A Supervised Quantification of the Color Names Characterizing the Visual Component Color in the ABCD Dermatological Criteria for a Further Melanoma Inspection

Jinen Daghrir, Jinen Daghrir, Lotfi Tlig, Moez Bouchouicha, Noureddine Litaiem, Faten Zeglaoui, Mounir Sayadi

2022

Abstract

Digital imaging is widely used for creating automated systems for medical purposes such as the diagnosis of certain kinds of diseases. One typical use of these computer vision diagnosis systems in dermatology is the inspection of melanoma skin cancer, which is one of the most fatal skin cancer. For the early detection of melanoma, a lot of systems have been proposed. Most of them use some visual features through image processing methods, such as color processing and border and texture inspection. Color variation is a good clue to differentiate melanoma and benign lesions. Thus, it is important to process skin lesion images to extract the various colors. The paper presents a new method that extracts the different color names from a skin lesion in a supervised way based on observed skin condition types. These features can ensure accurate melanoma detection with other types of features. To demonstrate the effectiveness of our suggested representation, we construct a prediction system for inspecting the malignancy of skin lesions. The experimental results show a consistent improvement in the prediction performance against other color representations.

Paper Citation

in Harvard Style

Daghrir J., Tlig L., Bouchouicha M., Litaiem N., Zeglaoui F. and Sayadi M. (2022). A Supervised Quantification of the Color Names Characterizing the Visual Component Color in the ABCD Dermatological Criteria for a Further Melanoma Inspection. In Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE, ISBN 978-989-758-566-1, pages 147-154. DOI: 10.5220/0010865300003188

in Bibtex Style

@conference{ict4awe22,
author={Jinen Daghrir and Lotfi Tlig and Moez Bouchouicha and Noureddine Litaiem and Faten Zeglaoui and Mounir Sayadi},
title={A Supervised Quantification of the Color Names Characterizing the Visual Component Color in the ABCD Dermatological Criteria for a Further Melanoma Inspection},
booktitle={Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,},
year={2022},
pages={147-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010865300003188},
isbn={978-989-758-566-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health - Volume 1: ICT4AWE,
TI - A Supervised Quantification of the Color Names Characterizing the Visual Component Color in the ABCD Dermatological Criteria for a Further Melanoma Inspection
SN - 978-989-758-566-1
AU - Daghrir J.
AU - Tlig L.
AU - Bouchouicha M.
AU - Litaiem N.
AU - Zeglaoui F.
AU - Sayadi M.
PY - 2022
SP - 147
EP - 154
DO - 10.5220/0010865300003188