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

Recognition of Electrical & Electronics Components

Recognition or more specifically Pattern or Object recognition is a typical characteristic of human beings and other living organisms. The term pattern or object means something that is set as an idea to be imitated. For example, in our childhood a shape ‘A’ is shown to us and we are asked to imitate that. So the shape is the ideal one. On the other hand, if what we produce or draw obeying that instruction is close to that shape, our teacher identifies that as ’A’. this identification is called recognition and the shapes we draw (that is object we made) may be termed as patterns. Thus, the pattern recognition means identification of the real object. Recognition should, therefore, be preceded by the development of the concept of the ideal or model or prototype. This process is called Learning. In most real life problems no ideal example is available. In that case, the concept of ideal is abstracted from many near perfect examples. Under this notion learning is of two types : supervised learning if appropriate label is attached to each of these examples ; and unsupervised learning if no labeling is available

Image enhancement techniques applied to solar feature detection

This dissertation presents the development of automatic image enhancement techniques for solar feature detection. The new method allows for detection and tracking of the evolution of filaments in solar images. Series of H-alpha full-disk images are taken in regular time intervals to observe the changes of the solar disk features. In each picture, the solar chromosphere filaments are identified for further evolution examination. The initial preprocessing step involves local thresholding to convert grayscale images into black-and-white pictures with chromosphere granularity enhanced. An alternative preprocessing method, based on image normalization and global thresholding is presented. The next step employs morphological closing operations with multi-directional linear structuring elements to extract elongated shapes in the image. After logical union of directional filtering results, the remaining noise is removed from the final outcome using morphological dilation and erosion with a circular structuring element. Experimental results show that the developed techniques can achieve excellent results in detecting large filaments and good detection rates for small filaments. The final chapter discusses proposed directions of the future research and applications to other areas of solar image processing, in particular to detection of solar flares, plages and sunspots

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

Digitization of sunspot drawings by Sp\"orer made in 1861-1894

Most of our knowledge about the Sun's activity cycle arises from sunspot observations over the last centuries since telescopes have been used for astronomy. The German astronomer Gustav Sp\"orer observed almost daily the Sun from 1861 until the beginning of 1894 and assembled a 33-year collection of sunspot data covering a total of 445 solar rotation periods. These sunspot drawings were carefully placed on an equidistant grid of heliographic longitude and latitude for each rotation period, which were then copied to copper plates for a lithographic reproduction of the drawings in astronomical journals. In this article, we describe in detail the process of capturing these data as digital images, correcting for various effects of the aging print materials, and preparing the data for contemporary scientific analysis based on advanced image processing techniques. With the processed data we create a butterfly diagram aggregating sunspot areas, and we present methods to measure the size of sunspots (umbra and penumbra) and to determine tilt angles of active regions. A probability density function of the sunspot area is computed, which conforms to contemporary data after rescaling.Comment: 10 pages, 8 figures, accepted for publication in Astronomische Nachrichten/Astronomical Note

Study of Target Enhancement Algorithms to Counter the Hostile Nuclear Environment

A necessary requirement of strategic defense is the detection of incoming nuclear warheads in an environment that may include nuclear detonations of undetected or missed target warheads. A computer model is described which simulates incoming warheads as distant endoatmospheric targets. A model of the expected electromagnetic noise present in a nuclear environment is developed using estimates of the probability distributions. Predicted atmospheric effects are also included. Various image enhancement algorithms, both linear and nonlinear, are discussed concerning their anticipated ability to suppress the noise and atmospheric effects of the nuclear environment. These algorithms are then tested, using the combined target and noise models, and evaluated in terms of the stated figures of merit

Horizontal flow fields observed in Hinode G-band images II. Flow fields in the final stages of sunspot decay

We present a subset of multi-wavelengths observations obtained with the Japanese Hinode mission, the Solar Dynamics Observatory (SDO), and the Vacuum Tower Telescope (VTT) at Observatorio del Teide, Tenerife, Spain during the time period from 2010 November 18-23. Horizontal proper motions were derived from G-band and Ca II H images, whereas line-of-sight velocities were extracted from VTT Echelle H-alpha 656.28 nm spectra and Fe I 630.25 nm spectral data of the Hinode/Spectro-Polarimeter, which also provided three-dimensional magnetic field information. The Helioseismic and Magnetic Imager on board SDO provided continuum images and line-of-sight magnetograms as context for the high-resolution observations for the entire disk passage of the active region. We have performed a quantitative study of photospheric and chromospheric flow fields in and around decaying sunspots. In one of the trailing sunspots of active region NOAA 11126, we observed moat flow and moving magnetic features (MMFs), even after its penumbra had decayed. We also noticed a superpenumbral structure around this pore. MMFs follow well-defined, radial paths from the spot all the way to the border of a supergranular cell surrounding the spot. In contrast, flux emergence near the other sunspot prevented it from establishing such well ordered flow patterns, which could even be observed around a tiny pore of just 2 Mm diameter. After the disappearance of the sunspots/pores a coherent patch of abnormal granulation remained at their location, which was characterized by more uniform horizontal proper motions, low divergence values, and diminished photospheric Doppler velocities. This region, thus, differs significantly from granulation and other areas covered by G-band bright points. We conclude that this peculiar flow pattern is a signature of sunspot decay and the dispersal of magnetic flux.Comment: 13 pages, 11 figures, accepted for publication in Astronomy and Astrophysic