extraction defects of radiographic images using local information in transform domain

Subject Areas : Electronics Engineering

zahra mousavi ¹ , Ahmad Keshavarz ²

1 - Department of Electrical Engineering, Islamic Azad University, Bushehr Branch, Bushehr, Iran
2 - Assistant Professor, Bushehr Persian Gulf University, Department of Electricity, Bushehr, Iran

Received: 2017-07-15 Accepted : 2017-07-15 Published : 2017-04-21

Keywords:

Abstract :

Radiography is one of most common methods for testing the quality of weld. At present radiographic images are interpreted by humans. In order to increase accuracy and speed of interpretation and costs decrease ,We are looking for a way to automatic detect of weld defects. The correct extraction of defects is The most important step to automatic processing.  Therefore ,in this paper a new strategy to extract the weld defects using image processing techniques is proposed.  In the proposed method after segmentation Region Of Interest (ROI), histogram matching and Weiner filter were used to remove noise and enhance the quality of image, then For optimum utilization of image data in different directions, Wavelet transform is used. Afterward by applying techniques such as local thresholding, morphology and edge detection on the components of the wavelet transform defect area of Radiography images was extracted

References:

1-                 دادخواه، امیر و سعید رضا،1390، تکنولوژی بازرسی جوش، چاپ سوم، تهران، انتشارات آزاده، صفحه 284

[2] Arulmozhi N, Manoharan N, Sheela RB, Venkatraman B, Baldev R. Isolation of defects in radiographic weld images with wavelet denoising using Log-Gabor filter. Int Conf Comput Intell Multimedia Appl 2007:394–9.

[3]Barbara Burke Hubburd, "The World According to Wavelets",A.K.Peters, 1998.

[4] Coltuc D, Bolon P, Chassery JM. Exact histogram specification. IEEE Trans Image Process 2006;15(5):1143–52

[5] C. Sidney Burrus, Ramesh A. Gopinath, Haitao Guo,"Introduction to Wavelets and Wavelet Transforms: A Primer,Prentice Hall, 1997.

[6] daSilvaRomeuR,SiqueiraMarcioHS,VieiradeSouzaMarcos Paulo, Rebello Joawidetildeo MA,Calowidehatb LuizP.Estimatedaccuracyofclassification of defectsdetectedinweldedjointsbyradiographytests.NDTEInt 2005;38:335–43.

[7] Frosio I, Lucchese M, Lissandrello F, Borghese NA. Automatic contrast enhancement in digital radiography. Nucl Sci Symp Conf 2008:4331–4.

[8]Gonzalez,R.c.and Woods,R.H. [2002].Digital Image Processing.2 nd.,Prentice Hall,Upper Saddle River,Nj.

[9]Gonzalez,R.c.and Woods,R.E.and Edding s.I,” Digital Image Processing using matlab “,last Edition,prentice Hall inc,2004

[10] KasbanH,ZahranO,ArafaH,El-KordyM,ElarabySayedMS,AbdEl-SamieFE. Welding defectdetectionfromradiographicimageusingcepstralapproach. NDT EInt2011;44(2):226–31.

[11] Kasban H, Zahran O, Arafa H, El-Kordy M, Elaraby, Sayed MS, et al. Quanti- tative and qualitative evaluation of gamma radiographic image enhancement. Int J Signal Process Image Process Pattern Recognition 2012;5(2):73–87.

 [12] Li, X., Tso, S. K., Guan, X., Huang, Q. (2006), "Improving Automatic Detection of Defects in Castings by Applying Wavelet Technique", IEEE Transactions on Industrial Electronics,vol. 53, no. 6, pp. 1927-1934

[13] LiaoTW,NiJ.AnautomatedradiographyNDTsystemforweldinspection: Part II.FlawDetection.NDTEInt1998;31(3):183–92.

[14] Juan Zapata, Rafael Vilar, Ramón Ruiz. "Performance evaluation of an automatic inspection system of weld defects in radiographic images based on neuro-classifiers." Expert Systems with Applications 38.7 (2011): 8812-8824.

[15] SaravananT,BagavathiappanS,PhilipJ,JayakumarT,RajB.Segmentationof defects fromradiographyimagesbythehistogramconcavitythreshold method. Insight2007;49(10):578–84.

 [16] SilvaRR,MeryD.State-of-the-artofweldseaminspectionbyradiography testing: PartI:imageprocessing.MaterEval2007;65(6):643–7.

[17] Wang G, Liao TW. Automatic identification of different types of welding defects in radiographic images. NDT E Int 2002;35:519–28.

 [18] WangG,LiaoTW.Automaticidentificationofdifferenttypesofwelding defects inradiographyimages.NDTEInt2002;35:519–28.

[19] Wang X, Wong BS, Tui CG, Khoo KP, Foo F. Image enhancement for radio- graphic non-destructive inspection of the aircraft. In: Proceedings of Asia– Pacific Conference on NDT, New Zealand; 2006.

[20] Zahran, O., Kasban, H., El-Kordy, M., El-Samie, F.E.A.," Automatic weld defect identification from radiograp imagehics ", NDT &E International (Elsevier), July, 2013, vol. 57.pp. 26-35.