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DOI: 10.14569/IJACSA.2015.060516
PDF

Automatic Ferrite Content Measurement based on Image Analysis and Pattern Classification

Author 1: Hafiz Muhammad Tanveer
Author 2: Hafiz Muhammad Tahir Mustafa
Author 3: Waleed Asif
Author 4: Munir Ahmad
Author 5: Muhammad Anjum Javed
Author 6: Maqsood Ahmad

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 6 Issue 5, 2015.

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Abstract: The existing manual point counting technique for ferrite content measurement is a difficult time consuming method which has limited accuracy due to limited human perception and error induced by points on boundaries of grid spacing. In this paper, we present a novel algorithm, based on image analysis and pattern classification, to evaluate the volume fraction of ferrite in microstructure containing ferrite and austenite. The prime focus of the proposed algorithm is to solve the problem of ferrite content measurement using automatic binary classification approach. Classification of image data into two distinct classes, using optimum threshold finding method, is the key idea behind the new algorithm. Automation of the process to measure the ferrite content and to speed up specimen’s testing procedure is the main feature of the newly developed algorithm. Improved performance index by reducing error sources is reflected from obtained results and validated through the comparison with a well-known method of Ohtsu.

Keywords: Pattern classification; Decision threshold; Machine learning; Microstructure

Hafiz Muhammad Tanveer, Hafiz Muhammad Tahir Mustafa, Waleed Asif, Munir Ahmad, Muhammad Anjum Javed and Maqsood Ahmad, “Automatic Ferrite Content Measurement based on Image Analysis and Pattern Classification” International Journal of Advanced Computer Science and Applications(IJACSA), 6(5), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060516

@article{Tanveer2015,
title = {Automatic Ferrite Content Measurement based on Image Analysis and Pattern Classification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2015.060516},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060516},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {5},
author = {Hafiz Muhammad Tanveer and Hafiz Muhammad Tahir Mustafa and Waleed Asif and Munir Ahmad and Muhammad Anjum Javed and Maqsood Ahmad}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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