Hottest pixel segmentation based thermal image analysis for children
In this paper, the first order statistics for gray level intensity defined from thermal image is implemented to govern the significant and distinguishable characteristic pattern in thermal image of affective states. The impact of thresholding mechanism is studied to differentiate between positiv...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2017
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/53830/ http://irep.iium.edu.my/53830/ http://irep.iium.edu.my/53830/ http://irep.iium.edu.my/53830/19/53830-edited.pdf http://irep.iium.edu.my/53830/8/53830-Hottest%20pixel%20segmentation%20based%20thermal%20image%20analysis%20for%20children_SCOPUS.pdf |
| Summary: | In this paper, the first order statistics for gray level
intensity defined from thermal image is implemented to govern
the significant and distinguishable characteristic pattern in
thermal image of affective states. The impact of thresholding
mechanism is studied to differentiate between positive affective
states (happy) and negative affective states (sad) analysis in
response to the stimuli adopted from International Affective
Pictures System (IAPS) database. The hottest pixel segmentation
technique is applied where it identifies the threshold level in a
way to classify the hottest pixel area. The region of interest is
narrowed to a forehead region with result of separation analysis
made to left and right area. Two experiments have been
conducted by using different set of stimuli and the results depicts
of asymmetry and differed in culmination pattern for these two
affective states. This conclusive result from this study suggests
that this feature can be used as one of the important feature to
give information of affective states on individuals with autism
spectrum disorder (ASD) with least of facial expressions and
perhaps would-be use in non-verbal means. |
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