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Reseach Article

Automated 3D Quantitative Analysis of Digital Microstructure Images of Materials using Stereology

Published on February 2014 by P. S. Hiremath, Anita Sadashivappa
National Conference on Recent Advances in Information Technology
Foundation of Computer Science USA
NCRAIT - Number 4
February 2014
Authors: P. S. Hiremath, Anita Sadashivappa
e5d6ddd1-0b40-4579-bfd1-84b4da075c20

P. S. Hiremath, Anita Sadashivappa . Automated 3D Quantitative Analysis of Digital Microstructure Images of Materials using Stereology. National Conference on Recent Advances in Information Technology. NCRAIT, 4 (February 2014), 25-32.

@article{
author = { P. S. Hiremath, Anita Sadashivappa },
title = { Automated 3D Quantitative Analysis of Digital Microstructure Images of Materials using Stereology },
journal = { National Conference on Recent Advances in Information Technology },
issue_date = { February 2014 },
volume = { NCRAIT },
number = { 4 },
month = { February },
year = { 2014 },
issn = 0975-8887,
pages = { 25-32 },
numpages = 8,
url = { /proceedings/ncrait/number4/15165-1434/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Recent Advances in Information Technology
%A P. S. Hiremath
%A Anita Sadashivappa
%T Automated 3D Quantitative Analysis of Digital Microstructure Images of Materials using Stereology
%J National Conference on Recent Advances in Information Technology
%@ 0975-8887
%V NCRAIT
%N 4
%P 25-32
%D 2014
%I International Journal of Computer Applications
Abstract

In material testing process, the assessment of 3D geometry from 2D microstructure images of materials using stereological methods seems to gain more importance. An exclusive field by name Stereology (collection of stereological methods) has evolved to address the quantitative analysis of materials. The stereology by manual practice is tiresome, time consuming and often produce biased results due to manual physiological limits. There is a definite need for automation of stereological procedures that can make greater impact on quality of quantitative analytical results. In this paper, an automated method to derive quantitative description of 3D geometry based on data obtained by quantitative image analysis of 2D digital microstructure images is proposed. The proposed method makes use of stereological parameters and digital image processing techniques for estimation of many stereological parameters (proposed by American Standard for Materials - ASM). The results obtained by proposed method correlate with the results obtained by manual methods satisfactorily. Further, it saves considerable amount of effort, time and cost in material testing process. Since the basic frame-work of the proposed method considers many quantifiable parameters which are otherwise difficult in manual process, it has practical significance in material testing laboratories.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Stereology Otsu's Segmentation Cast Iron Microstructure.