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Authors: Inmaculada Mora-Jiménez 1 ; Andrés Iglesias-Rojano 1 ; Mohammed El-Yaagoubi 1 ; José Luis Rojo-Álvarez 1 and Juan Antonio Pareja-Grande 2

Affiliations: 1 Department of Signal Theory and Communications, Telematics and Computing Systems, Rey Juan Carlos University, Madrid, Spain ; 2 Department of Neurology, Hospital Universitario Fundación de Alcorcón, Madrid, Spain

Keyword(s): Iris, Color Space, Color Similarity, Cluster Headache, Histogram Matching, Cross-correlation, Kullback-Leibler Divergence, Image Analysis.

Abstract: It is well known the existence of certain headaches in humans caused by the sympathetic hypofunction, either congenital or developed at birth. These pathologies, called cluster headaches, are physically manifested by the change in texture, color and/or intensity of the iris eye on the painful side. The automatic study of these variations would make it possible to provide quantitative measures of the existence of such pathology from color images of the left and right iris of a particular individual. In this context, this work analyzes the color of the left and right irises to identify chromatic differences between the irises belonging to the same individual by analyzing three color spaces. The iris color distribution in the same eye has been studied, as well as the degree of similarity and divergence between the chromatic distributions of irises in both eyes. Cross-correlation between color feature vectors exhibited low detection capabilities, whereas a relative measure based on the K ullback-Leibler divergence provided good performance to show color differences in the irises. No color space was identified as the most appropriate for evidencing color differences in all the scrutinized cases. The results obtained are promising on a dataset with eight patients, and can be considered a proof of concept on which it is necessary to extend the analysis with a larger database. From a practical viewpoint, this characterization could help to discriminate patients who attend the neurology department suffering from headache. (More)

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Paper citation in several formats:
Mora-Jiménez, I.; Iglesias-Rojano, A.; El-Yaagoubi, M.; Rojo-Álvarez, J. and Pareja-Grande, J. (2022). Statistical Analysis of Color Differences on Iris Images for Supporting Cluster Headache Diagnosis. In Proceedings of the 19th International Conference on Signal Processing and Multimedia Applications - SIGMAP; ISBN 978-989-758-591-3; ISSN 2184-9471, SciTePress, pages 40-47. DOI: 10.5220/0011318700003289

@conference{sigmap22,
author={Inmaculada Mora{-}Jiménez. and Andrés Iglesias{-}Rojano. and Mohammed El{-}Yaagoubi. and José Luis Rojo{-}Álvarez. and Juan Antonio Pareja{-}Grande.},
title={Statistical Analysis of Color Differences on Iris Images for Supporting Cluster Headache Diagnosis},
booktitle={Proceedings of the 19th International Conference on Signal Processing and Multimedia Applications - SIGMAP},
year={2022},
pages={40-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011318700003289},
isbn={978-989-758-591-3},
issn={2184-9471},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Signal Processing and Multimedia Applications - SIGMAP
TI - Statistical Analysis of Color Differences on Iris Images for Supporting Cluster Headache Diagnosis
SN - 978-989-758-591-3
IS - 2184-9471
AU - Mora-Jiménez, I.
AU - Iglesias-Rojano, A.
AU - El-Yaagoubi, M.
AU - Rojo-Álvarez, J.
AU - Pareja-Grande, J.
PY - 2022
SP - 40
EP - 47
DO - 10.5220/0011318700003289
PB - SciTePress