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	Automatic defect segmentation in X-ray images of welding seam
	Yang Jing ; Wang Mingquan ; Ren Shaoqing ; Wang Yu
	2010-10-12 ; 2010-10-12
关键词	Practical/ flaw detection image segmentation welds X-ray imaging/ automatic defect segmentation X-ray images welding seam inspective image mathematical morphology threshold selection flaw characteristic parameter extraction flaw characteristic parameter recognition/ C5260B Computer vision and image processing techniques E1630 Testing E1520E Joining processes and welding
中文摘要	The important step is how to extract and segment the information of defects from inspective image. Mathematical morphology was proposed in the study of flaw extraction technique. Therefore, the area of flaw and background can be removed successfully. In this paper, a few methods for threshold selection were analyzed. And the basic ideas of various methods as well as their advantages and defects were critically reviewed. The experimental results indicate that both of methods can accomplish defect extraction and segmentation automatically, which will lay a good foundation for flaw characteristic parameter extraction and recognition.
语种	中文
出版者	Editorial Department of Journal of Projectiles, Rockets, Missiles and Guidance ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/82558]
专题	清华大学
推荐引用方式 GB/T 7714	Yang Jing,Wang Mingquan,Ren Shaoqing,et al. Automatic defect segmentation in X-ray images of welding seam[J],2010, 2010.
APA	Yang Jing,Wang Mingquan,Ren Shaoqing,&Wang Yu.(2010).Automatic defect segmentation in X-ray images of welding seam..
MLA	Yang Jing,et al."Automatic defect segmentation in X-ray images of welding seam".(2010).

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