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Scalability of genetic programming model
Kozempel, Lukáš ; Přinosil, Jiří (referee) ; Burget, Radim (advisor)
Theme of this thesis is practical realization of so-called Island model which is one of way of parallel genetic programming. First part is theoretical. This part is describing terms of genetic programming, age-layered population structure and island model. In second part of thesis is described realization of island model in Java language.
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Optimization of MR acquisition parameters for the measurement of small objects
Pecháček, Libor ; Přinosil, Jiří (referee) ; Gescheidtová, Eva (advisor)
The subject of my thesis is a design of the methods optimizing, the acquisition of MR signals when small objects measure. The thesis is divided into several parts in order to give a deeper knowledge of the problem. The first part focuses on the theory associated with NMR (Nuclear Magnetic Resonance) and SNR (signal-to-noise ratio). The practical verification of the theory follows. The conclusion of this work is focused on MR images filtering by use of wavelet transform to suppress a noise in the image. The method optimization of MR acquisition parameters for the measurement of small objects is then distributed to the entire work.
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Modern Methods of MR Static Image Enhancement
Zbranek, Lukáš ; Přinosil, Jiří (referee) ; Smékal, Zdeněk (advisor)
The aim of this masters thesis is design and implement an appropriate method for highlighting MR images and the identification of rough edges to provide for division of controlled areas. To this purpose is possible to use the Wavelet analysis. For the simulation environment I using MATLAB entviroment, where introduce the comparison for different types of de-noising and too for different mother wavelets. These methods will be implemented on various MR images of termoromandibular joint.
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Automatic vocal-oriented recognition of human emotions
Houdek, Miroslav ; Přinosil, Jiří (referee) ; Atassi, Hicham (advisor)
This master thesis concerns with emotional states and gender recognition on the basis of speech signal analysis. We used various prosodic and cepstral features for the description of the speech signal. In the text we describe non-invasive methods for glottal pulses estimation. The described features of speech were implemented in MATLAB. For their classification we used the GMM classifier, which uses the Gaussian probability distribution for modeling a feature space. Furthermore, we constructed a system for recognition of emotional states of the speaker and a system for gender recognition from speech. We tested the success of created systems with several features on speech signal segments of various lengths and compared the results. In the last part we tested the influence of speaker and gender on the success of emotional states recognition.
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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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Face recognitions in images
Krhut, Miloš ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
The master thesis deals with the topic of detecting faces in digital images. There are generally described and classified the most frequently used methods and discussed their advantages and disadvantages. More detailed is described skin color detection, eye and mouth detection and are teoretically described machine learning algorithms and detection based on Haar-classifiers. The work aims to implementation of these methods in the OpenCV library, it refers to practical application of them a finally compares different provided trained files.
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Real time face recognizer
Juráček, Aleš ; Přinosil, Jiří (referee) ; Richter, Miloslav (advisor)
My diploma thesis deals about face detection in picture. I try to outline problems of computer vision, artificial intelligence and machine learning. I described in details the proposed detection by Viola and Jones, which uses AdaBoost learning algorithm. This method was deliberately chosen for speed and detection accuracy. This detector was made in programming language C / C + + using the OpenCV library. To a final learning was used database of faces images „MIT CVCL Face Database“. The main goal was to propose the face detector utilizable also in video-sequences.
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SIP client development in JavaME
Janeček, Aleš ; Přinosil, Jiří (referee) ; Kovář, Petr (advisor)
This thesis analyzes various alternatives of SIP protocol implementation on Java Micro Edition devices. This analysis is especially concentrated on SIP protocol, SIP API (JSR-180) and the development in contemporary mobile data networks. I design a midlet for a mobile phone SIP client on the basis of this analysis. The design is especially concentrated on communication, registration and text mesage transfer.
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Adaptive data compression by neural networks
Kučera, Michal ; Přinosil, Jiří (referee) ; Koula, Ivan (advisor)
Point of the work is using of neural networks for the datecompression. This brings new possibilities as by lossless as lossy compression. Draft of a few compress algorithm show the behaviour, advantages and weak points of these systems. As the solution we use knowledge of the layered perceptron Network and we try by the change of the structure and subparameters to teach such network to compress the data, according to our entry requirement. These networks have also advantages, which are meanwhile impediment to the using practically. The goal of this is to try some algorithms, look into their characteristics and posibility of the using. Then propose next posibility solutions and upgrading of these algorithms.
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