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Character recognition of machine-written documents
Kindermann, Hubert ; Blažek, Jan (advisor) ; Kolomazník, Jan (referee)
In the present thesis we solve the problem of symbol extraction and recognition from printed documents digitized by the scanner or camera. We introduce a noise resistant algorithm of document lighting normalization. We continue with the extraction of individual characters from the document and their recognition with a system of feedforward multilayer neural networks. We also focus on processing of the resulting set of recognized characters, which is necessary for further use of the extracted text. The last step is correction of the output based on surrounding letters of each character. We have successfully implemented an automatic system containing all the above components.
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Multimodal Image Processing in Art Investigation
Blažek, Jan ; Zitová, Barbara (advisor) ; Sablatnig, Robert (referee) ; Tonazzini, Anna (referee)
A B S T R A C T title: Multimodal Image Processing in Art Investigation author: Jan Blažek department: Department of Image Processing, IITA of the CAS supervisor: RNDr. Barbara Zitová PhD., Institute of Information Theory and Automation supervisor's e-mail address: zitova@utia.cas.cz abstract: Art investigation and digital image processing demar- cate an interdisciplinary field of the presented thesis. Over the past 8 years we have published thirteen papers belonging to this field of research. This thesis presents the current state of the art and puts these papers into context. Our research is focused on modalities in the visible and near-infrared parts of the spectrum and affects vari- ous tasks of art investigation. For studying the spectral response of paint materials, we suggest a low-cost mobile multi-band acquisition system and a calibration method extended by a light source with an adjustable wavelength. We created the m3art database of the spectral responses of pigments, available for comparison and public use. The central point of our research is underdrawing detection and visual- ization. For this purpose we have developed: acquisition guidelines based on optical properties of the topmost non-transparent layer, a visualization technique for comparison of modalities, and a signal separation technique...
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Registration of images of nuclear fuel assembly
Harmanec, Adam ; Blažek, Jan (advisor) ; Šikudová, Elena (referee)
Nuclear fuel is visually inspected during regular shutdowns in order to monitor defects and long-term changes. To enable automatic comparison of images of fuel assemblies, it is crucial to perform their registration, the implementation of which has not yet been published in the scientific literature. In this work we present an analysis of image registration techniques and similarity metrics inspired by the focus operators used in autofocus and shape-from-focus. Their performance has been evaluated using a series of experiments that tested their various properties on a novel data set obtained in cooperation with the research organization Centrum výzkumu Řež. Finally, we present and discuss the results and make recommendations on which to use in which scenario.
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Detection of grids on nuclear fuel set images
Palášek, Jan ; Blažek, Jan (advisor) ; Šikudová, Elena (referee)
Visual inspection of fuel assemblies is necessary to identify potential anomalies in their behaviour associated with their condition and their future usage. One of the possible find- ings are foreign objects caught on the fuel spacer grid which can disrupt the cladding of fuel rods during the operation. The goal of this thesis is to accurately segment the spacer grid from an image, which is a task dual to the foreign object detection, and therefore to automate visual inspection process in this area. We created new datasets covering typical problems appearing on the fuel assembly. To perform the segmentation, we em- ployed neural networks. We increased performance by data augmentation techniques and domain-specific output post-processing. We also measured the algorithm's performance by a newly introduced Line Distance metric, computing the size of the maximum un- certain area between the actual and the predicted transition between grids and rods. In the experiments, we found the best hyperparameters and reached very good results, outperforming our predecessor's algorithm by having three times lower Line Distance metric. 1
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Multimodal Image Processing in Art Investigation
Blažek, Jan ; Zitová, Barbara (advisor)
A B S T R A C T title: Multimodal Image Processing in Art Investigation author: Jan Blažek department: Department of Image Processing, IITA of the CAS supervisor: RNDr. Barbara Zitová PhD., Institute of Information Theory and Automation supervisor's e-mail address: zitova@utia.cas.cz abstract: Art investigation and digital image processing demar- cate an interdisciplinary field of the presented thesis. Over the past 8 years we have published thirteen papers belonging to this field of research. This thesis presents the current state of the art and puts these papers into context. Our research is focused on modalities in the visible and near-infrared parts of the spectrum and affects vari- ous tasks of art investigation. For studying the spectral response of paint materials, we suggest a low-cost mobile multi-band acquisition system and a calibration method extended by a light source with an adjustable wavelength. We created the m3art database of the spectral responses of pigments, available for comparison and public use. The central point of our research is underdrawing detection and visual- ization. For this purpose we have developed: acquisition guidelines based on optical properties of the topmost non-transparent layer, a visualization technique for comparison of modalities, and a signal separation technique...
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Deep Learning for MRI data
Karella, Tomáš ; Pilát, Martin (advisor) ; Blažek, Jan (referee)
The aim of the thesis is the classification of magnetic resonance images by Deep Learning models. The goal was to predict Alzheimer's disease on the dataset created by Alzheimer's Disease Neuroimaging Initiative (ADNI). To prepare the dataset, we built two processing pipelines, which align, normalise and remove irrelevant features from brain scans. We used the processed scans for a 2D and 3D dataset. We designed a few models based on convolutional and previously proposed architectures. Although, many studies published astonishing results on ADNI classification, the results of our experiments do not support previous research in this area. Contrary to what was previously thought, we found that the accuracy strongly depends on the dataset splitting. If we split the dataset by patients, not by scans, the accuracy drops significantly. We presented an overview of several previously published architectures and our experiments showing results of these architectures on the datasets generated by random splitting or subject-based splitting. We also pointed out how the dataset splitting choice changes the performance of our models. The work is a natural extension of study [Fung et al., 2019]. 1
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Automation of nuclear fuel visual inspection
Knotek, Jaroslav ; Blažek, Jan (advisor) ; Horáček, Jan (referee)
The safety and performance of nuclear plant relies, among others, on the quality of nuclear fuel. The quality fulfilling designed criteria of the fuel in use is inspected and reported on periodically. Visual inspection focuses on the condition of the fuel based on its visual properties. During the inspection, the fuel is being recorded and analysed by the inspector. The current state of the fuel assemblies is compared to the historical statistics which helps do decide whether this particular assembly remains or gets replaced. This thesis describe a project initiated by Centrum Výzkumu Řež focusing on digital image processing methods application to visual inspection process. The result of the project is a tool that accelerates the process of report making. Firstly, it transforms the inspection video into one image overview and highlight a significant part (more than 95%) of possible defects to the inspector. 1
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Analyses accompanying creation of law on the example of regulation of new phenomena, the so-called shared economy
Blažek, Jan ; Wintr, Jan (advisor) ; Tryzna, Jan (referee)
Analyses accompanying creation of law on the example of regulation of new phenomena, the so-called shared economy Abstrakt v anglickém jazyce This thesis deals with analyzes preceeding the parliamentary phase of the legislative process on the example of the modern phenomenon, the shared economy. In the case of regulation of a shared economy, the legislator faces a difficult task of regulating yet unregulated, and in such cases, there is a risk that in the event of an incorrect analysis, the regulation may be unfunctional and thus unnecessary. The author chose two analyzes for his thesis, namely analysis of regulatory impact assessment and related explanatory report. The topic becomes more important when we consider that today's era is called the age of legislation. In some ways, it also offers an alternative view of improving the quality of regulation (usually laws), because although the legislator is trying in every way to improve the quality of the Czech legal system, it focuses entirely on the legislative process in the chambers of the Parliament, or adopts new adjustments for the greater transparency of the legislative process. The thesis consists of an introduction, 6 chapters and a conclusion. The chapters are subdivided into subchapters. In the first and second chapter, the author defines the...
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Traffic sign classification by deep learning
Harmanec, Adam ; Blažek, Jan (advisor) ; Kratochvíl, Miroslav (referee)
Classification of road signs has been studied for many years and very promising results have been achieved. We present the analysis of used data sets as very limited for real case classification. In this thesis we analyse publicly available data sets and by merging and extending them, we create a wider and more comprehensive data set applicable in the Czech Republic. Finally, we propose a new convolutional neural network architecture and test it along with several preprocessing techniques on the new data set reaching accuracy of over 99%.
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Multimodal Image Processing in Art Investigation
Blažek, Jan ; Zitová, Barbara (advisor) ; Sablatnig, Robert (referee) ; Tonazzini, Anna (referee)
A B S T R A C T title: Multimodal Image Processing in Art Investigation author: Jan Blažek department: Department of Image Processing, IITA of the CAS supervisor: RNDr. Barbara Zitová PhD., Institute of Information Theory and Automation supervisor's e-mail address: zitova@utia.cas.cz abstract: Art investigation and digital image processing demar- cate an interdisciplinary field of the presented thesis. Over the past 8 years we have published thirteen papers belonging to this field of research. This thesis presents the current state of the art and puts these papers into context. Our research is focused on modalities in the visible and near-infrared parts of the spectrum and affects vari- ous tasks of art investigation. For studying the spectral response of paint materials, we suggest a low-cost mobile multi-band acquisition system and a calibration method extended by a light source with an adjustable wavelength. We created the m3art database of the spectral responses of pigments, available for comparison and public use. The central point of our research is underdrawing detection and visual- ization. For this purpose we have developed: acquisition guidelines based on optical properties of the topmost non-transparent layer, a visualization technique for comparison of modalities, and a signal separation technique...
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