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Tracing the Region of Interest in Thermal Human Face for Respiration Monitoring

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 119 - Number 4
Year of Publication: 2015
Authors:
Farah Al-khalidi
Reza Saatchi
Heather Elphick
Derek Burke
10.5120/21059-3716

Farah Al-khalidi, Reza Saatchi, Heather Elphick and Derek Burke. Article: Tracing the Region of Interest in Thermal Human Face for Respiration Monitoring. International Journal of Computer Applications 119(4):42-46, June 2015. Full text available. BibTeX

@article{key:article,
	author = {Farah Al-khalidi and Reza Saatchi and Heather Elphick and Derek Burke},
	title = {Article: Tracing the Region of Interest in Thermal Human Face for Respiration Monitoring},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {119},
	number = {4},
	pages = {42-46},
	month = {June},
	note = {Full text available}
}

Abstract

Monitoring respiration rate, i. e. the rate air is inhaled and exhaled is an important indicator of an individual's health. Respiration rate is generally measured using sensors attached to the patient's body. These contact based methods have a number of limitations, for example the attached sensor can cause discomfort to the patients. A novel, automated, non-contact based method of respiration monitoring, based on thermal imaging of the skin surface centered on the tip of the nose for the nose breathing as well as the mouth region for the mouth breathing. These methods are developed as well as the Image processing techniques were used to enhance the thermal images, remove unwanted noise and segmented the ROI. In this study the shape and size of the region of interest (ROI) are investigated. The ROI represents the facial affected area most affected by exhaled air temperature changes. This area is the tip of the nose and the upper lip for the nose breathing and the mouth area for the mouth breathing. Segmenting the ROI was considered an important task in monitoring respiration by thermal imaging. Further work is in progress to enhance the algorithm so that it can cope with very large head movements.

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