Person: Marco Detchart, Cedric
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Marco Detchart
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Cedric
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Automática y Computación
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0000-0002-4310-9060
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810938
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Publication Open Access From restricted equivalence functions on Ln to similarity measures between fuzzy multisets(IEEE, 2023) Ferrero Jaurrieta, Mikel; Takáč, Zdenko; Rodríguez Martínez, Iosu; Marco Detchart, Cedric; Bernardini, Ángela; Fernández Fernández, Francisco Javier; López Molina, Carlos; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaRestricted equivalence functions are well-known functions to compare two numbers in the interval between 0 and 1. Despite the numerous works studying the properties of restricted equivalence functions and their multiple applications as support for different similarity measures, an extension of these functions to an n-dimensional space is absent from the literature. In this paper, we present a novel contribution to the restricted equivalence function theory, allowing to compare multivalued elements. Specifically, we extend the notion of restricted equivalence functions from L to L n and present a new similarity construction on L n . Our proposal is tested in the context of color image anisotropic diffusion as an example of one of its many applications.Publication Open Access Similarity between interval-valued fuzzy sets taking into account the width of the intervals and admissible orders(Elsevier, 2020) Bustince Sola, Humberto; Marco Detchart, Cedric; Fernández Fernández, Francisco Javier; Wagner, Christian; Garibaldi, Jonathan M.; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y MatemáticasIn this work we study a new class of similarity measures between interval-valued fuzzy sets. The novelty of our approach lays, firstly, on the fact that we develop all the notions with respect to total orders of intervals; and secondly, on that we consider the width of intervals so that the uncertainty of the output is strongly related to the uncertainty of the input. For constructing the new interval-valued similarity, interval valued aggregation functions and interval-valued restricted equivalence functions which take into account the width of the intervals are needed, so we firstly study these functions, both in line with the two above stated features. Finally, we provide an illustrative example which makes use of an interval-valued similarity measure in stereo image matching and we show that the results obtained with the proposed interval-valued similarity measures improve numerically (according to the most widely used measures in the literature) the results obtained with interval valued similarity measures which do not consider the width of the intervals.Publication Open Access Image feature extraction using OD-monotone functions(Springer, 2018) Marco Detchart, Cedric; López Molina, Carlos; Fernández Fernández, Francisco Javier; Pagola Barrio, Miguel; Bustince Sola, Humberto; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y MatemáticasEdge detection is a basic technique used as a preliminary step for, e.g., object extraction and recognition in image processing. Many of the methods for edge detection can be fit in the breakdown structure by Bezdek, in which one of the key parts is feature extraction. This work presents a method to extract edge features from a grayscale image using the so-called ordered directionally monotone functions. For this purpose we introduce some concepts about directional monotonicity and present two construction methods for feature extraction operators. The proposed technique is competitive with the existing methods in the literature. Furthermore, if we combine the features obtained by different methods using penalty functions, the results are equal or better results than stateof-the-art methods.Publication Open Access Ordered directional monotonicity in the construction of edge detectors(Elsevier, 2021) Marco Detchart, Cedric; Bustince Sola, Humberto; Fernández Fernández, Francisco Javier; Mesiar, Radko; Lafuente López, Julio; Barrenechea Tartas, Edurne; Pintor Borobia, Jesús María; Estatistika, Informatika eta Matematika; Ingeniaritza; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas; IngenieríaIn this paper we provide a specific construction method of ordered directionally monotone functions. We show that the functions obtained with this construction method can be used to build edge detectors for grayscale images. We compare the results of these detectors to those obtained with some other ones that are widely used in the literature. Finally, we show how a consensus edge detector can be built improving the results obtained both by our proposal and by those in the literature when applied individually.