Open Access
Neuro-inspired edge feature fusion using Choquet integrals
(Elsevier, 2021) Marco Detchart, Cedric; Lucca, Giancarlo; López Molina, Carlos; Miguel Turullols, Laura de; Pereira Dimuro, Graçaliz; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex shapes and descriptors. While different aspects of the process have been extensively studied, such as lens adaptation or feature detection, some other aspects, such as feature fusion, have been mostly left aside. In this work, we elaborate on the fusion of early vision primitives using generalizations of the Choquet integral, and novel aggregation operators that have been extensively studied in recent years. We propose to use generalizations of the Choquet integral to sensibly fuse elementary edge cues, in an attempt to model the behaviour of neurons in the early visual cortex. Our proposal leads to a fully-framed edge detection algorithm whose performance is put to the test in state-of-the-art edge detection datasets.
Open Access
Dealing with uncertainty: a human perception approach in image processing
(2019) Marco Detchart, Cedric; López Molina, Carlos; Fernández Fernández, Francisco Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Una de las maneras de abordar la comparación entre objetos es mediante el uso de la similitud (comparando sus atributos comunes) o la disimilitud (comparando sus diferencias). La similitud ha sido estudiada de maneras muy diversas, desde muchos puntos de vista y en una variedad de campos tales que la psicología, la neurociencia o las matemáticas. Uno de los principales temas en los que las distancias y las similitudes han sido abordadas es a través de la lógica difusa, que permite implementar una perspectiva humana en las medidas de comparación, aportando una herramienta que permite capturar la incertidumbre inherente en la percepción de la distancia. Dentro de este contexto de la comparación y la similitud, encontramos un concepto relacionado, como es la correspondencia de características. Este concepto es una de las técnicas más utilizada en la detección de patrones o la evaluación del rendimiento de un algoritmo. En esta tesis doctoral hemos estudiado la similitud en el contexto de la lógica difusa junto con una serie de propuestas en las que tiene cabida. Entre otras, podemos citar la extracción de patrones en el análisis de huellas dactilares, cuyo estudio ha llevado en esta tesis al desarrollo de nuevos conceptos como las Funciones de Equivalencia Restringidas Radiales y las Medidas de Similitud Radiales, que modelan la similitud percibida entre datos radiales, tanto escalares como vectoriales. Además, como un estudio más explícito de las distancias en la lógica difusa, hemos abordado el estudio de las distancias, las medidas de similitud y la entropía en conjuntos difusos intervalo-valorados. Para ello, hemos incluido la amplitud del intervalo en el cálculo de las medidas. Esta condición adicional nos ha permitido conectar la incertidumbre contenida en el intervalo final con la del intervalo inicial. Finalmente, de manera complementaria hemos estudiado la aplicación de nuestros resultados teóricos en tareas de procesamiento de imagen. Hemos desarrollado un detector de bordes mediante el uso de funciones monótonas direccionalmente ordenadas y técnicas de toma de decisión por consenso. Además, hemos realizado un estudio que recoge las diferentes técnicas de análisis de calidad para los métodos de extracción de bordes, resultando en una nueva taxonomía de los diferentes métodos y un análisis de su comportamiento, mostrando que ninguno de los métodos es más adecuado que otro, siendo equivalentes entre si.
Open Access
Cognitive assistant for physical exercise monitoring in hand rehabilitation
(Springer, 2023-08-21) Rincón Arango, Jaime Andrés; Marco Detchart, Cedric; Julian, Vicente; Carrascosa, Carlos; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
This paper introduces a novel, affordable companion robot that has been designed for rehabilitation purposes among the elderly population. The robot is equipped with a camera that records exercises, and an animation screen that delivers clear and easy-to-follow instructions and feedback. To evaluate the device, a machine learning algorithm was used on a dataset of therapy exercises. The results indicate that the robot effectively recognizes gestures and accurately identifies the exercises being performed. This study presents a groundbreaking and cost-effective solution for elderly rehabilitation and has the potential to revolutionize the industry with its cutting-edge technology.
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 Matemáticas
In 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.
Open Access
Some properties and construction methods for ordered directionally monotone functions
(IEEE, 2017-08-24) Sesma Sara, Mikel; Marco Detchart, Cedric; Bustince Sola, Humberto; Barrenechea Tartas, Edurne; Lafuente López, Julio; Kolesárová, Anna; Mesiar, Radko; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
In this work we propose a new generalization of the notion of monotonicity, the so-called ordered directionally monotonicity. With this new notion, the direction of increasingness or decreasingness at a given point depends on that specific point, so that it is not the same for every value on the domain of the considered function.
Open Access
Personalized cognitive support via social robots
(MDPI, 2025-01-31) Rincón Arango, Jaime Andrés; Marco Detchart, Cedric; Julian, Vicente; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
This paper explores the use of personalized cognitive support through social robots to assist the elderly in maintaining cognitive health and emotional well-being. As aging populations grow, the demand for innovative solutions to address issues like loneliness, cognitive decline, and physical limitations increases. The studied social robots utilize machine learning and advanced sensor technology to deliver real-time adaptive interactions, including cognitive exercises, daily task assistance, and emotional support. Through responsive and personalized features, the robot enhances user autonomy and improves quality of life by monitoring physical and emotional states and adapting to the needs of each user. This study also examines the challenges of implementing assistive robots in home and healthcare settings, offering insights into the evolving role of AI-powered social robots in eldercare.
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 Matematika
Restricted 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.
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 Matemáticas
Edge 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.
Open Access
A framework for radial data comparison and its application to fingerprint analysis
(Elsevier, 2016) Marco Detchart, Cedric; Cerrón González, Juan; Miguel Turullols, Laura de; López Molina, Carlos; Bustince Sola, Humberto; Galar Idoate, Mikel; Automatika eta Konputazioa; Institute of Smart Cities - ISC; Automática y Computación; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
This work tackles the comparison of radial data, and proposes comparison measures that are further applied to fingerprint analysis. First, we study the similarity of scalar and non-scalar radial data, elaborated on previous works in fuzzy set theory. This study leads to the concepts of restricted radial equivalence function and Radial Similarity Measure, which model the perceived similarity between scalar and vectorial pieces of radial data, respectively. Second, the utility of these functions is tested in the context of fingerprint analysis, and more specifically, in the singular point detection. With this aim, a novel Template-based Singular Point Detection method is proposed, which takes advantage of these functions. Finally, their suitability is tested in different fingerprint databases. Different Similarity Measures are considered to show the flexibility offered by these measures and the behaviour of the new method is compared with well-known singular point detection methods.
Open Access
Hyperspectrum comparison using similarity measures
(IEEE, 2017-08-31) López Molina, Carlos; Marco Detchart, Cedric; Bustince Sola, Humberto; Fernández Fernández, Francisco Javier; López Maestresalas, Ainara; Ayala Martini, Daniela; Automática y Computación; Automatika eta Konputazioa; Proyectos e Ingeniería Rural; Landa Ingeniaritza eta Proiektuak
Similarity 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.