National Repository of Grey Literature 196 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Audio files analysis application
Dřevojánek, Dalibor ; Schimmel, Jiří (referee) ; Přinosil, Jiří (advisor)
This bacherol thesis focuses on RIFF format files, their structure, processing, usage and creating an application, which is able to show the structure of these files and their simple editing. Application is developed using the C# programming language and .NET framework. It can show the structure of a file in a tree view, plot a waveform sotred in an audio file, edit values in some chunks, extract a chunk of a RIFF file, save it to another file and add or remove a chunk from a RIFF file. Application also contains a console version which can be used in evironments without graphical interface. It is developed using integrated development environment Rider from the company JetBrains s.r.o and git repository stored in cloud service GitHub was used for source code storage and preservation.
Update of the exercise demonstrating the signal sampling process to the Signal and Systems Analysis course
Tauber, Jakub ; Přinosil, Jiří (referee) ; Krajsa, Ondřej (advisor)
This thesis is focused on the design and update of a preparation for sampling and quantization of analog signal and signal reconstruction from samples. The process of sampling and quantization of analog signal is described. Subsequently, the design of the sampling fixture and the design of the 8th order low pass filter fixture is carried out. The fixture design is done using the Eagle design program and the simulation was done in LTspice.
Tracking people based on their clothing in multi-camera systems
Sivak, Mykyta ; Přinosil, Jiří (referee) ; Číka, Petr (advisor)
This bachelor thesis focuses on the development and implementation of an algorithm for tracking individuals in multi-camera systems based on clothing pattern analysis. The aim was to design a system capable of tracking an individual in various positions and frames, using the Region of Interest (RoI) technique. The study begins with a comprehensive review of the existing literature on object tracking in video sequences, with a special focus on RoI tracking techniques. During the research, a new algorithm was developed and implemented that utilizes clothing patterns as the primary identification element for tracking and re-identifying individuals across different camera shots. The algorithm was experimentally validated on datasets containing video sequences from various environments, allowing for a detailed analysis of its effectiveness and reliability. The experimental results demonstrate that the proposed system achieves significant accuracy and efficiency compared to traditional methods and is particularly effective in challenging situations where other methods fail. The thesis concludes with an evaluation of the conducted experiments along with recommendations for future extensions and improvements of the system. Potential challenges and ethical aspects, including issues of privacy and personal data processing, are also discussed.
Control and acquisition of data from camera sensor OV2312
Kováč, Dávid ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis deals with the implementation of a driver for the camera sensor OV2312 into the libcamera framework, with the creation of an API interface that allows direct frame capture from a camera in the C++ language and with the creation of a program for demosaicing raw data from the camera sensor for the Raspberry Pi platforms. The aim of this thesis is not only the creation of software that would allow the camera sensor OV2312 to work with Raspberry Pi computers, but will also provide extended control options. The theoretical part describes the single board computers Raspberry Pi, the Libcamera library, the demosaicing process and the troubleshooting procedure. The output of the thesis is a modified Libcamera library that allows the user to capture images and change the parameters of the camera sensor. The created library for direct access to the camera in the C++ language allows to expand the capabilities of the camera sensor. The program for demosaicing provides the user the ability to convert raw data into images.
Lab tasks for dynamic code analysis
Košina, Petr ; Přinosil, Jiří (referee) ; Sysel, Petr (advisor)
The thesis focuses on static and dynamic analysis in software engineering. Static analysis involves examining the source code without executing it, whereas dynamic analysis focuses on executing the code and testing its runtime behavior. The thesis explores various techniques and tools for both types of analysis, including their advantages and limitations. Additionally, the content includes research on the implementation of dynamic code analysis methods across different operating systems. Emphasis is placed on comparing both methods and their application in real-world software environments. Specifically, it provides practical laboratory exercises designed to help students better understand the issues related to dynamic analysis.
Generative Neural Network for Creating Synthetic Photorealistic Images
Hora, Adam ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The main objective of this work is to select and design a neural network model that will be able to generate realistic images thematically fitting the selected dataset. The architecture used for the solution is Deep convolutional generative adversarial network. This network is than implemented in the Python programming language using the Tensorflow application programming interface and its included interface Keras. Finally, the model is trained on the selected dataset and the resulting generated images are presented. The final model and individual images are then evaluated using various quality assessment methods.
QR code detection using deep learning
Černohous, Matěj ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis deals with the design of an algorithm for detecting and decoding QR codes in images using deep learning techniques. The work involved the construction of 2 datasets, a YOLOv7 neural network model for detecting QR codes in images, a YOLOv4-tiny neural network model for detecting position markers of QR codes, and a Python program utilizing these models to read QR codes in images. For evaluation, the algorithm was compared with other options for QR code reading.
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.
Object tracking in video
Boszorád, Matej ; Přinosil, Jiří (referee) ; Rajnoha, Martin (advisor)
This bachelor thesis deals with the issue of tracking multiple objects in a video, specifically focusing on non-learning algorithms. The first chapter represents the theoretical part of the thesis, in which some of the often used tracking methods are described, such as mean-shift, scale-invariant object transformation, Kalman filter, particle filter and Gabor wavelet transformation. These algorithms are broken down by properties they use for proper tracking. The chapter also contains section assignment problem, which is mainly concerned with Hungarian algorithm. The next part describes options of merging multiple tracking methods that are broken down by construction type into parallel, cascade, weighted and discriminatory with example for each one. Moreover there is described adaptability of the tracking system. Bellow are described problems which may occur during tracking and possible solutions to them. This section consists of a solution of image noise, changes in illumination, appearance and extinction of an object, focusing mainly on solving the problem of object occlusion. Within the practical part is created algorithm composed of different types of tracking, the results of which are then compared with selected tracking systems from the multiple object tracking benchmark. The practical part includes the tools used and the explanation of the design, in which the main classes and methods used for the tracking are explained. Besides that, this section describes parallel merging and tracking adaptability . The results of the thesis contain a comparison of the use of tracking techniques separately and together. To compare the results, videos for pedestrian tracking and face tracking were used. This thesis was based on the assumption that merging multiple monitoring systems will help with the improvement of the tracking, which was confirmed by the results.
Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.

National Repository of Grey Literature : 196 records found   1 - 10nextend  jump to record:
Interested in being notified about new results for this query?
Subscribe to the RSS feed.