GLCM correlation approach for blood vessel identification in thermal image
The maturity of detection in emotions via thermal camera is evolving recently since it is able to detect the “hot” parts of human face composition replicating the area of blood vessels. The notion of non-invasive tools for data gatherings via a thermal camera has also been vigorously highlighte...
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Online Access: | http://irep.iium.edu.my/69453/1/69453_GLCM%20correlation%20approach%20for%20blood%20vessel.pdf http://irep.iium.edu.my/69453/2/69453_GLCM%20correlation%20approach%20for%20blood%20vessel_SCOPUS.pdf http://irep.iium.edu.my/69453/3/69453_GLCM%20correlation%20approach%20for%20blood%20vessel_WOS.pdf http://irep.iium.edu.my/69453/ https://ieeexplore.ieee.org/document/8626697 |
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my.iium.irep.694532019-06-18T08:12:53Z http://irep.iium.edu.my/69453/ GLCM correlation approach for blood vessel identification in thermal image Rusli, Nazreen Md Yusof, Hazlina Sidek, Shahrul Na'im Ishak, Nor Izzati T Technology (General) The maturity of detection in emotions via thermal camera is evolving recently since it is able to detect the “hot” parts of human face composition replicating the area of blood vessels. The notion of non-invasive tools for data gatherings via a thermal camera has also been vigorously highlighted. However, to the best of our knowledge, there is no research done to detect emotion of autistic children by using thermal camera. The autistic children are less able to present emotion through facial expression. We hypothesize that, the impact of cutaneous temperature changes due to blood flows in the blood vessels could be correlated to specific emotion state for healthy as well as autistic children. In this work, healthy children were assigned as subjects prior to the development of the algorithm for thermal imaging analysis to form a reference model. Facial thermal distribution was analyzed and a technique using Correlation in Gray Level Co-occurrence Matrices (GLCM) was proposed to identify the region with the presence of blood vessels. A fine k-Nearest Neighbor (k-NN) classifier shows a promising result for the proposed method and suggests that these analyses are momentous for distinguishing between five basic emotions and it could be used as non-verbal mediums to help on autistic children. Institute of Electrical and Electronics Engineers Inc. 2019-01-24 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/69453/1/69453_GLCM%20correlation%20approach%20for%20blood%20vessel.pdf application/pdf en http://irep.iium.edu.my/69453/2/69453_GLCM%20correlation%20approach%20for%20blood%20vessel_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/69453/3/69453_GLCM%20correlation%20approach%20for%20blood%20vessel_WOS.pdf Rusli, Nazreen and Md Yusof, Hazlina and Sidek, Shahrul Na'im and Ishak, Nor Izzati (2019) GLCM correlation approach for blood vessel identification in thermal image. In: 2018 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES 2018), 3rd-6th December 2018, Kuching, Sarawak. https://ieeexplore.ieee.org/document/8626697 10.1109/IECBES.2018.8626697 |
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T Technology (General) Rusli, Nazreen Md Yusof, Hazlina Sidek, Shahrul Na'im Ishak, Nor Izzati GLCM correlation approach for blood vessel identification in thermal image |
description |
The maturity of detection in emotions via
thermal camera is evolving recently since it is able to detect the
“hot” parts of human face composition replicating the area of
blood vessels. The notion of non-invasive tools for data
gatherings via a thermal camera has also been vigorously
highlighted. However, to the best of our knowledge, there is no
research done to detect emotion of autistic children by using
thermal camera. The autistic children are less able to present
emotion through facial expression. We hypothesize that, the
impact of cutaneous temperature changes due to blood flows in
the blood vessels could be correlated to specific emotion state
for healthy as well as autistic children. In this work, healthy
children were assigned as subjects prior to the development of
the algorithm for thermal imaging analysis to form a reference
model. Facial thermal distribution was analyzed and a
technique using Correlation in Gray Level Co-occurrence
Matrices (GLCM) was proposed to identify the region with the
presence of blood vessels. A fine k-Nearest Neighbor (k-NN)
classifier shows a promising result for the proposed method
and suggests that these analyses are momentous for
distinguishing between five basic emotions and it could be used
as non-verbal mediums to help on autistic children. |
format |
Conference or Workshop Item |
author |
Rusli, Nazreen Md Yusof, Hazlina Sidek, Shahrul Na'im Ishak, Nor Izzati |
author_facet |
Rusli, Nazreen Md Yusof, Hazlina Sidek, Shahrul Na'im Ishak, Nor Izzati |
author_sort |
Rusli, Nazreen |
title |
GLCM correlation approach for blood vessel identification in thermal image |
title_short |
GLCM correlation approach for blood vessel identification in thermal image |
title_full |
GLCM correlation approach for blood vessel identification in thermal image |
title_fullStr |
GLCM correlation approach for blood vessel identification in thermal image |
title_full_unstemmed |
GLCM correlation approach for blood vessel identification in thermal image |
title_sort |
glcm correlation approach for blood vessel identification in thermal image |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2019 |
url |
http://irep.iium.edu.my/69453/1/69453_GLCM%20correlation%20approach%20for%20blood%20vessel.pdf http://irep.iium.edu.my/69453/2/69453_GLCM%20correlation%20approach%20for%20blood%20vessel_SCOPUS.pdf http://irep.iium.edu.my/69453/3/69453_GLCM%20correlation%20approach%20for%20blood%20vessel_WOS.pdf http://irep.iium.edu.my/69453/ https://ieeexplore.ieee.org/document/8626697 |
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