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Digital image watermarking
Číka, Petr ; Krbilová, Izabela (referee) ; Makáň, Florian (referee) ; Němec, Karel (advisor)
Digital image watermarking has developed for the purpose of protecting intellectual property rights to multimedia data. The focus of this thesis is searching for an alternative solution of digital image watermarking methods. A detailed analysis of watermarking methods particularly in the frequency domain, and the modification of these methods are the main aim of this work. Improved performance in watermark extraction is one of the main goals. First, the common static image watermarking methods, possible attacks on the watermarked data and techniques for objective measurement of watermarked image quality are shortly introduced. Techniques which use the space domain for watermarking ar described in the next part of this work. It is about techniques which insert the watermark into the least significant bits of an image both in the RGB domain and in the YUV domain. The main part of the thesis depicts modified and newly developed static image watermarking methods in the frequency domain. These methods use various transforms and error-correction codes, by means of which the watermark robustness increases. All the methods developed are tested in MATLAB. Results together with tables and graphs are one part of work. The end of the thesis is devoted to a comparison of all the developed methods and their evaluation.
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Objective assessment and reduction of noise in musical signal
Rášo, Ondřej ; Makáň, Florian (referee) ; Krejčí, Jiří (referee) ; Balík, Miroslav (advisor)
The dissertation thesis focuses on objective assessment and reduction of disturbing background noise in a musical signal. In this work, a new algorithm for the assessment of background noise audibility is proposed. The listening tests performed show that this new algorithm better predicts the background noise audibility than the existing algorithms do. An advantage of this new algorithm is the fact that it can be used even in the case of a general audio signal and not only musical signal, i.e. in the case when the audibility of one sound on the background of another sound is assessed. The existing algorithms often fail in this case. The next part of the dissertation thesis deals with an adaptive segmentation scheme for the segmentation of long-term musical signals into short segments of different lengths. A new adaptive segmentation scheme is then introduced here. It has been shown that this new adaptive segmentation scheme significantly improves the subjectively perceived quality of the musical signal from the output of noise reduction systems which use this new adaptive segmentation scheme. The quality improvement is better than that achieved by other segmentation schemes tested.
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Signalling Transmission for Internet Television
Burget, Radim ; Makáň, Florian (referee) ; Vodrážka,, Jiří (referee) ; Komosný, Dan (advisor)
A signalization in an Internet protocol environment is commonly used for monitoring quality of service and other parameters of a network. This thesis is involved in transmission of signalization through internet protocol networks and proposes scalable solution for small and even for large-scale internet television broadcasting. The main contribution of this thesis lies in design and validation of optimal hierarchical tree on the basis of resources assigned. This is done in respect to geographical distance, network distance of each particular member of the hierarchical structure. For the design of algorithms simulations and global experimental network were used.
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Distributed Systems on the .NET Framework Platform
Vítek, Martin ; Makáň, Florian (referee) ; Cvrk, Lubomír (referee) ; Herman, Ivo (advisor)
With the expansion of the Internet communication and related availability of increasing number of services built on different technologies, distributed systems represent a solution to integrate these network services and provide them to users in a coherent form. The .NET Framework which provides an environment for application development in a highly distributed environment of Internet and intranet can be used to achieve this goal. This PhD thesis deals with access to shared resources in the context of distributed systems using the .NET platform. The first part of the work is devoted to describing the basic principles of distributed systems and .NET platform techniques, which can be used for implementation of the principles. For the purposes of request processing having asynchronous nature not only in distributed systems a universal interface for the description of asynchronous operations was designed and implemented. The interface extends standard asynchronous techniques on the .NET platform. In order to address the issue of access to shared resources model was designed based on the principles of object-oriented programming, along with basic algorithm to avoid deadlock in the case of use resources by multiple processes (threads) simultaneously. This extendable model has been successfully implemented and its functionality verified in basic scenarios of access to shared resources. After the definition of resources and their dependencies the implemented model allows working with resources as with any other objects on .NET platform. The synchronization processes proceed transparently in background.
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Keyword Detection in Speech Data
Pfeifer, Václav ; Makáň, Florian (referee) ; Dostál, Otto (referee) ; Balík, Miroslav (advisor)
Speech processing systems have been developed for many years but the integration into devices had started with the deployment of the modern powerful computational systems. This dissertation thesis deals with development of the keyword detection system in speech data. The proposed detection system is based on the Large Margin and Kernel methods and the key part of the system is phoneme classifier. Two hierarchical frame-based classifiers have been proposed -- linear and non-linear. An efficient training algorithm for each of the proposed classifier have been introduced. Simultaneously, classifier based on the Gaussian Mixture Models with the implementation of the hierarchical structure have been proposed. An important part of the detection system is feature extraction and therefor all algorithms were evaluated on the current most common feature techniques. A part of the thesis technical solution was implementation of the keyword detection system in MATLAB and design of the hierarchical phoneme structure for Czech language. All of the proposed algorithms were evaluated for Czech and English language over the DBRS and TIMIT speech corpus.
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Reference Nodes Selection for Anchor-Free Localization in Wireless Sensor Networks
Šimek, Milan ; Makáň, Florian (referee) ; Diviš, Zdeněk (referee) ; Komosný, Dan (advisor)
Dizertační práce se zabývá návrhem nového bezkotevního lokalizačního algoritmu sloužícího pro výpočet pozice uzlů v bezdrátových senzorových sítích. Provedené studie ukázaly, že dosavadní bezkotevní lokalizační algoritmy, pracující v paralelním režimu, dosahují malých lokalizačních chyb. Jejich nevýhodou ovšem je, že při sestavení množiny referenčních uzlu spotřebovávají daleko větší množství energie než algoritmy pracující v inkrementálním režimu. Paralelní lokalizační algoritmy využívají pro určení pozice referenční uzly nacházející se na protilehlých hranách bezdrátové sítě. Nový lokalizační algoritmus označený jako BRL (Boundary Recognition aided Localization) je založen na myšlence decentralizovaně detekovat uzly ležící na hranici síti a pouze z této množiny vybrat potřebný počet referenčních uzlu. Pomocí navrženého přístupu lze znažně snížit množství energie spotřebované v průběhu procesu výběru referenčních uzlů v senzorovém poli. Dalším přínosem ke snížení energetických nároku a zároveň zachování nízké lokalizační chyby je využití procesu multilaterace se třemi, eventuálně čtyřmi referenčními body. V rámci práce byly provedeny simulace několika dílčích algoritmu a jejich funkčnost byla ověřena experimentálně v reálné senzorové síti. Navržený algoritmus BRL byl porovnán z hlediska lokalizační chyby a počtu zpracovaných paketů s několika známými lokalizačními algoritmy. Výsledky simulací dokázaly, že navržený algoritmus představuje efektivní řešení pro přesnou a zároveň nízkoenergetickou lokalizaci uzlů v bezdrátových senzorových sítích.
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Objective assessment and reduction of noise in musical signal
Rášo, Ondřej ; Makáň, Florian (referee) ; Krejčí, Jiří (referee) ; Balík, Miroslav (advisor)
The dissertation thesis focuses on objective assessment and reduction of disturbing background noise in a musical signal. In this work, a new algorithm for the assessment of background noise audibility is proposed. The listening tests performed show that this new algorithm better predicts the background noise audibility than the existing algorithms do. An advantage of this new algorithm is the fact that it can be used even in the case of a general audio signal and not only musical signal, i.e. in the case when the audibility of one sound on the background of another sound is assessed. The existing algorithms often fail in this case. The next part of the dissertation thesis deals with an adaptive segmentation scheme for the segmentation of long-term musical signals into short segments of different lengths. A new adaptive segmentation scheme is then introduced here. It has been shown that this new adaptive segmentation scheme significantly improves the subjectively perceived quality of the musical signal from the output of noise reduction systems which use this new adaptive segmentation scheme. The quality improvement is better than that achieved by other segmentation schemes tested.
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Keyword Detection in Speech Data
Pfeifer, Václav ; Makáň, Florian (referee) ; Dostál, Otto (referee) ; Balík, Miroslav (advisor)
Speech processing systems have been developed for many years but the integration into devices had started with the deployment of the modern powerful computational systems. This dissertation thesis deals with development of the keyword detection system in speech data. The proposed detection system is based on the Large Margin and Kernel methods and the key part of the system is phoneme classifier. Two hierarchical frame-based classifiers have been proposed -- linear and non-linear. An efficient training algorithm for each of the proposed classifier have been introduced. Simultaneously, classifier based on the Gaussian Mixture Models with the implementation of the hierarchical structure have been proposed. An important part of the detection system is feature extraction and therefor all algorithms were evaluated on the current most common feature techniques. A part of the thesis technical solution was implementation of the keyword detection system in MATLAB and design of the hierarchical phoneme structure for Czech language. All of the proposed algorithms were evaluated for Czech and English language over the DBRS and TIMIT speech corpus.
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Signalling Transmission for Internet Television
Burget, Radim ; Makáň, Florian (referee) ; Vodrážka,, Jiří (referee) ; Komosný, Dan (advisor)
A signalization in an Internet protocol environment is commonly used for monitoring quality of service and other parameters of a network. This thesis is involved in transmission of signalization through internet protocol networks and proposes scalable solution for small and even for large-scale internet television broadcasting. The main contribution of this thesis lies in design and validation of optimal hierarchical tree on the basis of resources assigned. This is done in respect to geographical distance, network distance of each particular member of the hierarchical structure. For the design of algorithms simulations and global experimental network were used.
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Reference Nodes Selection for Anchor-Free Localization in Wireless Sensor Networks
Šimek, Milan ; Makáň, Florian (referee) ; Diviš, Zdeněk (referee) ; Komosný, Dan (advisor)
Dizertační práce se zabývá návrhem nového bezkotevního lokalizačního algoritmu sloužícího pro výpočet pozice uzlů v bezdrátových senzorových sítích. Provedené studie ukázaly, že dosavadní bezkotevní lokalizační algoritmy, pracující v paralelním režimu, dosahují malých lokalizačních chyb. Jejich nevýhodou ovšem je, že při sestavení množiny referenčních uzlu spotřebovávají daleko větší množství energie než algoritmy pracující v inkrementálním režimu. Paralelní lokalizační algoritmy využívají pro určení pozice referenční uzly nacházející se na protilehlých hranách bezdrátové sítě. Nový lokalizační algoritmus označený jako BRL (Boundary Recognition aided Localization) je založen na myšlence decentralizovaně detekovat uzly ležící na hranici síti a pouze z této množiny vybrat potřebný počet referenčních uzlu. Pomocí navrženého přístupu lze znažně snížit množství energie spotřebované v průběhu procesu výběru referenčních uzlů v senzorovém poli. Dalším přínosem ke snížení energetických nároku a zároveň zachování nízké lokalizační chyby je využití procesu multilaterace se třemi, eventuálně čtyřmi referenčními body. V rámci práce byly provedeny simulace několika dílčích algoritmu a jejich funkčnost byla ověřena experimentálně v reálné senzorové síti. Navržený algoritmus BRL byl porovnán z hlediska lokalizační chyby a počtu zpracovaných paketů s několika známými lokalizačními algoritmy. Výsledky simulací dokázaly, že navržený algoritmus představuje efektivní řešení pro přesnou a zároveň nízkoenergetickou lokalizaci uzlů v bezdrátových senzorových sítích.
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