López Molina, CarlosMarco Detchart, CedricBustince Sola, HumbertoFernández Fernández, Francisco JavierLópez Maestresalas, AinaraAyala Martini, Daniela2025-04-092025-04-092017-08-31López-Molina, C., Marco-Detchart, C., Bustince, H., Fernández, J., López-Maestresalas, A., Ayala-Martini, D. (2017) Hyperspectrum comparison using similarity measures. In Hayashi, I., Díaz I., 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS) (pp. 1-6). IEEE. https://doi.org/10.1109/IFSA-SCIS.2017.8023259978-1-5090-4917-210.1109/IFSA-SCIS.2017.8023259https://academica-e.unavarra.es/handle/2454/53919Similarity measures, as studied in the context of fuzzy set theory, have been proven applicable to many different fields. Surely, their primary role is to model the perceived (dis-) similarity between two fuzzy sets or, equivalently, the linguistic terms they represent. However, the richness of the dedicated study makes the similarity measures portable to other contexts in which quantitative comparison plays a key role. In this work we present the application of similarity measures to hyperspectrum comparison in the context of in-lab hyperspectral imaging for bioengineering.application/pdfeng© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work.Hyperspectral imagingFuzzy setsFuzzy set theoryPsychologyWavelength measurementPragmaticsinfo:eu-repo/semantics/conferenceObject2025-04-09info:eu-repo/semantics/openAccess