2016 |
Rusli, N; Yusof, H M; Sidek, S N; Latif, M H Hottest pixel segmentation based thermal image analysis for children Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781467377911, (cited By 0). Abstract | Links | BibTeX | Tags: Affective State, Autism Spectrum Disorders, Biomedical Engineering, Diseases, Feature Extraction, First-Order Statistics, Forehead Region, Gray Level Intensity, Image Analysis, Image Segmentation, Pixels, Segmentation Techniques, Thermal Image Analysis, Thermal Images @conference{Rusli2016274, title = {Hottest pixel segmentation based thermal image analysis for children}, author = {N Rusli and H M Yusof and S N Sidek and M H Latif}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015712176&doi=10.1109%2fIECBES.2016.7843457&partnerID=40&md5=847e69c597caab24e0cd0f4e2cf558c6}, doi = {10.1109/IECBES.2016.7843457}, isbn = {9781467377911}, year = {2016}, date = {2016-01-01}, journal = {IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences}, pages = {274-279}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, abstract = {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. © 2016 IEEE.}, note = {cited By 0}, keywords = {Affective State, Autism Spectrum Disorders, Biomedical Engineering, Diseases, Feature Extraction, First-Order Statistics, Forehead Region, Gray Level Intensity, Image Analysis, Image Segmentation, Pixels, Segmentation Techniques, Thermal Image Analysis, Thermal Images}, pubstate = {published}, tppubtype = {conference} } 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. © 2016 IEEE. |
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2016 |
Hottest pixel segmentation based thermal image analysis for children Conference Institute of Electrical and Electronics Engineers Inc., 2016, ISBN: 9781467377911, (cited By 0). |