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Integration of image data into a multilayer elevation map of the environment in real-time
Dobrovolný, Lukáš ; Dobossy, Barnabás (referee) ; Adámek, Roman (advisor)
This diploma thesis focuses on the optical calibration of RGB cameras, thermal cameras, as well as the mutual calibration of RGB cameras with LiDAR. For a thermal camera calibration, a special pattern that can be detected in the IR spectrum of the camera is required. In this thesis, we describe a tool we developed for calibrating this sensor. To verify the RGB camera calibration methods and its mutual calibration with LiDAR, we employ a robotic simulator as well as Matlab which provides the necessary tools. With the knowledge of the relative position of the camera and LiDAR, we are able to merge the data together. This method is then tested both in a simulator and with actual sensors. In the final part of the thesis, the image data is integrated into an elevation map.
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Automatic reading of numbers - real-time measurement of quantities from graphical displays of various instruments with a camera
Bartoš, Daniel ; Králík, Jan (referee) ; Appel, Martin (advisor)
This bachelor thesis deals with the process of converting numerical values displayed on graphical displays of measuring instruments without communication interfaces into data usable for subsequent analysis, using a camera and a program described in the implemen- tation section. The theoretical part is dedicated to the research and implementation of operations used in image processing, including morphological operations, in the MATLAB environment. The practical part of the thesis focuses on creating a program for real-time recording of numerical displays using a camera, processing the captured images with operations discussed in the research section, and reading them using the MATLAB OCR function. It also covers the subsequent processing of the read data and their storage during the measurement. This part also includes examples of measuring different types of displays, creating a user interface and application using the Application Compiler tool. The thesis concludes with a section serving as a user guide for the application.
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High dynamic range rendering of virtual 3D scenes
Goncearenco, Vadim ; Chlubna, Tomáš (referee) ; Pečiva, Jan (advisor)
Tato bakalářská práce je zaměřena na téma Vysokého Dynamického Rozsahu (HDR), konkrétně různých HDR technik, které jsou široce používány v oblasti počítačové grafiky. Navíc se zabývá Vulkan API a jeho aplikací pro HDR vykreslováni virtuálních 3D scén. Praktická část této práce je aplikace pro renderování 3D scén, jejímž účelem je demonstrovat praktickou implementaci popsaných HDR technik, jako jsou globální operátory mapování tónu (fotografické, filmové a založené na ACES), lokální operátor mapování tónu založený na bilaterálním filtru, dynamická adaptace oka, exposure fusion a pokročilý bloom efekt.
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Application of Python programming language in image analysis and modeling of physical processes of graphene
Stehlíček, Kamil ; Képeš, Erik (referee) ; Bartošík, Miroslav (advisor)
In this thesis, we focus on evaluating experimental data using the Python programming language across three different physics problems dealing with graphene. The goals of the thesis are based on practical experiments that use gallium or gallium nitride to alter the electro-optical properties of graphene or experiments that require the simulation of charge propagation in graphene nanoelectronics. These tasks successively use image analysis and numerical simulations. The theoretical part of the thesis serves as a research and as an introduction to basic image processing algorithms and numerical simulation techniques. The practical part of the thesis then focuses on the evaluation of the success of each program, its implementation in practical evaluation and explanation of experimental results.
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Detection of Diseases Caused by Diabetes in Retinal Images
Zapletal, Michal ; Semerád, Lukáš (referee) ; Kavetskyi, Andrii (advisor)
The goal of this thesis is to design and implement an algorithm for detecting exudates and microaneurysms in colored retinal images. These diseases are the first signs of diabetic retinopathy and early detection is crucial. The proposed algorithm begins with preprocessing, where excess background is removed, contrast is enhanced using CLAHE and histogram stretching, and noise filtering is applied. Optic disc localization is based on iterative background removal and row and column variances. Exudates detection is performed based on gamma correction, thresholding and optic disc removal. Microaneurysm detection is based on morphological operations, hit-or-miss transformation and principal component analysis (PCA). The algorithm was tested on 4 datasets with accuracy 73,1 % for exudates and 73,3 % for microaneurysms. The resulting program could assist in automatic disease detection, which could potentially save time for doctors.
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Machine Learning of Representations in Genetic Programming
Pomykal, Šimon ; Piňos, Michal (referee) ; Sekanina, Lukáš (advisor)
The aim of this thesis is to become acquainted with machine learning methods that are used for the automatic design of representations. Specifically, the work focuses on deep learning in the field of genetic programming (GP). Image processing is chosen as a case study, particularly noise reduction methods. By combining the acquired knowledge, a new representation is proposed, intended to replace the syntactic tree in the GP algorithm. This method is obtained using a transformer-type neural network. In conclusion, a modified version of GP that works with the new representation is created. This variant is compared with the original GP using the traditional representation in several experiments.
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Measuring the thickness of contamination layers in scanning electron microscopy using image processing
Macek, Matěj ; Munzar, Milan (referee) ; Čadík, Martin (advisor)
Motivací pro vznik této práce byl cíl společnosti Thermo Fisher Scientific vyvinout metodu měření tloušťky kontaminačních vrstev na snímcích ze skenovací elektronové mikroskopie (SEM) pomocí pokročilých technik zpracování obrazu. Hlavním cílem je vytvořit automatizované metody pro kvantifikaci kontaminace v obrazech, které nepříznivě ovlivňují zobrazování ve výzkumu v oblasti materiálových věd, pomocí technik zpracování obrazu. V této studii shromažďujeme soubor dat snímků s kontaminací a ručně anotujeme masky pro každý snímek. Tyto anotace budou sloužit k doladění a vyhodnocení účinnosti námi navrhovaných metod. Použitím kombinace algoritmů detekce hran a modelů strojového učení, konkrétně vyladěné sítě DeepLabv3, tato práce zvyšuje přesnost a účinnost detekce kontaminace. Analyzátor kontaminace založený na detekci hran (EDCA) využívá tradiční metody zpracování obrazu, zatímco model DeepLabv3 zavádí přístup strojového učení, který robustně zvládá různorodé obrazové podmínky. Srovnávací analýzy prokazují účinnost těchto metod při poskytování spolehlivých, škálovatelných a podrobných měření kontaminačních vrstev, což významně přispívá k rozvoji oboru materiálových věd.
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Detekce karet při turnajích v pokru
Kovalets, Vladyslav ; Šilling, Petr (referee) ; Vaško, Marek (advisor)
This bachelor's thesis focuses on the development of an advanced system for automatic recognition and registration of playing cards from video recordings of poker games. The technology of convolutional neural networks, specifically the YOLO network, was chosen as the basic tool. It enables effective identification of cards on the table and in the hands of players even under challenging conditions. The work involved creating an extensive dataset for training and testing the card detector, which achieved a recognition accuracy of 98.7%. An algorithm was designed to minimize detector errors and improve the overall accuracy of the system. The results of the study suggest that the developed system has potential for use in practice.
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Image processing methods in application to Kármán vortices
Šimůnek, Petr ; Hudec, Martin (referee) ; Himr, Daniel (advisor)
This diploma thesis focuses on flow visualization and image processing methods, with the aim of applying this theory to the practical analysis of fluid flow with particles. The introductory part of the thesis reviews flow visualization methods that are important for understanding fluid behavior in different systems and environments. Then it focuses on image processing methods, that are crucial for the analysis of image data obtained from flow experiments. In the practical part of this thesis, these theoretical insights are applied to the analysis of a series of images of fluid flow with particles in a tube obtained with a camera. The main objective is to describe fluid flow and identify the Kármán vortex, which is generated when the flow passes an obstacle.
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Conversion of fingerprints captured by a mobile device into a standardized format - image editing
Mucha, Vojtěch ; Říha, Kamil (referee) ; Číka, Petr (advisor)
This bachelor thesis deals with the issue of fingerprint conversion taken by a mobile device into a standardized format. In the present day, mobile devices are used more and more often to acquire biometric data, fingerprints included. Processing and standardization of such data is an essential part of the subsequent biometric analysis. The aim of the work is to design and implement an algorithm which would convert a photo of a finger into a grey scale picture of its fingerprint with distinct papillary lines and subdued valleys. The algorithm is implemented in C++ using OpenCV library and a trained neural network for finger detection from hand image. The achieved results are evaluated according to the algorithms for assessing the quality of fingerprints NFIQ 2 and Innovatrics.
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