Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)

A novel contour extraction algorithm based on dynamic programming in sausage visual inspection system

Authors
Liang Gao, Shuai Chen, Yue Ma
Corresponding Author
Liang Gao
Available Online December 2016.
DOI
10.2991/eeeis-16.2017.10How to use a DOI?
Keywords
Contour Extraction; Dynamic Programming; Visual Inspection.
Abstract

In order to overcome the influence of black region or complicated texture and extract a smooth contour, this paper provides a novel contour extraction algorithm based on twice dynamic programming. The final contour is extracted by a weighted average of the two contours, and control points optimization method is used to improve real-time and accuracy performance. The algorithm has been used in a sausage visual inspection system, and is proved effective in extracting smooth contour of sausages with complicated texture.

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 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
Series
Advances in Engineering Research
Publication Date
December 2016
ISBN
978-94-6252-320-3
ISSN
2352-5401
DOI
10.2991/eeeis-16.2017.10How 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  - Liang Gao
AU  - Shuai Chen
AU  - Yue Ma
PY  - 2016/12
DA  - 2016/12
TI  - A novel contour extraction algorithm based on dynamic programming in sausage visual inspection system
BT  - Proceedings of the 2nd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2016)
PB  - Atlantis Press
SP  - 76
EP  - 82
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-16.2017.10
DO  - 10.2991/eeeis-16.2017.10
ID  - Gao2016/12
ER  -