Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)

Mattress Overlapping Recognition Based on Markov Random Field

Authors
Fengyu Hu, Xianqiao Chen
Corresponding Author
Fengyu Hu
Available Online April 2017.
DOI
10.2991/eame-17.2017.27How to use a DOI?
Keywords
mattress sonar image; image segmentation; MRF model; belief propagation
Abstract

Mattress overlapping recognition is of great significance in tracing and detecting the quality, and provides reference data of mattress laying. The recognition process includes the generation and image correction of the color sinking sonar image, the image segmentation and the recognition of mattress overlapping; In which the key issue is the segmentation of sonar image segmentation. There are a lot of underwater sonar image noise, and the effect of the traditional segmentation method is poor; Markov Model can accurately show the characteristics and relationship of image content. For segmentation algorithm of mattress image, using belief propagation (BP) algorithm .Experimental results show that it has a good effect.

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 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/eame-17.2017.27
ISSN
2352-5401
DOI
10.2991/eame-17.2017.27How 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  - Fengyu Hu
AU  - Xianqiao Chen
PY  - 2017/04
DA  - 2017/04
TI  - Mattress Overlapping Recognition Based on Markov Random Field
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017)
PB  - Atlantis Press
SP  - 113
EP  - 116
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-17.2017.27
DO  - 10.2991/eame-17.2017.27
ID  - Hu2017/04
ER  -