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Marco Detchart, Cedric

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https://academica-e.unavarra.es/handle/2454/49498

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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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2015 - 20195
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Start date: 2015 × End date: 2019 ×

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Now showing 1 - 5 of 5
  • Thumbnail Image
    PublicationOpen 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.
  • Thumbnail Image
    PublicationOpen Access
    Optical images-based edge detection in Synthetic Aperture Radar images
    (Elsevier, 2015) Silva Junior, Gilberto P.; Frery, Alejandro C.; Bustince Sola, Humberto; Barrenechea Tartas, Edurne; Marco Detchart, Cedric; Automática y Computación; Automatika eta Konputazioa
    We address the issue of adapting optical images-based edge detection techniques for use in Polarimetric Synthetic Aperture Radar (PolSAR) imagery. We modify the gravitational edge detection technique (inspired by the Law of Universal Gravity) proposed by Lopez-Molina et al., using the non-standard neighbourhood configuration proposed by Fu et al., to reduce the speckle noise in polarimetric SAR imagery. We compare the modified and unmodified versions of the gravitational edge detection technique with the well-established one proposed by Canny, as well as with a recent multiscale fuzzy-based technique proposed by Lopez-Molina et al. We also address the issues of aggregation of gray level images before and after edge detection and of filtering. All techniques addressed here are applied to a mosaic built using class distributions obtained from a real scene, as well as to the true PolSAR image; the mosaic results are assessed using Baddeley’s Delta Metric. Our experiments show that modifying the gravitational edge detection technique with a non-standard neighbourhood configuration produces better results than the original technique, as well as the other techniques used for comparison. The experiments show that adapting edge detection methods from Computational Intelligence for use in PolSAR imagery is a new field worthy of exploration.
  • Thumbnail Image
    PublicationOpen 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.
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    PublicationOpen 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.
  • Thumbnail Image
    PublicationOpen Access
    Directions of directional, ordered directional and strengthened ordered directional increasingness of linear and ordered linear fusion operators
    (IEEE, 2019) Sesma Sara, Mikel; Marco Detchart, Cedric; Lafuente López, Julio; Roldán López de Hierro, Antonio Francisco; Mesiar, Radko; Bustince Sola, Humberto; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
    In this work we discuss the forms of monotonicity that have been recently introduced to relax the monotonicity condition in the definition of aggregation functions. We focus on directional, ordered directional and strengthened ordered directional monotonicity, study their main properties and provide some results about their links and relations among them. We also present two families of functions, the so-called linear fusion functions and ordered linear fusion functions and we study the set of directions for which these types of functions are directionally, ordered directionally and strengthened ordered directionally increasing. In particular, OWA operators are an example of ordered linear fusion functions.