Fuzzy models for fingerprint description

Fuzzy models, traditionally used in the control field to model controllers or plants behavior, are used in this work to describe fingerprint images. The textures, in this case the directions of the fingerprint ridges, are described for the whole image by fuzzy if-then rules whose antecedents consider a part of the image and the consequent is the associated dominant texture. This low-level fuzzy model allows extracting higher-level information about the fingerprint, such as the existence of fuzzy singular points and their fuzzy position within the image. This is exploited in two applications: to provide comprehensive information for user of unattended automatic recognition systems and to extract linguistic patterns to classify fingerprints

Noise Reduction by Fuzzy Image Filtering

A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of two stages. The first stage computes a fuzzy derivative for eight different directions. The second stage uses these fuzzy derivatives to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Both stages are based on fuzzy rules which make use of membership functions. The filter can be applied iteratively to effectively reduce heavy noise. In particular, the shape of the membership functions is adapted according to the remaining noise level after each iteration, making use of the distribution of the homogeneity in the image. A statistical model for the noise distribution can be incorporated to relate the homogeneity to the adaptation scheme of the membership functions. Experimental results are obtained to show the feasibility of the proposed approach. These results are also compared to other filters by numerical measures and visual inspection

On the construction of interval-valued fuzzy morphological operators

Classical fuzzy mathematical morphology is one of the extensions of original binary morphology to greyscale morphology. Recently, this theory was further extended to interval-valued fuzzy mathematical morphology by allowing uncertainty in the grey values of the image and the structuring element. In this paper, we investigate the construction of increasing interval-valued fuzzy operators from their binary counterparts and work this out in more detail for the morphological operators, which results in a nice theoretical link between binary and interval-valued fuzzy mathematical morphology. The investigation is done both in the general continuous and the practical discrete case. It will be seen that the characterization of the supremum in the discrete case leads to stronger relationships than in the continuous case. (C) 2011 Elsevier B.V. All rights reserved.17818410

On the Decomposition of Interval-Valued Fuzzy Morphological Operators

Interval-valued fuzzy mathematical morphology is an extension of classical fuzzy mathematical morphology, which is in turn one of the extensions of binary morphology to greyscale morphology. The uncertainty that may exist concerning the grey value of a pixel due to technical limitations or bad recording circumstances, is taken into account by mapping the pixels in the image domain onto an interval to which the pixel's grey value is expected to belong instead of one specific value. Such image representation corresponds to the representation of an interval-valued fuzzy set and thus techniques from interval-valued fuzzy set theory can be applied to extend greyscale mathematical morphology. In this paper, we study the decomposition of the interval-valued fuzzy morphological operators. We investigate in which cases the [alpha (1),alpha (2)]-cuts of these operators can be written or approximated in terms of the corresponding binary operators. Such conversion into binary operators results in a reduction of the computation time and is further also theoretically interesting since it provides us a link between interval-valued fuzzy and binary morphology.36327029

Recurrent origin of peripheral, coastal (sub)species in Mediterranean <i>Senecio</i> (Asteraceae)

<p><b><i>Background</i></b>: It is argued that coastal endemic taxa may evolve in parallel at the periphery of the distributional range of a widespread species.</p> <p><b><i>Aims</i></b>: We tested this hypothesis for the origins of three peripheral, coastal isolates of <i>Senecio, S. glaucus</i> ssp. <i>glaucus</i> (Israel), <i>S. g</i>. ssp. <i>coronopifolius</i> p.p. (Sicily), and <i>S. hesperidium</i> (Morocco), from widespread <i>S. glaucus</i> ssp. <i>coronopifolius</i>. We also determined the relative roles of selection vs. genetic drift in shaping phenotypic divergence in ssp. <i>glaucus</i> and <i>S. hesperidium</i>, using Lande’s test of neutral morphological change.</p> <p><b><i>Methods</i></b>: We surveyed morphological and/or allozyme variation in the three peripheral isolates and mainly inland populations of <i>S. g</i>. ssp. <i>coronopifolius.</i></p> <p><b><i>Results</i></b>: Genetic data supported independent origins of the coastal taxa from nearby populations of ssp. <i>coronopifolius</i>. These descendant and ancestral populations showed pronounced morphological but weak genetic differentiation. Phenotypic similarities between ssp. <i>glaucus</i> (Israel) and <i>S. hesperidium</i> (Morocco) in plant height and floral traits may have resulted from parallel divergent selection from ssp. <i>coronopifolius</i>, though drift remains an alternative cause in <i>S. hesperidium</i>.</p> <p><b><i>Conclusions</i></b>: Our results indicate parallel ecotype formation and (sub)speciation in <i>Senecio</i> in which primarily selective vs. neutral determinants promoted the recurrent origin of coastal types in, respectively, Israel and Morocco.</p

Interval-Valued and Intuitionistic Fuzzy Mathematical Morphologies as Special Cases of L-Fuzzy Mathematical Morphology

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)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.4315071Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)CNPq [309608/2009-0]FAPESP [2009/16284-2