Bustince, HumbertoBarrenechea, EdurneFernández Castillo, JesúsPagola, MiguelMontero De Juan, Francisco JavierGuerra, C.2023-06-202023-06-202010Bustince, H., Barrenechea, E., Fernandez, J., Pagola, M., Montero, J., Guerra, C.: Contrast of a fuzzy relation. Information Sciences. 180, 1326-1344 (2010). https://doi.org/10.1016/j.ins.2009.12.0130020-025510.1016/j.ins.2009.12.013https://hdl.handle.net/20.500.14352/42258In this paper we address a key problem in many fields: how a structured data set can be analyzed in order to take into account the neighborhood of each individual datum. We propose representing the dataset as a fuzzy relation, associating a membership degree with each element of the relation. We then introduce the concept of interval-contrast, a means of aggregating information contained in the immediate neighborhood of each element of the fuzzy relation. The interval-contrast measures the range of membership degrees present in each neighborhood. We use interval-contrasts to define the necessary properties of a contrast measure, construct several different local contrast and total contrast measures that satisfy these properties, and compare our expressions to other definitions of contrast appearing in the literature. Our theoretical results can be applied to several different fields. In an Appendix A, we apply our contrast expressions to photographic images.engjournal articlehttps//doi.org/10.1016/j.ins.2009.12.013http://www.sciencedirect.com/science/article/pii/S002002550900543Xrestricted access004.8Fuzzy relationInterval-contrastLocal contrastTotal contrastInteligencia artificial (Informática)1203.04 Inteligencia Artificial