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Numerical image processing methods for rotating condenser microscope images processing
Týč, Matěj ; Martišek, Dalibor (referee) ; Druckmüller, Miloslav (advisor)
Tato práce popisuje vznik obrazu v transmisním světelném mikroskopu s proměnnou aperturou kondenzoru. Tento způsob pořizování obrazu je výhodný při pozorování tlustých vzorků, což jsou objekty, u kterých je v mikroskopickém měřítku významná výška. Klasické transmisní mikroskopy pro tento výzkum vhodné nejsou, protože výsledný obraz, který produkují, obsahuje patrné informace z velkého objemu vzorku mimo oblast, která je vyšetřovaná. Tento problém byl vyřešen po vynálezu konfokálního mikroskopu, který je ovšem daleko dražší a má i některé nevýhody navíc. Cílem je zpracovat obrazy pořízené pomocí kondenzoru s rotující aperturou tak, aby došlo k redukci podílu nežádoucí informace a obraz se tak stal "čistším". Tato metoda zpracování obrazu nemohla být použita v minulosti, protože tehdejší počítače neměly dostatečnou paměť a výkon. Na tuto metodu se dá nahlížet jako na převod množiny výstupů z mikroskopu s vylepšenou osvětlovací soustavou na odpovídající množinu výstupů konfokálního mikroskopu.
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Neural Network Based Edge Detection
Jamborová, Soňa ; Grézl, František (referee) ; Švub, Miroslav (advisor)
This work is about suggestion and implementation of the software for detection of edges in images using neurons network. It defines basic terms for this topic and focusing mainly at preperation imaging imformation for detection using nerons network. Describing and comparing different aproachings for using implemented software on synthetic and real set of images, including experiments.
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Statistical characteristics of the traffic flow microstructure
Apeltauer, Jiří ; Nagy,, Ivan (referee) ; Kumpošt,, Petr (referee) ; Holcner, Petr (advisor)
The actual traffic flow theory assumes interactions only between neighbouring vehicles within the traffic. This assumption is reasonable, but it is based on the possibilities of science and technology available decades ago, which are currently overcome. Obviously, in general, there is an interaction between vehicles at greater distances (or between multiple vehicles), but at the time, no procedure has been put forward to quantify the distance of this interaction. This work introdukce a method, which use mathematical statistics and precise measurement of time distances of individual vehicles, which allows to determine these interacting distances (between several vehicles) and its validation for narrow densities of traffic flow. It has been revealed that at high traffic flow densities there is an interaction between at least three consecutive vehicles and four and five vehicles at lower densities. Results could be applied in the development of new traffic flow models and its verification.
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Object tracking in high-speed camera images
Myška, Michal ; Druckmüller, Miloslav (referee) ; Štarha, Pavel (advisor)
This master thesis is dealing with object tracking in high-speed camera images, within what we are trying to find their trajectory and orientation. The mathematical theory associated with this problem as well as the methods used fo image processing are described here. The main outcome is an application with a user interface through which we can calculate the desired parameters of the individual objects.
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Correction of phase image background in the digital holographic microscope using convolution
Rudolfová, Zdena ; Malina, Radomír (referee) ; Uhlířová, Hana (advisor)
This bachelor thesis concentrates on a correction of background in the phase image of cells from a transmitted-light digital holographic microscope (TDHM). Optical aberrations in the optical systems of the object and reference arms cause "deformation" of the phase image. The cell is not displayed on a background with a constant value of phase, it is displayed on a background with phase values continuously changing between different places in the image. A method for removing the consequence of this imperfection from the image is described in this thesis. The principle lies in partial convolution of the phase image with a convolution kernel determined by a two-dimensional Gaussian function with the same variance in the both axes. To eliminate loss of information about the cells, the convolution is computed only from those parts of the phase image which contain no cells. The result of the convolution is considered to be an approximation of the background. This approximation is then subtracted from the phase image. The resulting phase image has a constant background, containing only noise. The necessary mathematical concepts are resumed in the introductory part of the thesis. The basic principle of the TDHM image reconstruction is also described. As a part of the thesis, a computer programme Odečet pozadí (Background subtraction) was created, which processes the phase images from the TDHM using this method.
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Presentation of selected themes of BSIS in PPT-environment
Havlín, Radomil ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
The bachelors thesis occupy by topics of the course BSIS, which can be presented by the multimedia and animation techniques in the presentation. In the introduction, these topics are given a different method of processing. In most cases, provides a modular solution by demonstration and argued spectrum signal. The chapters describe the operation with one, two signals at the time, the properties of Fourier transform with illustrative demonstration, the correlation with convolution, kvaziperiodické signals and the last chapter the spectrum of selective signals.
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Design of a New Method for Stereovision
Kopečný, Josef ; Drahanský, Martin (referee) ; Orság, Filip (advisor)
This thesis covers with the problems of photogrammetry. It describes the instruments, theoretical background and procedures of acquiring, preprocessing, segmentation of input images and of the depth map calculating. The main content of this thesis is the description of the new method of stereovision. Its algorithm, implementation and evaluation of experiments. The covered method belongs to correlation based methods. The main emphasis lies in the segmentation, which supports the depth map calculation.
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Image similarity measuring using deep learning
Štarha, Dominik ; Šeda, Pavel (referee) ; Rajnoha, Martin (advisor)
This master´s thesis deals with the reseach of technologies using deep learning method, being able to use when processing image data. Specific focus of the work is to evaluate the suitability and effectiveness of deep learning when comparing two image input data. The first – theoretical – part consists of the introduction to neural networks and deep learning. Also, it contains a description of available methods, their benefits and principles, used for processing image data. The second - practical - part of the thesis contains a proposal a appropriate model of Siamese networks to solve the problem of comparing two input image data and evaluating their similarity. The output of this work is an evaluation of several possible model configurations and highlighting the best-performing model parameters.
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