Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)

Research on Infrared Image Segmentation Method for Electrical Equipment

Authors
Yanhua Lei, Yan Bao, Chen Li, Hongtao Yu
Corresponding Author
Yanhua Lei
Available Online February 2017.
DOI
https://doi.org/10.2991/emcm-16.2017.264How to use a DOI?
Keywords
Infrared image segmentation; Electric equipment; GAC model; Image Preprocessing; Wavelet Transform
Abstract
Infrared Thermography(IRT) plays a very important role in monitoring and inspecting thermal defects of electrical equipment without shutting down. This paper analyzes two methods on the infrared image gray pretreatment. According to the noise types and characteristics of the infrared image, this paper uses the denoising method that based on wavelet transform and mean filter, it effectively suppresses the image noise signal. Compared with the traditional segment method, the improved GAC model has no problem of image edge fracture while segmenting images. And the experiment indicates that the improved GAC model solves the problem that the GAC model always remains in the local minimum while segmenting images which lead to unsatisfactory or unsuccessful segmentation.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
Part of series
Advances in Computer Science Research
Publication Date
February 2017
ISBN
978-94-6252-297-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/emcm-16.2017.264How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yanhua Lei
AU  - Yan Bao
AU  - Chen Li
AU  - Hongtao Yu
PY  - 2017/02
DA  - 2017/02
TI  - Research on Infrared Image Segmentation Method for Electrical Equipment
BT  - 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.264
DO  - https://doi.org/10.2991/emcm-16.2017.264
ID  - Lei2017/02
ER  -