WuL.ChenS., Intelligent welding technology. Defence Industry Press, Beijing, 2000.
2.
WilsonM., The role of seam tracking in robotic welding and bonding. The Industrial Robot.Vol. 29, No. 2, 132–137, 2002.
3.
KuoH. C.WuL. J., An image tracking system for welded seams using fuzzy logic. Journal of Materials Processing Technology, Vol. 120, No. 2, 169–185, 2002.
4.
CederbergP.OlssonM.BolmsjöG., Virtual triangulation sensor development, behavior simulation and CAR integration applied to robotic arc-welding. Journal of Intelligent and Robotic Systems.Vol. 35, No. 4, 365–379, 2002.
5.
LiY.XuD.LiT., Seam tracking sensor based on laser structured light. Chinese Journal of Sensors and Actuators, Vol. 18, No. 3, 488–492, 2005.
6.
HaugK.PritschowG., Reducing distortions caused by the welding arc in a laser stripe sensor system for automated seam tracking. Industrial Electronics. Proceedings of the IEEE International Symposium on 12—16 July 1999, Tunisia, Vol. 2, 919–924.
7.
SicardP.LevineM. D., Joint Recognition and Tracking for Robotic Arc Welding. IEEE Transaction on Systems, Man, and Cybernetics, Vol. 19, No. 4, 714–728, 1989.
8.
LiG.WangG.ZhongJ., A genetic algorithm on welding seam image segmentation. Fifth World Congress on Intelligent Control and Automation. WCICA 2004, Hangzhou, China. Vol. 3, 15—19 June 2004, 2176–2178.
9.
OtsuN., A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, No. 1, 62–66, 1979.
10.
LiuJ.XieW.GaoX., Multi-thresholded image segmentation with genetic algorithms. Pattern Recognition and Artificial Intelligence, Vol. 8, A01. 126–132, 1995.
11.
UzunI. S.AmiraA.BouridaneA., FPGA implementations of fast Fourier transforms for real-time signal and image processing. IEE Proceedings Vision, Image and Signal ProcessingVol. 152, Issue 3, 3 June 2005, 283–296.
12.
ZhouY.CaiZ.ZhangH., A welding seam recognition method Based on Wavelet transform and Hough transform. The seventh International Conference on Electronic Measurement and Instruments. Vol. 6, 269–273, Beijing, China, 2005.
13.
LiuX.WangG.ShiY., Image processing of welding seam based on single-stripe laser vision system. Sixth International Conference on Intelligent Systems Design and Applications, Vol. 2, 463–470, Jinan, China, 2006.
14.
LiX.ZhuS., Survey of Wavelet Domain Image Denoising. Journal of Image and Graphics, Vol. 11, No. 9, 1201–1208, 2006.
15.
WangD.Haese-CoatV.BrunoA.. Some statistical properties of mathematical morphology. IEEE Transactions on Signal Processing, Vol. 43, No. 8, 1955–1965, 1995.
16.
CaiC.LiuM.DingM.. Morphological edge detector based on partial differential equations. Journal of Huazhong University of Science and Technology, Vol. 31, No. 10, 1–3, 2003.
17.
XuD.JiangZ.WangL.. Features Extraction for Structured Light Image of Welding Seam with Arc and Splash Disturbance. The Eighth International Conference on Control, Automation, Robotics, and Vision, Kunming, China, December, 1559–1563, 2004.
18.
ZouB.WuJ.ZhangH., A new algorithm for segmentation of weld seam images based on mathematical morphology. The seventh International Conference on Electronic Measurement and Instruments. Vol. 6, 471–473, Beijing, China, 2005.
19.
HaugK.PritschowG., Robust laser stripe sensor for the automated weld seam tracking in the shipbuilding industry. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society. 31 Aug. 4 Sept. Germany, Aachen, 1998, Vol. 2, 1236–1241.
20.
KimJ. S.SonY. T.ChoH. S., A robust method for vision-based seam tracking in robotic arc welding. The 10th IEEE International Symposium on Intelligent Control, Piscataway, USA, 1995, 363–368.
21.
KunttulI.LepistölL.RauhamaaJ.. Multiscale Fourier descriptor for shape classification. Proceedings of the 12th International Conference on Image Analysis and Processing, 536–541, Mantova, Italy, 2003.
22.
LiY.XuD.TanM., Welding joints recognition based on Hausdorff distance. Chinese High Technology Letters.Vol. 16, No. 11, 1129–1133, 2006.
23.
HuttenlocherD. P.KlandermanG. A.RucklidgeW., Comparing images using the Hausdorff distance. IEEE Transaction on Pattern Analysis and Machine Intelligence.Vol. 15, No. 9, 850–863, 1993.
24.
YueH.SunL.LiK., Research on recognition of the seam type based on adaptive resonance theory network. China Mechanical Engineering, Vol. 10, No. 8, 894–896, 1999.
25.
WuJ.SmithJ. S.LucasJ., Weld bead placement system for multipass welding. IEE Proc. Science, Measurement and Technology, Vol. 143Iss. 2, 85–90, March 1996.
26.
Janabi-SharifiF.WilsonW. J., Automatic Selection of Image Features for Visual Servoing. IEEE Transaction on Robotics and Automation, Vol. 13, No. 6, 890–903, 1997.
27.
HuangJ.JiangL.ZouY., Wavelet transform algorithm of seam image process with DSP. Transactions of the China Welding Institution.Vol. 16, No. 11, 77–80, 2005.
28.
DuX., Research on the five freedoms visual servo control system. Doctoral dissertation, Institute of Automation, Chinese Academy of Sciences, 2004.
29.
LouX.YangD.WuY., Dynamic scene detection based on centroid characteristic model for intelligent monitor system. Computer Automated Measurement & Control, No. 12, 1345–1347, 2005.
30.
LiY.XuD.ShenY., Multi-features selection and extraction of structured light images of vision sensor for seam tracking. Chinese Journal of Sensors and Actuators, Vol. 19, No. 6, 2676–2681, 2006.