Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)

The Method for Recognizing Recognition Helmet Based On Color and Shape

Authors
Geng Zhang, Lei Lv, Dan Li, Min Zhu
Corresponding Author
Geng Zhang
Available Online April 2017.
DOI
10.2991/icmmct-17.2017.238How to use a DOI?
Keywords
Helmet, Face Location, Color feature, Shape Feature
Abstract

The helmet is widely used in industrial production, in order to prevent accidents, ensure production safety, the establishment of automatic detection of helmet and alarm system becomes more and more urgent. We use intelligent video recognition technology to realize the recognition of the helmet, by mapping the skin color detection and eyes and mouth to locate the face, then scan the upper part of the face, extract color features and shape features to determine whether the head wear a helmet. The method is based on the substation environment, without deliberately artificial, flexible with all kinds of different focal lengths of the camera to complete the verification, and have a higher pass rate.

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 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
10.2991/icmmct-17.2017.238
ISSN
2352-5401
DOI
10.2991/icmmct-17.2017.238How 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  - Geng Zhang
AU  - Lei Lv
AU  - Dan Li
AU  - Min Zhu
PY  - 2017/04
DA  - 2017/04
TI  - The Method for Recognizing Recognition Helmet Based On Color and Shape
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 1219
EP  - 1223
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.238
DO  - 10.2991/icmmct-17.2017.238
ID  - Zhang2017/04
ER  -