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Feature Extraction of Welds from Industrial Computed Radiography Using Image Analysis and Local Statistic Line-Clustering  

Hwang, Jung-Won (Dept. of Electronics Computer Eng., Hanyang Univeristy)
Hwang, Jae-Ho (Dept. of Electrical Eng., Hanbat National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.45, no.5, 2008 , pp. 103-110 More about this Journal
Abstract
A reliable extraction of welded area is the precedent task before the detection of weld defects in industrial radiography. This paper describes an attempt to detect and extract the welded features of steel tubes from the computed radiography(CR) images. The statistical properties are first analyzed on over 160 sample radiographic images which represent either weld or non-weld area to identify the differences between them. The analysis is then proceeded by pattern classification to determine the clustering parameters. These parameters are the width, the functional match, and continuity. The observed weld image is processed line by line to calculate these parameters for each flexible moving window in line image pixel set. The local statistic line-clustering method is used as the classifier to recognize each window data as weld or non-weld cluster. The sequential procedure is to track the edge lines between two distinct regions by iterative calculation of threshold, and it results in extracting the weld feature. Our methodology is concluded to be effective after experiment with CR weld images.
Keywords
Feature Extraction; Radiography; Weld Image; Line-Clustering; Local Statistics;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 C. Gueudre, J. Moysan and G. Corneloup, "Weld quality control by radioscopy using edge and area segmentation method," in Proc. of 15th WCNDT, Roma, Italy, Oct. 2000
2 N. Nafaa, D. Redouane and B. Amar, "Weld defect extraction and classification in radiographic testing based artificial neural networks," in Proc. of 15th WCNDT, Roma, Italy, Oct. 2000
3 H. I. Shafeek, E. S. Gadelmawla, A. A. Abdel-Shafy and I. M. Elewa, "Assessment of welding defects for gas pipeline radiographs using computer vision," NDT&E, Vol. 37, pp. 291-299, 2004   DOI   ScienceOn
4 황재호, "선군집분할방법에 의한 특징추출", 정보처리학회논문지 B, 제13권 B편 제4호, 401-408쪽, 2006년 8월   과학기술학회마을   DOI
5 황재호, 김원식, "순차적 층위군집(層位群集)판별에 의한 경동맥 내중막 두께 측정", 전자공학회논문지 제43권 SC편, 제5호, 89-100쪽, 2006년 9월   과학기술학회마을
6 D. Redouane, K. Yacine, A. Amal, A. Farid and B. Amar, "Evaluation of corroded pipelines wall thickness using image processing in industrial radiography," in Proc. of 15th WCNDT, Roma, Italy, Oct. 2000
7 X. Zhang and J. Xu and Y. Li, "The research of defect recongition for radiographic weld image based on fuzzy neural network," in Proc. of 5th WCICA, Hangzhou, China, June 2004
8 A. Leon-Garcia, Probability and Random Processes for Electrical. Engineering, 2nd ed., Addison-Wesley, 1994
9 H. Jagannathan, N. Bhaskar, P. Sriraman and N. A. Vijay, "A step towards automatic defect pattern analysis and evaluation in industrial radiography using digital image processing," in Proc. of 15th WCNDT, Roma, Italy, Oct. 2000
10 H. H. Barrett and W. Swindell, Radiographic imaging, Academic Press, 1981
11 T. W. Liao and J. Ni, "An automated radiographic NDT system for weld inspection:part 1-weld extraction," NDT&E, Vol. 29, no. 3, pp. 157-162, 1996   DOI   ScienceOn
12 T. W. Liao, D. Li and Y. Li, "Extraction of welds from radiographic images using fuzzy classifiers," Information Science, Vo. 126, pp. 21-40, 2000   DOI   ScienceOn
13 O. Alekseychuk, Detection of crack-like indications in digital radiography by global optimization of a probabilistic estimation function, PhD Thesis, BAM-Dissertationsreihe, Band 18, Berlin, Germany, 2006
14 R. J. Patei, "Digital applications of radiography," in Proc. of 3rd MENDT, Manama, Barain, Nov. 2005
15 E. Deprins, "Computed radiography in NDT applications," in Proc. of 16th WCNDT, Montreal, Canada, Aug. 2004
16 C. Daniel and F. S. Wood, Fitting Equations to Data, John Wiley & Sons, New York, 1980
17 C. Melvin and K. Sbdel-Hadi, "A simulated comparison of turnstile and Poisson photons for X-ray imaging," in Proc. of IEEE CCECE, pp. 1165-1170, Manitoba, Canada, May 2002
18 Y. Kabir and R. Drai, "A new co-operative segmentation method applied to X-ray images," in Proc. of 15th WCNDT, Roma, Italy, Oct. 2000