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Reseach Article

Article:Automatic Defect Detection and Counting In Radiographic Weldment Images

by Prof.Mythili Thiruganam, Dr.S.Margret Anouncia, Sachin Kantipudi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 10 - Number 2
Year of Publication: 2010
Authors: Prof.Mythili Thiruganam, Dr.S.Margret Anouncia, Sachin Kantipudi
10.5120/1457-1971

Prof.Mythili Thiruganam, Dr.S.Margret Anouncia, Sachin Kantipudi . Article:Automatic Defect Detection and Counting In Radiographic Weldment Images. International Journal of Computer Applications. 10, 2 ( November 2010), 1-5. DOI=10.5120/1457-1971

@article{ 10.5120/1457-1971,
author = { Prof.Mythili Thiruganam, Dr.S.Margret Anouncia, Sachin Kantipudi },
title = { Article:Automatic Defect Detection and Counting In Radiographic Weldment Images },
journal = { International Journal of Computer Applications },
issue_date = { November 2010 },
volume = { 10 },
number = { 2 },
month = { November },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume10/number2/1457-1971/ },
doi = { 10.5120/1457-1971 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:58:42.476312+05:30
%A Prof.Mythili Thiruganam
%A Dr.S.Margret Anouncia
%A Sachin Kantipudi
%T Article:Automatic Defect Detection and Counting In Radiographic Weldment Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 10
%N 2
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Digital Image Analysis is one of the most challenging and important tasks in many scientific and engineering applications. Extracting the Region of Interest (ROI) from the image and recognition in image processing are very important steps. When these tasks are manually performed, it is tedious and difficult involving human experts. This paper focuses on automatic defect detection and counting in radiographic weldment images thus considering defects in weldment images as object of interest. To detect defects in radiographic weldment images, thresholding and segmentation algorithm is used and a new procedure is introduced for counting number of defects in the input images. The results obtained from the proposed work are impressive with respect to the computational time and defect detection rate. The performance of the proposed algorithm is found better than the existing defect detection algorithms.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Defect Weldment Region of Interest (ROI)