manipal, Karnataka 576104, India
Pacheeripadikkal Jidesh
Affiliation:
Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Surathkal, Karnataka 575025, India
Parampalli Sudheendra
Affiliation:
Department of Metallurgical and Materials Engineering, National Institute of Technology Karnataka, Surathkal, Karnataka 575025, India
Suresh D. Kulkarni
Affiliation:
Centre for Atomic and Molecular Physics, Manipal University, Manipal, Karnataka 576104, India
*
*Corresponding author. E-mail: [email protected]
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Abstract

A new mathematical algorithm is reported for the accurate and efficient analysis of pore properties of nanoporous anodic alumina (NAA) membranes using scanning electron microscope (SEM) images. NAA membranes of the desired pore size were fabricated using a two-step anodic oxidation process. Surface morphology of the NAA membranes with different pore properties was studied using SEM images along with computerized image processing and analysis. The main objective was to analyze the SEM images of NAA membranes quantitatively, systematically, and quickly. The method uses a regularized shock filter for contrast enhancement, mathematical morphological operators, and a segmentation process for efficient determination of pore properties. The algorithm is executed using MATLAB, which generates a statistical report on the morphology of NAA membrane surfaces and performs accurate quantification of the parameters such as average pore-size distribution, porous area fraction, and average interpore distances. A good comparison between the pore property measurements was obtained using our algorithm and ImageJ software. This algorithm, with little manual intervention, is useful for optimizing the experimental process parameters during the fabrication of such nanostructures. Further, the algorithm is capable of analyzing SEM images of similar or asymmetrically porous nanostructures where sample and background have distinguishable contrast.

Type
Materials Applications
Copyright
Copyright © Microscopy Society of America 2013 

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