Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

Research on Weld Location Algorithm based on Active Shape Model

Authors
Meiju Liu, Jinyi Jiang
Corresponding Author
Meiju Liu
Available Online April 2017.
DOI
10.2991/emim-17.2017.53How to use a DOI?
Keywords
Weld location; ASM; Feature model; Average positioning accuracy
Abstract

In order to improve the welding quality and avoid the welding deviation, a weld seam location algorithm based on active shape model is proposed. The local feature model is set up to detect the image, and then each feature point is used to construct the local feature. Finally, the new location of the model is searched. In the experiment, the training samples are selected to model, and the test samples are used to search and locate. By comparative experiments show that the proposed algorithm has the characteristics of high accuracy, small error, and can meet the requirements of the accuracy of the laser weld positioning system.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
978-94-6252-356-2
ISSN
2352-538X
DOI
10.2991/emim-17.2017.53How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Meiju Liu
AU  - Jinyi Jiang
PY  - 2017/04
DA  - 2017/04
TI  - Research on Weld Location Algorithm based on Active Shape Model
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 249
EP  - 253
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.53
DO  - 10.2991/emim-17.2017.53
ID  - Liu2017/04
ER  -