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Replacement of QR Codes by Colored Matrices
Moc, Filip ; Szentandrási, István (referee) ; Herout, Adam (advisor)
This bachelor's thesis is about developing new color code for saving digital data in an image. In this report you can find informations about existing related technologies including some existing codes. You can also find here design of the new code and it's gradual improvements. There is also description of generation and recognition of this code. Finally there are results of experiments which demonstrates the success of all the work.
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Methods for biomedical image signal segmentation
Krumpholc, Lukáš ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work deals with methods of segmentation of biomedical image signals. It describes, sums up and compares representative methods of digital image processing. Segmentation based on parametric representation is one of the mentioned methods. So as the basic parameter can be chosen for example luminance and the final binary image is obtained by thresholding. Next described method is segmentation based on edge representation. This method can be divided into edge detection by the help of edge detectors and of Hough transformation. Edge detectors work with the first and second derivation. The following method is region-based segmentation, which can be used for a image with noise. This category can be divided into three parts. The first one is segmentation via splitting and merging regions, when the image is split and the created regions are tested on a defined condition. If the condition is satisfied, the region merges and doesn’t continue splitting. The second one is region growing segmentation, when adjacent pixels with a similar intensity of luminance are grouped together and create a segmentated region. Third one is watershed segmentation algorithm based on the idea of water diffusion on uneven surface. The last group of methods is segmentation via flexible and active contours. Here is described an active shape model proceeding from a possibility to deform models so that they match with sample shapes. Next I also describe method Snakes, where occurs gradual contour shaping up to the edge of the object in the image. For the final editing is used mathematical morphology of segmentated images. I aimed to meet methods of image signals segmentation, to cover the chosen methods as a script in programming language Matlab and to check their properties on images.
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Multi-Label Classification of Text Documents
Průša, Petr ; Očenášek, Pavel (referee) ; Bartík, Vladimír (advisor)
The master's thesis deals with automatic classifi cation of text document. It explains basic terms and problems of text mining. The thesis explains term clustering and shows some basic clustering algoritms. The thesis also shows some methods of classi fication and deals with matrix regression closely. Application using matrix regression for classifi cation was designed and developed. Experiments were focused on normalization and thresholding.
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Neural Network Based Edge Detection
Janda, Miloš ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
Aim of this thesis is description of neural network based edge detection methods that are substitute for classic methods of detection using edge operators. First chapters generally discussed the issues of image processing, edge detection and neural networks. The objective of the main part is to show process of generating synthetic images, extracting training datasets and discussing variants of suitable topologies of neural networks for purpose of edge detection. The last part of the thesis is dedicated to evaluating and measuring accuracy values of neural network.
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Filtering methods for NMR measurements
Nezhyba, Jiří ; Mikulka, Jan (referee) ; Gescheidtová, Eva (advisor)
This master’s thesis deals with the wavelet transform and its use in processing and removing noise from images acquired by nuclear magnetic resonance. It defines fundamental terms for this work as mother wavelet or thresholding. Above all, it describes the principle of wavelet transform, thresholding techniques and criteria for evaluating the effectiveness of filtration. It describes the relation between wavelet transforms and digital filter banks. The experimental section describes the designed filtering method for removing noise from an image captured by the technique of nuclear magnetic resonance. We applied to different kinds of mother wavelets. Evaluation of the effectiveness of filtering was performed using the signal to noise ratio, relative contrast and the steepness of the intensity changes in signal intensity. It also discusses the comparison of properties of the image and selecting the mother wavelets based on image characteristics. Images were compared in terms of a histogram, cumulative histogram, k-space and the difference image.
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Image fusion in thermal spectrum
Petrásek, Daniel ; Dvořák, Pavel (referee) ; Mekyska, Jiří (advisor)
In this paper, there is mentioned necessary theory of image processing and fusion, which belongs to a group of the most used ways of image processing in the present. In the first part there is mentioned basic findings of image and electromagnetic spectrum. In the second part there is discussed some facts of infrared radiation, thermal cameras, then it is continued with elementary methods of image focus evaluation, segmentation and noise thresholding. In next part there is introduced scheme of image fusion system and basic idea of its implementation. In the end of this thesis there is described implemented system of image fusion, detailed description of reached results, thesis rating and few ideas of improving whole system.
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Line tracking for delivery robot
Juhas, Miroslav ; Horák, Karel (referee) ; Janáková, Ilona (advisor)
This thesis describes basics of methods and algorithms used in computer vision and application of them at a simple practical problem – line-tracking for delivery robot. The first part of this thesis contains basic theoretical knowledge of computer vision, which is important for understanding the problem. It is an introduction to problems of computer vision. The second part of thesis describes solving of particular steps, which are image preprocessing, segmentation, trajectory detection and algorithms for direction control. It contains outcomes of particular steps and selection of methods acceptable for solving the problem. There are presented experiences with tests of algorithms on the UTAR platform in context of this work. The last part of thesis is evaluating results taken during work.
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Contour Shape Classification for Detection of Mis-Segmented bones in CT Data
Janovič, Tomáš ; Jan, Jiří (referee) ; Walek, Petr (advisor)
The thesis discusses the possibilities of using contour shape classification for detection of mis-segmented bones in computed tomography (CT) data. In the first part there are presented published methods and algorithms which deal with the segmentation of bone structures in CT data. Then segmentation of cortical bones is implemented by a simple thresholding with global threshold. The threshold is determined by the optimized fitting of a selected type probability distribution to the histogram. Subsequently, the thesis describes some important shape descriptors that can quantitatively describe the shapes of objects in the image. Further, the contour extraction is implemented and a suitable shape descriptor, cumulative angular function, is applied. Finally, the points which can potentially indicate mis-segmented bones are detected by using continuous wavelet transform. The proposed technique is tested on the real CT data.
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Implementation of wavelet transform in C++
Valouch, Lukáš ; Hasmanda, Martin (referee) ; Beneš, Radek (advisor)
The aim of this thesis is implementation of wavelet transform algorithm for noise reduction. The noise reduction itself is focused on improving informative capabilities of sonographic (ultrasound) images in medicine. For this purpose, thresholding of detailed coefficients on individual levels of multiresolution analysis was used. Common procedures were not used for searching for the most suitable thresholds of those levels. The alternative concept's design is based on fundamental empirical approach, where the individual thresholds are optimised by evolution algorithms. However, with this algorithmic procedure, more problems manifest regarding the objective evaluation of the success of noise reduction. Because of this, the program uses commonly used parameters such as mean square error of the whole image, linear slope edge approximation, relative contrast of two differently bright and distinct points and the standard deviation of compact surface. Described theoretical knowledge is used in developed application DTWT. It executes multilevel decomposition and reversed reconstruction by discrete time wavelet transform, thresholding of detailed coefficients and final evaluation of performed noise reduction. The developed tool can be used separately to reduce noise. For our purposes, it has been modified in way, that it executed through the component for evolutionary optimization of parameters (Optimize Parameters) in created scenario in RapidMiner program. In the optimization process, this component used evaluation received from DTWT program as fitness function. Optimal thresholds were sought separately for three wavelet families - Daubeschies, Symmlets and Coiflets. The evolution algorithm chose soft threshold for all three wavelet families. In comparison to hard threshold, it is more suitable for noise reduction, but it has tendencies to blur the edges more. The devised method had in most cases greater evaluated success of noise reduction with wavelet transform with threshold search done by evolution algorithms, than commonly used filters. In visual comparison however the wavelet transform introduced some minor depreciating artefacts into the image. It is always about compromise between noise reduction and maximal preservation of image information. Objectively evaluating this dilemma is not easy and is always dependant on subjective viewpoint which in case of sonographic images is that of the attending physician.
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Text separation
Burlak, Vladimír ; Macho, Tomáš (referee) ; Richter, Miloslav (advisor)
This bachelor’s thesis describes basic methods of picture segmentation for the purpose of separation of text from a background. In first part are described general methods meant for picture processing. There is described verging, edge detection and interference reduction. In second part are defined categories of text in picture. Third part is focused on program which will help with picture segmentation.
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