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Similarity Measure of Points of Interest in Image
Křehlík, Jan ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This document deals with experimental verifying to use machine learning algorithms AdaBoost or WaldBoost to make classifier, that is able to find point in the second picture that matches original point in the first picture. This work also depicts finding points of interest in image as a first step of finding correspondence. Next there are described some descriptors of points of interest. Corresponding points could be useful for 3D modeling of shooted scene.
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Hardware Acceleration of Image Filtering
Fiala, Martin ; Martínek, Tomáš (referee) ; Kořenek, Jan (advisor)
This master's thesis contains introduction to image filtration problems, especially to theoretical outlets, whose origin lies in linear systems theory and mathematical function analysis. There are described some approaches and methods which are used to image smoothing and for edge detection in an image. Mainly Sobel operator, Laplace operator and median filter are covered. The main contents of this project is discussion of some approaches of hardware acceleration of image filtering and design of time effective software and hardware implementations of filters in a form of program functions and combinational circuits using theoretical knowledges about time complexity of algorithms. Hardware and software implementation of named filters was done too. For every filter, time of filtration was measured and results were compared and analyzed.
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Techniques Used for Image Blurring and Sharpening
Lichý, Stanislav ; Juránek, Roman (referee) ; Venera, Jiří (advisor)
This bachelor's thesis deals with methods of digital image filtering. First of all, it contains basic notions necessary to understand problems, such as digital image, pixel, color spaces, noise and noise types. Secondly, important algorithms of image sharpening and noise reduction are described. Then, algorithms working principles are explained. Achieved results are analyzed together with a discussion about algorithms suitability and their time complexity. Lastly, selected algorithms are implemented by C++ programming language, using an open source library OpenCV.
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Hardware Acceleration of Image Filtering
Fiala, Martin ; Martínek, Tomáš (referee) ; Kořenek, Jan (advisor)
This master's thesis contains introduction to image filtration problems, especially to theoretical outlets, whose origin lies in linear systems theory and mathematical function analysis. There are described some approaches and methods which are used to image smoothing and for edge detection in an image. Mainly Sobel operator, Laplace operator and median filter are covered. The main contents of this project is discussion of some approaches of hardware acceleration of image filtering and design of time effective software and hardware implementations of filters in a form of program functions and combinational circuits using theoretical knowledges about time complexity of algorithms. Hardware and software implementation of named filters was done too. For every filter, time of filtration was measured and results were compared and analyzed.
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Symmetry and Separation in the case of Laplace operator in low dimensions
Hudeček, Štěpán ; Krýsl, Svatopluk (advisor) ; Salač, Tomáš (referee)
In this thesis we analyze symmetry operators for partial differential opera- tors, in particular for Laplace and Helmholtz operators in dimension two and three. In both cases an important object is the Lie algebra of the Euclidean group. Separated solutions for partial differential operators are defined and il- lustrated for both of the mentioned operators. Examples of coordinate systems are listed, in which the solution separates. 1
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Nerovnosti Friedrichsova a Poincarého typu a jejich výpočet
MOSKOVKA, Alexej
This thesis deals with the theory of Friedrichs' and Poincaré inequalities and their constants. They are important in mathematical analysis, functional analysis and theory of partial differential equations. The key property of them is the boundness of L-norms of functions by L-norms of gradients of functions. Constants can be derived analytically for simple geometries or approximated numerically. We provide an explicit derivation for an interval, a rectangle and a rectangular cuboid. We also perform a numerical computation for the interval and the rectangle as well as for an annulus, for which constants are unknown.
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Geometric Versus Spectral Convergence for the Neumann Laplacian under Exterior Perturbations of the Domain
Arrieta, J. M. ; Krejčiřík, David
This chapter is concerned with the behavior of the eigenvalues and eigenfunctions of the Laplace operator in bounded domains when the domain undergoes a perturbation. It is well known that if the boundary condition that we are imposing is of Dirichlet type, the kind of perturbations that we may allow in order to obtain the continuity of the spectra is much broader than in the case of a Neumann boundary condition. This is explicitly stated in the pioneer work of Courant and Hilbert [CoHi53], and it has been subsequently clarified in many works, see [BaVy65, Ar97, Da03] and the references therein among others. See also [HeA06] for a general text on different properties of eigenvalues and [HeD05] for a study on the behavior of eigenvalues and in general partial differential equations when the domain is perturbed.
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Techniques Used for Image Blurring and Sharpening
Lichý, Stanislav ; Juránek, Roman (referee) ; Venera, Jiří (advisor)
This bachelor's thesis deals with methods of digital image filtering. First of all, it contains basic notions necessary to understand problems, such as digital image, pixel, color spaces, noise and noise types. Secondly, important algorithms of image sharpening and noise reduction are described. Then, algorithms working principles are explained. Achieved results are analyzed together with a discussion about algorithms suitability and their time complexity. Lastly, selected algorithms are implemented by C++ programming language, using an open source library OpenCV.
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Similarity Measure of Points of Interest in Image
Křehlík, Jan ; Beran, Vítězslav (referee) ; Herout, Adam (advisor)
This document deals with experimental verifying to use machine learning algorithms AdaBoost or WaldBoost to make classifier, that is able to find point in the second picture that matches original point in the first picture. This work also depicts finding points of interest in image as a first step of finding correspondence. Next there are described some descriptors of points of interest. Corresponding points could be useful for 3D modeling of shooted scene.
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