On the importance of metrics in practical applications

[EN] Students motivation for learning mathematical concepts can be increased when showing the usefulness of these concepts in practical problems. One important mathematical concept is the concept of metric space and, more related to the applications, the concept of metric function. In this work we aim to illustrate how important is to appropriately choose the metric when dealing with a practical problem. In particular, we focus on the problem of detection of noisy pixels in colour images. In this context, it is very important to appropriately measure the distances and similarities between the image pixels, which is done by means of an appropriate metric. We study the performance of different metrics, including recent fuzzy metrics, within a specific filter to show that it is indeed a critical choice to appropriately solve the task.Camarena, J.; Morillas, S.; Cisneros, F. (2011). On the importance of metrics in practical applications. Modelling in Science Education and Learning. 4:119-128. doi:10.4995/msel.2011.3066SWORD119128

Aplicació de mètriques fuzzy en la millora computacional d'algorismes de filtratge d'imatges en color

El filtrado de imágenes es una tarea fundamental para la mayoría de los sistemas de visión por computador cuando las imágenes se usan para análisis automático o, incluso, para inspección humana. De hecho, la presencia de ruido en una imagen puede ser un grave impedimento para las sucesivas tareas de procesamiento de imágenes como, por ejemplo, la detección de bordes o el reconocimiento de patrones u objetos y, por lo tanto, el ruido debe ser reducido. Del mismo modo, el aumento de la resolución y el tamaño de las imágenes nos conduce a requerimientos computacionales más altos, los cuales hemos de intentar rebajar sobre todo para aplicaciones en tiempo real o similares. En los últimos años el interés por utilizar imágenes en color se ha visto incrementado de forma significativa en una gran variedad de aplicaciones. Es por esto que el filtrado de imágenes en color se ha convertido en un área de investigación interesante. Se ha observado ampliamente que las imágenes en color deben ser procesadas teniendo en cuenta la correlación existente entre los distintos canales de color de la imagen. En este sentido, la solución probablemente más conocida y estudiada es el enfoque vectorial. Las primeras soluciones que proponen técnicas de filtrado vectorial, son las conocidas técnicas del filtro de mediana vectorial (VMF) o el filtro direccional vectorial (VDF). Desafortunadamente, estas técnicas no se adaptan a las características locales de la imagen, lo que implica que habitualmente los bordes y detalles de las imágenes se emborronan y pierden calidad. A fin de solventar este problema, se han propuesto recientemente varios filtros vectoriales adaptativos, entre los que destacan las técnicas de peer group. En los últimos años ha aparecido la teoría de los denominados conjuntos fuzzy, borrosos o difusos (lógica, métricas y topologías), que se ha demostrado es una herramienta adecuada para el filtrado de imágenes. En la presente Tesis Doctoral las metas principales son: (i) el esCamarena Estruch, JG. (2009). Aplicació de mètriques fuzzy en la millora computacional d'algorismes de filtratge d'imatges en color [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/4339Palanci

A simple fuzzy method to remove mixed Gaussian-Impulsive noise from color images

© 2013 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 works.Mixed impulsive and Gaussian noise reduction from digital color images is a challenging task because it is necessary to appropriately process both types of noise that in turn need to be distinguished from the original image structures such as edges and details. Fuzzy theory is useful to build simple, efficient, and effective solutions for this problem. In this paper, we propose a fuzzy method to reduce Gaussian and impulsive noise from color images. Our method uses one only filtering operation: a weighted averaging. A fuzzy rule system is used to assign the weights in the averaging so that both noise types are reduced and image structures are reserved. We provide experimental results to show that the performance of the method is competitive with respect to state-of-the-art filters.This work was supported by the Spanish Ministry of Science and Innovation under Grant MTM2009-12872-C02-01.Camarena Estruch, JG.; Gregori Gregori, V.; Morillas, S.; Sapena Piera, A. (2013). A simple fuzzy method to remove mixed Gaussian-Impulsive noise from color images. IEEE Transactions on Fuzzy Systems. 21(5):971-978. https://doi.org/10.1109/TFUZZ.2012.2234754S97197821

El concepto de métrica fuzzy a través del filtrado de imágenes digitales

[EN] Fuzzy logic has been recently successfully used in several Engineering applications. In particular, fuzzy metrics have been applied to color image filtering improving, in many cases, classical filters results. In this work we study the notion of fuzzy metric and present a simulation model which allows postgraduate students to understand this notion and study the fuzzy metrics properties through color image filtering.[ES] La lógica fuzzy ha sido utilizada recientemente en numerosas aplicaciones de la ingeniería con resultados exitosos. En particular, las métricas fuzzy han sido aplicadas al filtrado de imágenes en color mejorando, en muchos casos, los resultados de los filtros clásicos. En este trabajo abordamos la noción de métrica fuzzy y presentamos un modelo de simulación que permite a los alumnos de postgrado conocer esta noción y acceder a las propiedades de las métricas fuzzy a través del filtrado de imágenes en color.Valentín Gregori agradece la ayuda del Ministerio de Economía y Competitividad MTM 2012-37894-C02-01, Samuel Morillas y Almanzor Sapena agradecen la ayuda del Ministerio de Educación MTM2009-12872-C02-01.Camarena, J.; Gregori, V.; Morillas, S.; Sapena, A. (2013). El concepto de métrica fuzzy a través del filtrado de imágenes digitales. Modelling in Science Education and Learning. 6(3):5-17. doi:10.4995/msel.2013.1976SWORD5176

Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal