DocumentCode :
2794402
Title :
Application of Fuzzy Enhancement Algorithm and KSW Entropy Algorithm in Segmentation of Pre-welding Seam Image
Author :
Liu, Xiwen ; Wang, Guorong ; Shi, Yonghua
Author_Institution :
Dept. of Mech. Eng., South China Univ. of Technol., Guangzhou
Volume :
1
fYear :
2006
fDate :
16-18 Oct. 2006
Firstpage :
260
Lastpage :
263
Abstract :
Fuzzy enhancement algorithm and KSW entropy algorithm are proposed for pre-welding seam image segmentation. Before automatic welding, the welding seam image is often segmented so that it can be recognized by robot. KSW entropy algorithm is an effective way for segmentation. Image enhancement is often applied before segmentation in order to get better result. As the pre-welding seam image is not uniform, the effect is not ideal after applying regular enhancement algorithm and KSW entropy algorithms to it. Fuzzy enhancement algorithm can eliminate the noises and preserve the details of the image intelligently. The image dividing point has close relation with the result of fuzzy enhancement algorithm. Self adapting algorithm about how to get the proper image dividing point is discussed. When fuzzy enhancement algorithm and KSW entropy segmentation algorithm are used to pre-welding seam image, the experiment results prove that the best effect can be got and little time will be cost
Keywords :
entropy; fuzzy set theory; image denoising; image enhancement; image segmentation; robotic welding; KSW entropy; automatic welding; fuzzy enhancement; image denoising; image enhancement; prewelding seam image segmentation; welding robots; Entropy; Histograms; Image edge detection; Image enhancement; Image processing; Image segmentation; Mechanical engineering; Robot vision systems; Robotics and automation; Welding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
Type :
conf
DOI :
10.1109/ISDA.2006.101
Filename :
4021446
Link To Document :
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