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《Chinese Journal of Scientific Instrument》 2011-06
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Real-time detection and segmentation of submerged-arc welding defects in X-ray radiography images

Gao Weixin1,Hu Yuheng2,Mu Xiangyang1,Wu Xiaomeng1(1 School of Electrical Engineering,Xi'-an Shiyou University,Xi'-an 710065,China;2 Dept.Electrical and Computer Engineering,University of Wisconsin-Madison,Madison WI53706,USA)  
An efficient X-ray radiography image analysis algorithm is developed for the real time detection and segmentation of submerged-arc welding defects.The raw X-ray image is first pre-processed to remove impulsive noise,enhance gray scale contrast with sin function,and segment the region of interests(ROI) where the welding image locates.Next,a segmentation method based on OTSU is studied,and examples show that the method can obtain good segmentation result.Lastly,a density based spatial clustering method is developed for defect detection and segmentation.Compared with a baseline threshold segmentation algorithm,the proposed clustering segmentation method demonstrates significant performance enhancement.100 X-ray radiography images obtained from a real factory were tested;and the proposed algorithm achieves a sensitivity of 74/78 and specificity of 19/21.Compared with previously reported algorithms,the proposed algorithm is robust,efficient and directly applicable to real world applications.
【Fund】: 陕西省自然科学基础研究计划(2010JQ8033);; 陕西省教育厅专项科研计划(08jk411);; 西安市科技计划(YF07033)资助项目
【CateGory Index】: TP391.41
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