Implication functions in interval-valued fuzzy set theory

Interval-valued fuzzy set theory is an extension of fuzzy set theory in which the real, but unknown, membership degree is approximated by a closed interval of possible membership degrees. Since implications on the unit interval play an important role in fuzzy set theory, several authors have extended this notion to interval-valued fuzzy set theory. This chapter gives an overview of the results pertaining to implications in interval-valued fuzzy set theory. In particular, we describe several possibilities to represent such implications using implications on the unit interval, we give a characterization of the implications in interval-valued fuzzy set theory which satisfy the Smets-Magrez axioms, we discuss the solutions of a particular distributivity equation involving strict t-norms, we extend monoidal logic to the interval-valued fuzzy case and we give a soundness and completeness theorem which is similar to the one existing for monoidal logic, and finally we discuss some other constructions of implications in interval-valued fuzzy set theory

Detecao de Bordas baseada em Morfologia Matemática Fuzzy Intervalar e as Funcoes de Agregacao K

Edge detection is a digital image processing tool. It determines points in a digital image where light intensity suddenly changes. This process applies to a digital image which assumes some degree of uncertainty in the location and intensity of the pixel in the real image. In this work, we propose an edge detection model which consists in capturing this uncertainty in terms of interval images. Then we apply interval-valued fuzzy morphology to calculate the interval-valued erosion and dilation. Finally, we compute the convex combinations of the upper and lower bounds of the interval-valued erosion and dilation image, to obtain a morphological erosion and dilation respectively, and thus an edge image.A deteccao de bordas é uma ferramenta de processamento digital de imagenes. Ela determina pontos de uma imagem digital onde a intensidade da luz muda repentinamente. Esse processo aplica-se a uma imagem digital a qual supoe algum grau de incerteza na localizacao e na intensidade do pixel da imagem real. Neste trabalho, é proposto um modelo de detecao de bordas que consiste na captura dessa incerteza em termos de imagens intervalares, para depois aplicar a erosao e dilatacao intervalar fuzzy. Finalmente, por meio de uma combinacao convexa sobre os limites superiores e inferiores da erosao e a dilatacao intervalar, sao obtidas a erosao e a dilatacao morfológica respectivamente, com as quais se faz possível produzir uma imagem borda

Interval-valued and intuitionistic fuzzy mathematical morphologies as special cases of L-fuzzy mathematical morphology

Mathematical morphology (MM) offers a wide range of tools for image processing and computer vision. MM was originally conceived for the processing of binary images and later extended to gray-scale morphology. Extensions of classical binary morphology to gray-scale morphology include approaches based on fuzzy set theory that give rise to fuzzy mathematical morphology (FMM). From a mathematical point of view, FMM relies on the fact that the class of all fuzzy sets over a certain universe forms a complete lattice. Recall that complete lattices provide for the most general framework in which MM can be conducted. The concept of L-fuzzy set generalizes not only the concept of fuzzy set but also the concepts of interval-valued fuzzy set and Atanassov’s intuitionistic fuzzy set. In addition, the class of L-fuzzy sets forms a complete lattice whenever the underlying set L constitutes a complete lattice. Based on these observations, we develop a general approach towards L-fuzzy mathematical morphology in this paper. Our focus is in particular on the construction of connectives for interval-valued and intuitionistic fuzzy mathematical morphologies that arise as special, isomorphic cases of L-fuzzy MM. As an application of these ideas, we generate a combination of some well-known medical image reconstruction techniques in terms of interval-valued fuzzy image processing

Aggregation functions for typical hesitant fuzzy elements and the action of automorphisms

This work studies the aggregation operators on the set of all possible membership degrees of typical hesitant fuzzy sets, which we refer to as H, as well as the action of H-automorphisms which are defined over the set of all finite non-empty subsets of the unitary interval. In order to do so, the partial order ≤H, based on α-normalization, is introduced, leading to a comparison based on selecting the greatest membership degrees of the related fuzzy sets. Additionally, the idea of interval representation is extended to the context of typical hesitant aggregation functions named as the H-representation. As main contribution, we consider the class of finite hesitant triangular norms, studying their properties and analyzing the H-conjugate functions over such operators. © 2013 Elsevier Inc. All rights reserved.Peer Reviewe

Characterization and statistics of distance-based morphological operators using Voronoi diagram with application for edge detection in color images

Orientador: Marcos Eduardo Ribeiro do Valle MesquitaTese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação CientíficaResumo: A morfologia matemática (MM) é uma teoria que utiliza conceitos geométricos e topológicos para processamento e análise de imagens. Aplicações da MM incluem, por exemplo, detecção de bordas, segmentação e reconstrução automática de imagens, reconhecimento de padrões e decomposição de sinais e imagens. Nesta tese, estudamos os operadores morfológicos para imagens em tons de cinza e coloridas segundo a abordagem baseada em distância proposta por Angulo. Este tipo de abordagem geralmente se depara com a difícil tarefa de escolher uma referência apropriada. Nesta tese, estabelecemos uma relação direta entre a escolha da referência e o diagrama de Voronoi. Além disso, utilizamos conceitos de estatística descritiva para superar a dificuldade de escolher uma referência e, com isso, definimos novos operadores, chamados pseudo-morfológicos. Por exemplo, a média de dilatações ou a média de erosões, o desvio padrão do gradiente, entre outros. Experimentos computacionais mostraram que alguns dos novos operadores pseudo-morfológicos, por exemplo o desvio padrão do gradiente, apresentaram um bom desempenho quando aplicados em problemas de detecção de bordas em imagens coloridasAbstract: Mathematical morphology (MM) is a theory that uses geometric and topological concepts for image processing and analysis. Applications MM include boundary detection, automatic image segmentation and reconstruction, pattern recognition, and signal and image decomposition. In this thesis, we study morphological operators for grayscale and color images defined according to the distance-based approach proposed by Angulo. This type of approach usually involves the difficult task of choosing an appropriate reference. In this thesis, we establish a direct relationship between the choice of reference and the Voronoi diagram. In addition, we use descriptive statistics concepts to overcome the hard task of choosing a reference, and thus we define new pseudo-morphological operators. Such as the average of dilations and the average of erosions, the standard deviation of the gradient. Computational experiments show that some of the new pseudo-morphological operators, for example the standard deviation of the gradient are suitable for edge detection of color imagesDoutoradoMatematica AplicadaDoutor em Matemática Aplicad

REPRESENTABILITY IN INTERVAL-VALUED FUZZY SET THEORY

Interval-valued fuzzy set theory is an increasingly popular extension of fuzzy set theory where traditional [0, 1]-valued membership degrees are replaced by intervals in [0, 1] that approximate the (unknown) membership degrees. To construct suitable graded logical connectives in this extended setting, it is both natural and appropriate to “reuse” ingredients from classical fuzzy set theory. In this paper, we compare different ways of representing operations on interval-valued fuzzy sets by corresponding operations on fuzzy sets, study their intuitive semantics, and relate them to an existing, purely order-theoretical approach. Our approach reveals, amongst others, that subtle differences in the representation method can have a major impact on the properties satisfied by the generated operations, and that contrary to popular perception, interval-valued fuzzy set theory hardly corresponds to a mere twofold application of fuzzy set theory. In this way, by making the mathematical machinery behind the interval-valued fuzzy set model fully transparent, we aim to foster new avenues for its exploitation by offering application developers a much more powerful and elaborate mathematical toolbox than existed before

Fuzzy techniques for noise removal in image sequences and interval-valued fuzzy mathematical morphology

Image sequences play an important role in today's world. They provide us a lot of information. Videos are for example used for traffic observations, surveillance systems, autonomous navigation and so on. Due to bad acquisition, transmission or recording, the sequences are however usually corrupted by noise, which hampers the functioning of many image processing techniques. A preprocessing module to filter the images often becomes necessary. After an introduction to fuzzy set theory and image processing, in the first main part of the thesis, several fuzzy logic based video filters are proposed: one filter for grayscale video sequences corrupted by additive Gaussian noise and two color extensions of it and two grayscale filters and one color filter for sequences affected by the random valued impulse noise type. In the second main part of the thesis, interval-valued fuzzy mathematical morphology is studied. Mathematical morphology is a theory intended for the analysis of spatial structures that has found application in e.g. edge detection, object recognition, pattern recognition, image segmentation, image magnification… In the thesis, an overview is given of the evolution from binary mathematical morphology over the different grayscale morphology theories to interval-valued fuzzy mathematical morphology and the interval-valued image model. Additionally, the basic properties of the interval-valued fuzzy morphological operators are investigated. Next, also the decomposition of the interval-valued fuzzy morphological operators is investigated. We investigate the relationship between the cut of the result of such operator applied on an interval-valued image and structuring element and the result of the corresponding binary operator applied on the cut of the image and structuring element. These results are first of all interesting because they provide a link between interval-valued fuzzy mathematical morphology and binary mathematical morphology, but such conversion into binary operators also reduces the computation. Finally, also the reverse problem is tackled, i.e., the construction of interval-valued morphological operators from the binary ones. Using the results from a more general study in which the construction of an interval-valued fuzzy set from a nested family of crisp sets is constructed, increasing binary operators (e.g. the binary dilation) are extended to interval-valued fuzzy operators

Fuzzy Mathematics

This book provides a timely overview of topics in fuzzy mathematics. It lays the foundation for further research and applications in a broad range of areas. It contains break-through analysis on how results from the many variations and extensions of fuzzy set theory can be obtained from known results of traditional fuzzy set theory. The book contains not only theoretical results, but a wide range of applications in areas such as decision analysis, optimal allocation in possibilistics and mixed models, pattern classification, credibility measures, algorithms for modeling uncertain data, and numerical methods for solving fuzzy linear systems. The book offers an excellent reference for advanced undergraduate and graduate students in applied and theoretical fuzzy mathematics. Researchers and referees in fuzzy set theory will find the book to be of extreme value