Proposal of a weighted differential similarity method for asbestos detection in hyperspectral images

Authors

DOI:

https://doi.org/10.61799/2216-0388.2328

Keywords:

Asbestos-cement, hyperspectral images, spectral differential similarity, remote sensing.

Abstract

According to the World Health Organization (WHO), more than 100 thousand people die each year from asbestos-related cancers, several of which are attributed to exposure to this material in the home. Likewise, considering the computational challenges associated with material detection in hyperspectral images and the need to improve the accuracy of spectral distance-based methods, this study aims to propose as its contribution a new method called Weighted Differential Similarity (WDS), which is based on the percentage weighting of the absolute difference between the asbestos-cement spectral signature and the spectral signature to be classified. For the development of this study, the CRISP-DM methodology was adapted into four phases: P1. Business and Data Understanding, P2. Data Preparation, P3. Modeling and Evaluation, and P4. Model Deployment. As results, the discrimination capability of the proposed method for asbestos-cement was evaluated using 1,500 spectral signatures from six materials by weighting bands 50 to 170 out of the 380 bands considered. Using an 80/20 training-testing split, WDS achieved an accuracy of 99.7%, precision of 98.0%, recall of 100%, and F1-score of 99.0%, compared with 97.7%, 87.5%, 100%, and 93.3% obtained by SDS, respectively. In conclusion, these results, together with the lower number of false positives obtained by WDS, demonstrate a better generalization capability of the proposed method when applied to previously unseen spectral signatures.

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Author Biographies

  • Gabriel Elías Chanchí-Golondrino, Universidad de Cartagena, Cartagena de Indias, Colombia

    Profesor de la Facultad de Ingeniería de la Universidad de Cartagena

  • Manuel Alejandro Ospina-Alarcón, Universidad de Cartagena, Cartagena de Indias, Colombia

    Profesor de la Facultad de Ingeniería de la Universidad de Cartagena

  • Manuel Saba, Universidad de Cartagena, Cartagena de Indias, Colombia

    Profesor de la Facultad de Ingeniería de la Universidad de Cartagena

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Published

2026-09-01

Issue

Section

Artículo Originales

How to Cite

[1]
Chanchí-Golondrino, G.E. et al. 2026. Proposal of a weighted differential similarity method for asbestos detection in hyperspectral images. Mundo FESC Journal. 16, 36 (Sep. 2026). DOI:https://doi.org/10.61799/2216-0388.2328.