Nasal cavity detection in facial thermal image for non-contact measurement of breathing

In this research, we propose a method of improving on the accuracy of detecting nasal cavity location in far infrared images for non-contact measurement of human breathing. We found that although our previous method for far infrared imaging can detect regions that include nasal cavities well, severa...

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Bibliographic Details
Published in2012 35th International Conference on Telecommunications and Signal Processing (TSP) pp. 586 - 590
Main Authors Hanawa, D., Morimoto, T., Tearda, S., Sakai, T., Shimazaki, S., Igarashi, K., Tsuchiya, R., Mochiduki, K., Furusato, M., Oguchi, K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2012
Subjects
Binarize process
Cavity resonators
Face
Facial thermal image
Finite impulse response filter
Humans
Monitoring
Nasal cavity detection
Non-contact measurement of breathing
Radio frequency
Training
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Summary:In this research, we propose a method of improving on the accuracy of detecting nasal cavity location in far infrared images for non-contact measurement of human breathing. We found that although our previous method for far infrared imaging can detect regions that include nasal cavities well, several false alarms occur. In order to reduce false alarms, we propose to apply false alarm classification into our current method. In false alarm classification, binarize process is employed to segment facial area and background strictly. Based on the result of binarize process, false alarm on background can be classified from the results of detection. 5,100 FIR images are collected to train our nasal cavity detector; we evaluate the number of false alarms and detection failures. The results show that proposed method can reduce false alarm events.
ISBN:9781467311175
1467311170
DOI:10.1109/TSP.2012.6256364