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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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2019
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| Subjects: | |
| 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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| Institution: | Universiti Islam Antarabangsa Malaysia |
| Language: | English English English |
| Summary: | 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. |
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