DocumentCode :
3065394
Title :
Image Processing Technology for Pipe Weld Visual Inspection
Author :
Liao, Gaohua ; Xi, Junmei
Author_Institution :
Nanchang Inst. of Technol., Nanchang, China
Volume :
1
fYear :
2009
fDate :
10-11 July 2009
Firstpage :
173
Lastpage :
176
Abstract :
To the pipeline welding defect detection, robot tracking weld reliably, the welds original image acquired by visual sensor need pretreatment to eliminate the impact of noise. A pipeline welding machine vision detection method proposed in this paper. First of all, the use of neighborhood mean filter for smoothing, the largest variance threshold method selecting adaptive threshold to segmentation image. Image after smooth will be the binarization processing. Then remove the small area noise with labeling method, get a clear image of the weld. The level of projection method to the recognition of weld image and determine the location of weld. The experiments show that the pretreatment method solute the prevailing situation of uneven illumination, and also reducing the size of the processing image, reducing the amount of data, saving time, meeting the needs of the pipeline weld tracking real-time detection, laying a solid foundation for follow-up quality inspection.
Keywords :
image segmentation; inspection; mechanical engineering computing; pipelines; reliability; welding; adaptive image thresholding; binarization processing; image processing; image segmentation; pipe weld visual inspection; pipeline welding defect detection; pipeline welding machine vision detection; robot tracking weld reliably; visual sensor; Adaptive filters; Image processing; Image segmentation; Image sensors; Inspection; Machine vision; Pipelines; Robot sensing systems; Smoothing methods; Welding; Image processing; Object recognition; computer vision; robot;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location :
Taiyuan, Shanxi
Print_ISBN :
978-0-7695-3679-8
Type :
conf
DOI :
10.1109/ICIE.2009.262
Filename :
5210863
Link To Document :
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